Real Block

The different types of ZK-EVMs

delabs@newsletter.paragraph.com (Real Block) — Fri, 12 Aug 2022 06:07:28 GMT

2022 Aug 04 See all posts

Special thanks to the PSE, Polygon Hermez, Zksync, Scroll, Matter Labs and Starkware teams for discussion and review.

There have been many "ZK-EVM" projects making flashy announcements recently. Polygon open-sourced their ZK-EVM project, ZKSync released their plans for ZKSync 2.0, and the relative newcomer Scroll announced their ZK-EVM recently. There is also the ongoing effort from the Privacy and Scaling Explorations team, Nicolas Liochon et al's team, an alpha compiler from the EVM to Starkware's ZK-friendly language Cairo, and certainly at least a few others I have missed.

The core goal of all of these projects is the same: to use ZK-SNARK technology to make cryptographic proofs of execution of Ethereum-like transactions, either to make it much easier to verify the Ethereum chain itself or to build ZK-rollups that are (close to) equivalent to what Ethereum provides but are much more scalable. But there are subtle differences between these projects, and what tradeoffs they are making between practicality and speed. This post will attempt to describe a taxonomy of different "types" of EVM equivalence, and what are the benefits and costs of trying to achieve each type.

Overview (in chart form)

Type 1 (fully Ethereum-equivalent)

Type 1 ZK-EVMs strive to be fully and uncompromisingly Ethereum-equivalent. They do not change any part of the Ethereum system to make it easier to generate proofs. They do not replace hashes, state trees, transaction trees, precompiles or any other in-consensus logic, no matter how peripheral.

Advantage: perfect compatibility

The goal is to be able to verify Ethereum blocks as they are today - or at least, verify the execution-layer side (so, beacon chain consensus logic is not included, but all the transaction execution and smart contract and account logic is included).

Type 1 ZK-EVMs are what we ultimately need make the Ethereum layer 1 itself more scalable. In the long term, modifications to Ethereum tested out in Type 2 or Type 3 ZK-EVMs might be introduced into Ethereum proper, but such a re-architecting comes with its own complexities.

Type 1 ZK-EVMs are also ideal for rollups, because they allow rollups to re-use a lot of infrastructure. For example, Ethereum execution clients can be used as-is to generate and process rollup blocks (or at least, they can be once withdrawals are implemented and that functionality can be re-used to support ETH being deposited into the rollup), so tooling such as block explorers, block production, etc is very easy to re-use.

Disadvantage: prover time

Ethereum was not originally designed around ZK-friendliness, so there are many parts of the Ethereum protocol that take a large amount of computation to ZK-prove. Type 1 aims to replicate Ethereum exactly, and so it has no way of mitigating these inefficiencies. At present, proofs for Ethereum blocks take many hours to produce. This can be mitigated either by clever engineering to massively parallelize the prover or in the longer term by ZK-SNARK ASICs.

Who's building it?

The Privacy and Scaling Explorations team ZK-EVM effort is building a Type 1 ZK-EVM.

Type 2 (fully EVM-equivalent)

Type 2 ZK-EVMs strive to be exactly EVM-equivalent, but not quite Ethereum-equivalent. That is, they look exactly like Ethereum "from within", but they have some differences on the outside, particularly in data structures like the block structure and state tree.

The goal is to be fully compatible with existing applications, but make some minor modifications to Ethereum to make development easier and to make proof generation faster.

Advantage: perfect equivalence at the VM level

Type 2 ZK-EVMs make changes to data structures that hold things like the Ethereum state. Fortunately, these are structures that the EVM itself cannot access directly, and so applications that work on Ethereum would almost always still work on a Type 2 ZK-EVM rollup. You would not be able to use Ethereum execution clients as-is, but you could use them with some modifications, and you would still be able to use EVM debugging tools and most other developer infrastructure.

There are a small number of exceptions. One incompatibility arises for applications that verify Merkle proofs of historical Ethereum blocks to verify claims about historical transactions, receipts or state (eg. bridges sometimes do this). A ZK-EVM that replaces Keccak with a different hash function would break these proofs. However, I usually recommend against building applications this way anyway, because future Ethereum changes (eg. Verkle trees) will break such applications even on Ethereum itself. A better alternative would be for Ethereum itself to add future-proof history access precompiles.

Disadvantage: improved but still slow prover time

Type 2 ZK-EVMs provide faster prover times than Type 1 mainly by removing parts of the Ethereum stack that rely on needlessly complicated and ZK-unfriendly cryptography. Particularly, they might change Ethereum's Keccak and RLP-based Merkle Patricia tree and perhaps the block and receipt structures. Type 2 ZK-EVMs might instead use a different hash function, eg. Poseidon. Another natural modification is modifying the state tree to store the code hash and keccak, removing the need to verify hashes to process the EXTCODEHASH and EXTCODECOPY opcodes.

These modifications significantly improve prover times, but they do not solve every problem. The slowness from having to prove the EVM as-is, with all of the inefficiencies and ZK-unfriendliness inherent to the EVM, still remains. One simple example of this is memory: because an MLOAD can read any 32 bytes, including "unaligned" chunks (where the start and end are not multiples of 32), an MLOAD can't simply be interpreted as reading one chunk; rather, it might require reading two consecutive chunks and performing bit operations to combine the result.

Who's building it?

Scroll's ZK-EVM project is building toward a Type 2 ZK-EVM, as is Polygon Hermez. That said, neither project is quite there yet; in particular, a lot of the more complicated precompiles have not yet been implemented. Hence, at the moment both projects are better considered Type 3.

Type 2.5 (EVM-equivalent, except for gas costs)

One way to significantly improve worst-case prover times is to greatly increase the gas costs of specific operations in the EVM that are very difficult to ZK-prove. This might involve precompiles, the KECCAK opcode, and possibly specific patterns of calling contracts or accessing memory or storage or reverting.

Changing gas costs may reduce developer tooling compatibility and break a few applications, but it's generally considered less risky than "deeper" EVM changes. Developers should take care to not require more gas in a transaction than fits into a block, to never make calls with hard-coded amounts of gas (this has already been standard advice for developers for a long time).

An alternative way to manage resource constraints is to simply set hard limits on the number of times each operation can be called. This is easier to implement in circuits, but plays much less nicely with EVM security assumptions. I would call this approach Type 3 rather than Type 2.5.

Type 3 (almost EVM-equivalent)

Type 3 ZK-EVMs are almost EVM-equivalent, but make a few sacrifices to exact equivalence to further improve prover times and make the EVM easier to develop.

Advantage: easier to build, and faster prover times

Type 3 ZK-EVMs might remove a few features that are exceptionally hard to implement in a ZK-EVM implementation. Precompiles are often at the top of the list here;. Additionally, Type 3 ZK-EVMs sometimes also have minor differences in how they treat contract code, memory or stack.

Disadvantage: more incompatibility

The goal of a Type 3 ZK-EVM is to be compatible with most applications, and require only minimal re-writing for the rest. That said, there will be some applications that would need to be rewritten either because they use pre-compiles that the Type 3 ZK-EVM removes or because of subtle dependencies on edge cases that the VMs treat differently.

Who's building it?

Scroll and Polygon are both Type 3 in their current forms, though they're expected to improve compatibility over time. Polygon has a unique design where they are ZK-verifying their own internal language called zkASM, and they interpret ZK-EVM code using the zkASM implementation. Despite this implementation detail, I would still call this a genuine Type 3 ZK-EVM; it can still verify EVM code, it just uses some different internal logic to do it.

Today, no ZK-EVM team wants to be a Type 3; Type 3 is simply a transitional stage until the complicated work of adding precompiles is finished and the project can move to Type 2.5. In the future, however, Type 1 or Type 2 ZK-EVMs may become Type 3 ZK-EVMs voluntarily, by adding in new ZK-SNARK-friendly precompiles that provide functionality for developers with low prover times and gas costs.

Type 4 (high-level-language equivalent)

A Type 4 system works by taking smart contract source code written in a high-level language (eg. Solidity, Vyper, or some intermediate that both compile to) and compiling that to some language that is explicitly designed to be ZK-SNARK-friendly.

Advantage: very fast prover times

There is a lot of overhead that you can avoid by not ZK-proving all the different parts of each EVM execution step, and starting from the higher-level code directly.

I'm only describing this advantage with one sentence in this post (compared to a big bullet point list below for compatibility-related disadvantages), but that should not be interpreted as a value judgement! Compiling from high-level languages directly really can greatly reduce costs and help decentralization by making it easier to be a prover.

Disadvantage: more incompatibility

A "normal" application written in Vyper or Solidity can be compiled down and it would "just work", but there are some important ways in which very many applications are not "normal":

Contracts may not have the same addresses in a Type 4 system as they do in the EVM, because CREATE2 contract addresses depend on the exact bytecode. This breaks applications that rely on not-yet-deployed "counterfactual contracts", ERC-4337 wallets, EIP-2470 singletons and many other applications.
Handwritten EVM bytecode is more difficult to use. Many applications use handwritten EVM bytecode in some parts for efficiency. Type 4 systems may not support it, though there are ways to implement limited EVM bytecode support to satisfy these use cases without going through the effort of becoming a full-on Type 3 ZK-EVM.
Lots of debugging infrastructure cannot be carried over, because such infrastructure runs over the EVM bytecode. That said, this disadvantage is mitigated by the greater access to debugging infrastructure from "traditional" high-level or intermediate languages (eg. LLVM).

Developers should be mindful of these issues.

Who's building it?

ZKSync is a Type 4 system, though it may add compatibility for EVM bytecode over time. Nethermind's Warp project is building a compiler from Solidity to Starkware's Cairo, which will turn StarkNet into a de-facto Type 4 system.

The future of ZK-EVM types

The types are not unambiguously "better" or "worse" than other types. Rather, they are different points on the tradeoff space: lower-numbered types are more compatible with existing infrastructure but slower, and higher-numbered types are less compatible with existing infrastructure but faster. In general, it's healthy for the space that all of these types are being explored.

Additionally, ZK-EVM projects can easily start at higher-numbered types and jump to lower-numbered types (or vice versa) over time. For example:

A ZK-EVM could start as Type 3, deciding not to include some features that are especially hard to ZK-prove. Later, they can add those features over time, and move to Type 2.
A ZK-EVM could start as Type 2, and later become a hybrid Type 2 / Type 1 ZK-EVM, by providing the possibility of operating either in full Ethereum compatibility mode or with a modified state tree that can be proven faster. Scroll is considering moving in this direction.
What starts off as a Type 4 system could become Type 3 over time by adding the ability to process EVM code later on (though developers would still be encouraged to compile direct from high-level languages to reduce fees and prover times)
A Type 2 or Type 3 ZK-EVM can become a Type 1 ZK-EVM if Ethereum itself adopts its modifications in an effort to become more ZK-friendly.
A Type 1 or Type 2 ZK-EVM can become a Type 3 ZK-EVM by adding a precompile for verifying code in a very ZK-SNARK-friendly language. This would give developers a choice between Ethereum compatibility and speed. This would be Type 3, because it breaks perfect EVM equivalence, but for practical intents and purposes it would have a lot of the benefits of Type 1 and 2. The main downside might be that some developer tooling would not understand the ZK-EVM's custom precompiles, though this could be fixed: developer tools could add universal precompile support by supporting a config format that includes an EVM code equivalent implementation of the precompile.

Personally, my hope is that everything becomes Type 1 over time, through a combination of improvements in ZK-EVMs and improvements to Ethereum itself to make it more ZK-SNARK-friendly. In such a future, we would have multiple ZK-EVM implementations which could be used both for ZK rollups and to verify the Ethereum chain itself. Theoretically, there is no need for Ethereum to standardize on a single ZK-EVM implementation for L1 use; different clients could use different proofs, so we continue to benefit from code redundancy.

However, it is going to take quite some time until we get to such a future. In the meantime, we are going to see a lot of innovation in the different paths to scaling Ethereum and Ethereum-based ZK-rollups.

Blockchain, supply chain collaboration and the era of digital ec…

delabs@newsletter.paragraph.com (Real Block) — Fri, 05 Aug 2022 00:04:35 GMT

This article is the first draft of the author's participation in the preparation of the TBI Trusted Blockchain Promotion Plan "Blockchain Supply Chain Collaborative Application White Paper"

Blockchain, as a technology closer to money, has gradually entered the public eye since 2016 and has been over-promoted. After my beloved Xi Jinping delivered a 1024 blockchain speech, it ignited many students in the blockchain field (including me). ) The fanatical heart. However, the blockchain has begun to be hyped again, technology and applications have also been exaggerated, and all Internet companies have become blockchain companies overnight.

In fact, domestic propaganda is far from the facts, and China's blockchain technology is very popular in Europe and the United States. The beauty of the blockchain we look forward to is a transformation from one system to another, which cannot be achieved overnight. Part of the content of this article is not applied research, but is more inclined to technology application prospects, and part of the content is not achievable by a single technology.

Despite this, we still seem to be able to see that digitization will bring about the beauty of the flow of productivity factors such as land, capital, human resources, knowledge, attention, emotion, etc. across time and space, and look forward to the power of change!

Trust, sharing and collaboration

Purchasing raw materials, producing products, managing inventory, transportation, and trade are the most ancient economic activities. With the development of complex technology, especially information technology, economic activities are constantly developing in the direction of digitization to reduce productivity costs and improve production efficiency.

"The Second East India Expedition Returns to Amsterdam", by Hendrik Cornelisz Vroom, 1599. This painting shows the scene of the Overijssel, Vriesland, Mauritius and Hollandia returning to Amsterdam after the second Dutch trade expedition went to East India in 1599. Amsterdam is shown on the right in the painting.

At the same time, in today’s user-centric and rapidly changing era of globalization, companies no longer rely solely on their own capabilities, but begin to collaborate with partners in the supply chain to meet users’ needs for product lifecycle information and comply with specific policies. Regulatory and audit requirements, rapid response to market changes, and improved competitive advantage.

Collaboration usually occurs between supply chain entities with long-term cooperative relationships. Two or more parties share information based on mutual trust, which brings convenience to the business arrangements and operations of all parties, and improves the carrying capacity and operational efficiency of the entire supply chain. Share the benefits while sharing the risks.

The Estelle Maersk, laden with "trust", slowly docked at the port of Rotterdam in the Netherlands. (Https://url.cn/5zTm22q)

Therefore, trust is the basis and prerequisite for supply chain collaboration, and the long chain, cross-regional, and high complexity characteristics of the supply chain determine that achieving high transparency through information resource sharing is essential for reducing transaction friction and achieving efficient collaboration.

At the same time, trust and information resource sharing are important foundations for the realization of collaborative goal formulation and execution, incentive mechanism arrangements, decision-making synchronization, and collaborative performance management.

Blockchain, a new model of collaboration in the era of digital economy

More than 20 years ago, the Internet became an unprecedented and highly disruptive technology that changed the way of information dissemination in the past. Information digitization has completely changed the foundation of many large-scale mature enterprises, and the widespread adoption of the commercial Internet has brought about the reorganization of supply chain information and value networks.

As a decentralized distributed ledger technology, blockchain is considered to be a new technological revolution that reshapes the value flow relationship on the Internet, or it will become the underlying basic technology for value connection in the digital economy era.

Network interaction diagram of ports and terminals based on the blockchain-based TradeLens digital shipping platform, 2019.12.08. Yellow represents ports and terminals that are directly integrated with TradeLens, and cyan represents ports and terminals that contribute data to TradeLens. (Https://www.tradelens.com/ecosystem/)

TradeLens is a blockchain-based digital shipping platform jointly developed by Maersk and IBM. The current TradeLens ecosystem is composed of more than 100 different organizations, registering more than 10 million shipping events every week, and Tradelens members can capture up to 600 ports and Terminal data, 55 ports and terminals directly integrated interactive data with Tradelens, more than a dozen customs departments participated to improve the visibility, security and automation of the passage. (Https://url.cn/5Q8GWME)

The blockchain connects the supply chain and collaborates with all parties\

Blockchain brings a safe and reliable collaborative environment for the main body of the supply chain\

At the same time, blockchain-based smart contracts exist in the form of codes, which can realize automatic verification and automatic execution of contract terms, and have an important impact on supply chain coordination in terms of trust, time, cost, efficiency, and risk control.

Blockchain strengthens the trust relationship between the parties in the supply chain collaboration\

The longest PoW chain data structure diagram of the Bitcoin blockchain, and the longest chain principle ensures the consistency of data among the nodes of the Bitcoin blockchain. Bitcoin: A Peer-to-Peer Electronic Cash System. (https://bitcoin.org/bitcoin.pdf)

Blockchain has changed the single-point radiation conduction mode of the traditional supply chain collaboration main body information, making the collection, verification, and storage of information more credible, and the information transmission and use are flatter, and information sharing is more convenient. Complex supply chain coordination has compliance from trust basis to realization means, which can bring higher information transparency and visibility to supply chain coordination.

The main application direction of blockchain in the field of supply chain collaboration

Data sharing and visibility\

The establishment of a unified supply chain collaboration platform based on the characteristics of blockchain decentralization and multi-nodes can record the complete product digital footprint of products in the supply chain process from raw material procurement and production to final sales to users, and all information can be accessed instantly All parties in the supply chain do not need to participate through intermediaries that may affect the quality and transparency of information.

The blockchain-based collaboration platform brings greater visibility and control to products and supply chain processes, avoiding unnecessary coordination and miscommunication. Supply chain collaboration partners can promptly discover problems, bottlenecks, and possible unethical behaviors. Instantly understand each other's performance and make better decisions to improve the efficiency of supply chain coordination.

TradeLens digital shipping platform visual interface (Setting Trade Free with TradeLens: A Demonstration.)

At the same time, the integration of supply chain processes based on a transparent and visual shared ledger will further reduce coordination complexity, optimize decision-making synchronization processes, and truly realize the improvement of supply chain synergy performance.

Eliminate intermediate links and data security\

Blockchain is very suitable for coordination in complex processes. For example, international trade is considered to be the most complex link in supply chain practice, involving factories, inland transportation, ports, customs inspections, carriers, shippers, recipients, and For a large number of supply chain stakeholders such as insurance companies and banks, most of the processes are based on paper documents, which can easily cause delays and greatly hinder the flow of goods.

Blockchain can help realize the digitization of paper documents, and establish point-to-point shared records between network participants in real time. The stored and shared data is tamper-proof and anti-manipulation, and the security and accuracy of the data pass through each node The server stores the complete transaction history and can be verified to be guaranteed.

Eliminating intermediate links such as the back-to-back transmission of complex paper documents and unnecessary communication can greatly improve the efficiency of the flow of information, funds, and goods in international trade.

Automatic verification execution and efficient collaboration\

The blockchain-based smart contract can realize automatic verification and automatic execution of terms. Its judgment is based on the public records on the blockchain, rather than the data controlled by any party alone, so it has a high degree of credibility and will Greatly improve the efficiency of collaboration.

Supply chain collaboration partners can convert incentive mechanisms, contract performance arrangements, and risk indicator detection into contract codes. When a new record is entered, the smart contract automatically detects whether the relevant terms are met, such as the consistency of the data on the bill of lading, packing list, waybill, and receipt certificate and the compliance with the contract terms, and then trigger the corresponding contract terms.

The combination of blockchain and IoT can further improve the reliability of data sources and the efficiency of data collection. Combining trusted data recorded on the blockchain with AI can intelligently track inventory, predict demand, detect supply chain environments, and predict risks , Solve a large number of supply chain coordination problems, reduce transaction friction, and improve coordination efficiency.

Blockchain application thinking challenges in the field of supply chain collaboration

Blockchain has brought huge thinking shocks and challenges in the field of supply chain collaboration. The supply chain collaboration based on blockchain requires all parties to break the shackles of the original system, share information resources, optimize or even reshape the business structure, and build a supply chain value community together, and ultimately achieve better products and services and the changes of all parties. Big benefits have brought impacts and challenges to the original mode of information transmission and value transmission

Information transfer\

Distrusted partners are unwilling to collaborate and fear to share information resources, and potential conflicts and injustices may affect the timeliness, accuracy and credibility of data, and have a negative impact on supply chain coordination.

Therefore, successful supply chain coordination requires that all parties to the supply chain have long-term relationships and basic trust, and are willing to share information resources, share benefits, and share risks.

Compared with the collaboration based on a certain center, the distributed data collection, integration, and sharing based on the blockchain-based collaborative approach puts forward higher coordination requirements for the consensus of all parties on the supply chain, the arrangement of incentive mechanisms, and the implementation of common goals and tasks. .

Value transfer\

Multi-party supply chain collaboration can achieve higher returns by creating a value community. It is necessary to think about the architecture and collaboration model of the supply chain from a higher level, involving supply chain process integration, collaborative performance formulation, decision synchronization, incentive mechanism arrangements, etc., which ultimately affect the company Internal business processes and even individual intermediate entities will be replaced, bringing about changes in the entire supply chain and even related industries.

Blockchain, supply chain collaboration and the era of digital ec…

delabs@newsletter.paragraph.com (Real Block) — Thu, 21 Jul 2022 03:36:09 GMT

This article is the first draft of the author's participation in the preparation of the TBI Trusted Blockchain Promotion Plan "Blockchain Supply Chain Collaborative Application White Paper"

Trust, sharing and collaboration

The Estelle Maersk, laden with "trust", slowly docked at the port of Rotterdam in the Netherlands. (Https://url.cn/5zTm22q)

Blockchain, a new model of collaboration in the era of digital economy

The blockchain connects the supply chain and collaborates with all parties\

The geographically dispersed and difficult-to-interoperate management system of the main body of the supply chain raises the threshold and complexity of synergy, which can easily lead to disconnection in the synergy of the supply chain. Blockchain, as a distributed accounting technology, naturally fits the scattered and complex characteristics of supply chain collaboration entities. It can connect the supply chain entities together and provide an efficient basic platform or tool for collaboration.

Blockchain brings a safe and reliable collaborative environment for the main body of the supply chain\

Different from the traditional collaborative management model based on centralized entities for information resource sharing (such as Dell’s supplier collaborative management platform and large customer internal information sharing platform in the late 1990s), the blockchain-based distributed ledger technology can greatly improve The security and reliability of the collaborative environment can effectively solve network attacks, immorality, fraud and other issues in supply chain collaboration.

Blockchain strengthens the trust relationship between the parties in the supply chain collaboration\

The reliability of shared information and the security of data management greatly affect the efficiency of supply chain collaboration. Blockchain is based on the characteristics of decentralization, open and transparent account book data between nodes, and data traceability and non-tampering. It brings a new trust system based on mathematics, provides basic trust tools for information sharing and collaborative cooperation, and can strengthen the main body of supply chain collaboration. Relationship between trust.

The main application direction of blockchain in the field of supply chain collaboration

Data sharing and visibility\

At present, the centralized system of supply chain enterprises (such as ERP system) can only manage supply chain information within the enterprise, and cannot effectively collect and manage every piece of data generated along the supply chain.

TradeLens digital shipping platform visual interface (Setting Trade Free with TradeLens: A Demonstration.)

Eliminate intermediate links and data security\

As a distributed shared ledger, the blockchain provides a basis for removing complex intermediate links-the integrity, consistency, and availability of data are guaranteed by the entire network instead of relying on a centralized middleman.

Automatic verification execution and efficient collaboration\

The complexity of the supply chain leads to frequent errors and inconsistencies in various links, such as document problems, transportation problems, price terms, product standards, and it is extremely difficult to track the implementation of common goals and task progress reached by all parties in the supply chain.

Blockchain application thinking challenges in the field of supply chain collaboration

Information transfer\

From information islands to sharing and collaboration, from centralized sharing and collaboration to distributed data collection, integration, and sharing, the transformation requires a high degree of trust and common and consistent collaboration goals between supply chain entities.

Value transfer\

The main body of the supply chain needs to deal with the challenge of transforming from an individual value center to a value community. Blockchain technology makes supply chain collaboration no longer dependent on a centralized collaboration platform, which can reduce the degree of monopoly of rights, minimize collaboration risks, and bring higher common benefits. However, the current economic winners may be worried about losing profits or dominant positions. resist.

Web3成为主流的3个阻碍——Mirror CTO

delabs@newsletter.paragraph.com (Real Block) — Wed, 20 Jul 2022 04:57:26 GMT

观点来自Mirror CTO @strangechances

“你认为下一个周期 web3成为主流的阻碍是什么?” @strangechances认为主要与 L2 和钱包有关。

1. 产品和项目需要迁移到 L2 网络或在上面启动

扼杀每个周期的原因是以太坊 L1 无法扩展并且使用起来变得昂贵。这一点在 2020 年的“DeFi 之夏”和 2021 年的 NFT 爆发中表现得非常明显。交易费用变得太贵，让人们望而却步。最终，只有鲸鱼才能负担得起在 DeFi 中进行有利可图的交易，而且只有大型投机者才会在 2021 年铸造 Yuga Labs NFT。

2. 交易所需要直接向 L2 提供便宜的入口（只需几美分）

我们不应该期望用户购买 ETH 并桥接到 L2。用户需要通过法币直接从交易所购买 L2 代币，然后将它们廉价地发送到 L2 网络中，以便他们可以使用这些产品。我们应该看看像 Coinbase 这样的应用程序来帮助用户进入 L2。

3. 产品，特别是钱包需要抽象 L2 网络

如今，你使用万事达卡还是维萨卡并不重要。所有的支付处理器都可以处理其中任何一个，并且它们抽象了差异。L2 网络也需要发生同样的事情，钱包很可能需要承担这项任务。

不同的产品将在不同的 L2 上推出。如果我们期望用户浏览所有不同的 L2 会很麻烦，因此钱包（Coinbase Wallet、Rainbow、Argent 等）需要抽象 L2 并提供在它们之间无缝桥接的方法。用户不需要担心：他们拥有 Arbitrum ETH 代币却想使用 Optimism 上的 Mirror该怎么办。

https://g.mirror.xyz/vt5PlXQrz8mTqEo4DHNy_cEWoVfmnAP5ufRf2voCJMw

#stETH脱锚与 #以太坊PoS中心化

delabs@newsletter.paragraph.com (Real Block) — Sat, 11 Jun 2022 05:56:30 GMT

1. 关于stETH与ETH的单向兑换：脱锚本该是常态

stETH由ETH1:1铸造，但兑换是单向，1stETH并不能兑换回ETH。因此，stETH更像是一个带有一定收益（APY4%）的远期合约，而交割日期就是以太坊Merge后信标连上的ETH开放赎回之日。

到这里看来，由于stETH单向兑换问题，其价格应该是低于ETH现价的。

https://dune.com/dataalways/stETH-De-Peg

2. 但是，stETH/ETH的兑换为什么能长时间维持在1:1？

stETH的官方Lido通过年化4%吸引用户前来Stake。与此同时，Lido并通过各种Defi的方式（包括作为MakerDAO抵押物、上线Uniswap、上线Curve池、上线AAVE），上线了二级市场FTX等交易所，为stETH尽可能的提供流动性，使得stETH的价值很难脱锚ETH。

这也促使资金不断涌入Lido。

3. 然而，以太坊正在研究对PoS中心化的打击，会影响stETH的价格

(1) 目前，LIDO拥有超过30%的ETH STAKE份额，这造成了ETH PoS网络的高度中心化，并可能带来治理攻击问题。随着merge的临近，社区不断有人提出stETH的中心化问题，包括交易所stake也存在同样的问题。

https://research.lido.fi/t/should-lido-on-ethereum-be-limited-to-some-fixed-of-stake/2225

(2) 以太坊社区大佬近期纷纷对PoS中心化抛出观点

1）@superphiz表示，鼓励协议自己设置22%的限额。

https://twitter.com/superphiz/status/1525218193756807169

2）@VitalikButerin V神表示，如果一个stake pool的份额超过了15%，就应该收更多的费用直到份额回到15%以下为止。

https://twitter.com/VitalikButerin/status/1525301234516652032

4. stETH对ETH价格的影响：引发DeFi清算

以太坊社区对PoS中心化问题的处理对策，会直接影响stETH本身的价值。与此同时，stETH下跌可能引发DeFi的清算，比如instadapp上的vault 一旦比率跌到0.85 就会触发ETH被大规模清算，此外从情绪上也可能会带动ETH的下跌，甚至波及整个加密市场。

5. 另外，stETH的流动性跟以太坊还是不能比的。

在市场下行的氛围里，越来越多的stETH和ETH存在被抛售的需求，但是低流动性的stETH可能会因为流动性不足导致价格与ETH的脱锚，特别是在极端行情下更容易发生。

【NFT】-热狗MC HotDog

delabs@newsletter.paragraph.com (Real Block) — Fri, 03 Jun 2022 15:11:05 GMT

还没来得及搞清楚各种虚拟币就已经进化到NFT，众声喧哗中元宇宙又突然降临。

两年多的时间身体还困在疫情金钱却展开了新的游戏，虚拟的世界里有海市蜃楼的幻影，真是超屌的灵肉分离。

现在的世界还在受苦，却想像着将来会在元宇宙里跳舞。口罩戴在嘴上又不是遮眼的羞布，大家都看得见是谁在追求财富却佯称是创造艺术，疑似老鼠会临时搭建的一座新灯塔诱惑大家继续当韭菜口味的白老鼠。

国王的新衣这次还是中二老男孩热狗来说破，NFT，Nonstop Fxxking Trouble，这才是写在我们公链上的非同质性，不用加密，独一无二它无法交易，谁也买不走我们人生的真实性。

媒体炒作好说歹说兜售一场梦，曲线图起伏上冲下洗荷包还是空，俗话说币圈一天人间十年，偷油吃的半人半鼠不知何时会滚下来，还不如去推阿姨的三轮车跑得快。

热狗MC HotDog 《NFT》♫

Decentralized Society: Finding Web3’s Soul1

delabs@newsletter.paragraph.com (Real Block) — Mon, 23 May 2022 08:28:29 GMT

E. Glen Weyl,2 Puja Ohlhaver,3 Vitalik Buterin

4 May 2022

"The Dao is the hearth and home of the ten thousand things. Good souls treasure it, lost souls ﬁnd shelter in it.” — Laozi, #62

Abstract

Web3 today centers around expressing transferable, financialized assets, rather than encoding social relationships of trust. Yet many core economic activities—such as uncollateralized lending and building personal brands—are built on persistent, non-transferable relationships. In this paper, we illustrate how non-transferable “soulbound” tokens (SBTs) representing the commitments, credentials, and affiliations of “Souls” can encode the trust networks of the real economy to establish provenance and reputation. More importantly, SBTs enable other applications of increasing ambition, such as community wallet recovery, sybil-resistant governance, mechanisms for decentralization, and novel markets with decomposable, shared rights. We call this richer, pluralistic ecosystem “Decentralized Society” (DeSoc)—a co-determined sociality, where Souls and communities come together bottom-up, as emergent properties of each other to co-create plural network goods and intelligences, at a range of scales. Key to this sociality is decomposable property rights and enhanced governance mechanisms—such as quadratic funding discounted by correlation scores—that reward trust and cooperation while protecting networks from capture, extraction, and domination. With such augmented sociality, web3 can eschew today’s hyper-financialization in favor of a more transformative, pluralist future of increasing returns across social distance.

1 We are grateful to Audrey Tang, Phil Daian, Danielle Allen, Leon Erichsen, Matthew Prewitt, Divya Siddarth, Jaron Lanier, and Robert Miller for their thoughtful feedback and comments. All errors and views are our own. 2 Microsoft Corporation & RadicalXChange Foundation, glen@radicalxchange.org. Glen vinicula este documento a su Alma. 3 Flashbots Ltd., puja@flashbots.net. Puja dedicates this paper to her grandmother, Satya, whose love and light will always shine on many Souls. 4 Ethereum Foundation, vitalik.buterin@ethereum.org.

§1 INTRODUCTION

Web3 has stunned the world by forging a parallel system of finance of unprecedented flexibility and creativity in less than a decade. Cryptographic and economic primitives such as public key cryptography, smart contracts, proof of work, and proof of stake have led to a sophisticated and open ecosystem for expressing financial transactions. Yet the economic value finance trades on is generated by humans and their relationships. Because web3 lacks primitives to represent such social identity, it has become fundamentally dependent on the very centralized web2 structures it aims to transcend, replicating their limitations. Examples of these dependencies include:

Most NFT artists rely on centralized platforms like OpenSea and Twitter to commit to scarcity and initial provenance.
DAOs that try to move beyond simple coin-voting often rely on web2 infrastructure, such as social media profiles, for sybil resistance.
Many web3 participants rely on custodial wallets managed by centralized entities like Coinbase or Binance. Decentralized key management systems are not user-friendly for any but the most sophisticated.

Furthermore, the lack a native web3 identity makes today’s DeFi ecosystem unable to support activities ubiquitous in the real economy, such as undercollateralized lending or simple contracts, like an apartment lease. In this paper, we illustrate how even small and incremental steps towards representing social identity with soulbound tokens could overcome these limitations and bring the ecosystem far closer to regenerating markets with their underpinning human relationships in a native web3 context. Even more promising, we highlight how native web3 social identity, with rich social composability, could yield great progress on broader long-standing problems in web3 around wealth concentration and vulnerability of governance to financial attacks, while spurring a Cambrian explosion of innovative political, economic, and social applications. We refer to these use cases and the richer pluralistic ecosystem that they enable as “Decentralized Society” (DeSoc).

§2 OUTLINE

We begin by explaining the primitives of DeSoc, centered around accounts (or wallets) holding non-transferable (initially public) “soulbound” tokens (SBTs) representing commitments, credentials, and affiliations. Such tokens would be like an extended resume, issued by other wallets that attest to these social relations.

We then describe a “stairway” of increasingly ambitious applications across the social stack such primitives could empower, including: ● establishing provenance ● unlocking undercollateralized lending markets through reputation ● enabling decentralized key management ● thwarting and compensating for coordinated strategic behavior ● measuring decentralization ● creating novel markets with decomposable, shared rights and permissions

This description culminates with a vision of DeSoc—a co-determined sociality, where Souls and communities come together bottom-up, as emergent properties of each other to co-create plural network goods, including plural intelligences, at a range of social scales. Finally, we answer several potential concerns and objections, and make comparisons to other identity paradigms familiar in the web3 space, conceding often how our vision is just a first step but nonetheless an advance in programmable privacy and communication. Then, we consider technical pathways to bootstrap the vision we imagine. Building off these, we look forward, more philosophically, to the potential of DeSoc to redirect web3 to a more profound, legitimate, and transformative path.

§3 SOULS

Our key primitive is accounts, or wallets, that hold publicly visible, non-transferable (but possibly revocable-by-the-issuer) tokens.5 We refer to the accounts as “Souls” and tokens held by the accounts as “Soulbound Tokens” (SBTs). We initially assume publicity despite our deep interest in privacy because it is technically simpler to validate as a proof-of-concept, even if limited by the subset of tokens people are willing to publicly share. Later in the paper, we introduce the concept of “programmable privacy” for richer use cases. Imagine a world where most participants have Souls that store SBTs corresponding to a series of affiliations, memberships, and credentials. For example, a person might have a Soul that stores SBTs representing educational credentials, employment history, or hashes of their writings or works of art. In their simplest form, these SBTs can be “self-certified,” similar to how we share information about ourselves in our CVs. But the true power of this mechanism emerges when SBTs held by one Soul can be issued—or attested—by other Souls, who are counterparties to these relationships. These counterparty Souls could be individuals, companies, or institutions. For example, the Ethereum Foundation could be a Soul that issues SBTs to Souls who attended a developer conference. A university could be a Soul that issues SBTs to

5 We have chosen this set of properties not because they are clearly the most desirable collection of characteristics, but because they are easy to implement in the current environment and permit significant functionality. We explore programmably private SBTs in Section 5.3.

graduates. A stadium could be a Soul that issues SBTs to longtime Dodgers fans.

Note there is no requirement for a Soul to be linked to a legal name, or for there to be any protocol-level attempt to ensure “one Soul per human.” A Soul could be a persistent pseudonym with a range of SBTs that cannot easily be linked.6 We also do not assume non-transferability of Souls across humans. Instead, we try to illustrate how these properties, where needed, can naturally emerge from the design itself.

§4 STAIRWAY TO DESOC

4.1 Art & Soul

Souls are a natural way for artists to stake their reputation on their works. When issuing a tradeable NFT, an artist could issue the NFT from their Soul. The more SBTs the artist’s Soul carries, the easier it would be for buyers to identify the Soul as belonging to that artist, and thereby also confirm the NFT’s legitimacy. Artists could go a step further to issue a linked SBT stored in their Soul that attests to the NFT’s membership to a “collection” and vouches for whatever scarcity limits the artist wishes to set. Souls would thus create a verifiable, on-chain way to stake and build reputation on the provenance and scarcity of an object.

Applications extend beyond art, to services, rentals, and any market built on scarcity, reputation, or authenticity. An example of the latter is verifying the authenticity of purported factual recordings, such as photographs and videos. With advances in deep fake technology, direct inspection by both humans and algorithms will increasingly fail to detect veracity. While blockchain inclusion enables us to trace the time a particular work was made, SBTs would enable us to trace the social provenance, giving us rich social context to the Soul that issued the work—their constellation of memberships, affiliations, credentials—and their social distance to the subject. “Deep fakes” could be readily identified as those artifacts originated outside of time and social context, while trusted artifacts (like photographs) would emerge from the attestation of reputable photographers. Whereas present technology de-contextualizes cultural products (like pictures) and opens them to unchecked, viral attacks lacking social context, SBTs can recontextualize such objects and empower Souls to take advantage of trust relationships already present within communities as a meaningful backstop to protect reputation.

4.2 Soul Lending

Perhaps the largest financial value built directly on reputation is credit and uncollateralized lending. Currently, the web3 ecosystem cannot replicate simple forms of uncollateralized lending, because all assets

6 Note, however, that in principle legal names could be represented themselves as SBTs: a family name would be a membership SBT to a family group and a given name could be a gifted SBT from parents to their child. In fact, richer notions of names would be easy to represent if, for example, other family lines or relations gifted membership SBTs to a new child.

are transferable and saleable—thus simply forms of collateral. The “traditional” financial ecosystem supports many forms of uncollateralized lending, but relies on centralized credit scores to gauge creditworthiness of borrowers who have little incentive to share information about their credit history. But such scores have many flaws. At best, they opaquely overweight and underweight factors relevant to creditworthiness, and bias those who haven’t accumulated sufficient data—mainly minorities and the poor. At worst, they can enable Black Mirror opaque “social credit” systems that engineer social outcomes and reinforce discriminations.

An ecosystem of SBTs could unlock a censorship-resistant, bottom-up alternative to top-down commercial and “social” credit systems. SBTs that represent education credentials, work history, and rental contracts could serve as a persistent record of credit-relevant history, allowing Souls to stake meaningful reputation to avoid collateral requirements and secure a loan. Loans and credit lines could be represented as non-transferable but revocable SBTs, so they are nested amongst a Soul’s other SBTs—a kind of non-seizable reputational collateral—until they are repaid and subsequently burned, or better yet, replaced with proof of repayment. SBTs offer useful security properties: non-transferability prevents transferring or hiding outstanding loans, while a rich ecosystem of SBTs ensures that borrowers who try to escape their loans (perhaps by spinning up a fresh Soul) will lack SBTs to meaningfully stake their reputation. The ease of computing public liabilities with SBTs would open-source lending markets. New correlations between SBTs and repayment risk would emerge, birthing better lending algorithms that predict creditworthiness and thereby reduce the role of centralized, opaque credit-scoring infrastructure. Better yet, lending would likely occur within social connections. In particular, SBTs would offer a substrate for community lending practices similar to those pioneered by Muhammad Yunus and the Grameen Bank, where members of a social network agree to support one another’s liabilities. Because a Soul’s constellation of SBTs represents memberships across social groups, participants could easily discover other Souls who would be valuable co-participants in a group lending project. Whereas commercial lending is a “lend-it-and-forget-it” until repayment model, community lending might take a “lend-it-and-help-it” approach—combining working capital with human capital with greater rates of return. How does uncollateralized community lending get off the ground? At the start, we expect Souls to carry only SBTs that reflect information they are comfortable with sharing publicly, such as information in a CV. While limited in scope, it might be a level of resolution sufficient for intra-community lending experiments to take off, especially if the SBTs are issued by reputable institutions. For example, a constellation of SBTs that show certain programming credentials, participation in several conferences, and work history might be sufficient for a Soul to take a loan (or raise seed capital) for their venture. Such credentials and social relationships already informally play an important, but opaque role in capital allocation like venture capital.

4.3 Not Losing Your Soul

The non-transferability of key SBTs—such as one-time issued education credentials—raises an important question: how do you not lose your Soul? Recovery methods today, like muti-sig recovery or mnemonics, have different tradeoffs in mental overhead, ease of transacting, and security. Social recovery is an emerging alternative that relies on a person’s trusted relationships. SBTs allow a similar, but broader paradigm: community recovery, where the Soul is the intersectional vote of its social network. Social recovery is a good starting point for security, but has several drawbacks in security and usability. A user curates a set of “guardians'' and gives them the power, by majority, to change the keys of their wallet. Guardians could be a mix of individuals, institutions, or other wallets. The problem is a user must balance the desire for a reasonably high number of guardians against the precaution that guardians be from discrete social circles to avoid collusion. Also, guardians can pass away, relationships sour, or people simply fall out of touch, requiring frequent and attention-taxing updates. While social recovery avoids a single point of failure, successful recovery nonetheless depends on curating and maintaining trusted relationships with a majority of guardians.

A more robust solution is to tie Soul recovery to a Soul’s memberships across communities, not curating but instead drawing on a maximally broad set of real-time relationships for security. Recall that SBTs represent memberships to different communities. Some of these communities—like employers, clubs, colleges, or churches—might be more off-chain in nature, while others—like participation in protocol governance or a DAO—might be more on-chain. In a community recovery model, recovering a Soul’s private keys would require a member from a qualified majority of a (random subset of) Soul’s communities to consent.

Social recovery SBT community recovery

Like social recovery, we assume that the Soul has access to secure, off-chain communications channels where “authentication”—through conversation, meeting in person, or confirming a shared secret—can occur. Such communication channels would require greater bandwidth (technically the ability to carry richer “information entropy”) than, for example, on-chain bots or computation over SBTs themselves. Indeed, we can think of SBTs as fundamentally being all about representing participation or access to such authentic—namely high bandwidth—communication channels. Precise details to make this work will require experimentation. How guardians are chosen and how many guardians’ consent is required, for example, are key security parameters for further research. With such a rich information base, however, community recovery should be computationally possible, with security increasing as a Soul joins more distinct communities and forms more meaningful relationships. Community recovery, as a security mechanism, embodies the theory of identity proposed by turn-of-the-20th-century sociologist Georg Simmel—founder of social network theory—in which individuality emerges from the intersection of social groups, just as social groups emerge as the intersection of individuals. Maintaining and recovering cryptographic possession of a Soul requires consent of the Soul’s network. By embedding security in sociality, a Soul can always regenerate their keys through community recovery, which deters Soul theft (or sale): because a Seller would need to prove selling the recovery relationships, any attempt to sell a Soul lacks credibility.

4.4 Souldrops

So far we have explained how Souls can come to represent individuals and reflect their unique traits and solidarities as they acquire SBTs that reflect their affiliations, memberships, and credentials. Such individuation helps Souls build reputations, establish provenance, access uncollateralized lending markets, and protect reputation and identity. But the converse is also true; SBTs also enable communities to be convened at unique intersections of Souls. Thus far web3 has largely relied on token sales or airdrops to summon new communities, which yield little accuracy or precision. Airdrops, in which tokens are algorithmically given for free to a set of wallets, mostly fall to some combination of existing token holders and wallets—easily attacked by sybils, encouraging strategic behavior and the Matthew effect. SBTs offer a radical improvement we call “souldrops.” “Souldrops” are airdrops based on computations over SBTs and other tokens within a Soul. For example, a DAO that wants to convene a community within a particular layer 1 protocol could souldrop to developers who hold 3 out of the last 5 conference attendance SBTs, or other tokens reflecting attendance like POAPs. Protocols could also programmatically weight token drops across a combination of SBTs. We can imagine a non-profit whose mission is to plant trees dropping governance tokens to Souls who hold a mix of environmental action SBTs, gardening SBTs, and carbon sequestration tokens—perhaps dropping more tokens to the carbon sequestration token-holders. Souldrops could also introduce novel incentives to encourage community engagement. Dropped

SBTs could be engineered to be soulbound for a period but eventually “vest” into transferable tokens over time. Or the reverse could be true. Transferable tokens held for some period could unlock the right to SBTs that confer further governance rights over a protocol. SBTs open a rich possibility space to experiment with mechanisms that maximize community engagement and other goals, like decentralization, which we discuss further below.

4.5 The DAO of Souls

Distributed autonomous organizations (DAOs) are virtual communities that come together around a common purpose, coordinated by voting through smart contracts on a public blockchain. While DAOs offer great potential for coordination of global communities across distance and difference, they are vulnerable to sybil attacks where a single user can have multiple wallets to accrue voting power—or in less sophisticated one-token-one-vote style governance, simply hoard tokens to accrue 51% voting power and dispossess the other 49%.

DAOs could mitigate sybil attacks with SBTs in several ways, by:

● computing over a Soul’s constellation of SBTs to differentiate between unique Souls and probable bots, and denying any voting power to a Soul that appears to be a Sybil.

● conferring more voting power to Souls who hold more reputable SBTs—like work or educational credentials, licenses, or certifications.

● issuing specialized “proof-of-personhood” SBTs, which could help other DAOs bootstrap sybil resistance.

● checking for correlations between SBTs held by Souls who support a particular vote, and applying a lower vote weight to voters who are highly correlated.

The latter idea of correlation checking is particularly promising and novel. A vote supported by many Souls who all share the same SBT(s) is more likely to be a Sybil attack and—even if not a Sybil attack—such a vote is more likely to be a group of Souls who are making the same error in judgment or who share the same bias, and so should reasonably be weighted less than a vote with the same numerical level of support but from a more diverse base of participants.7

We explore the latter idea mathematically in greater detail in the context of quadratic funding in the

7 See https://twitter.com/VitalikButerin/status/1264948490834247681 and https://twitter.com/VitalikButerin/status/1265252184813420544 for informal Twitter poll evidence suggesting that people already find the idea of taking diversity into account in decision-making mechanisms intuitive.

Appendix, where we introduce a new primitive, called the “correlation score.” This concept of correlation discounting could be extended to structure deliberative conversations. For example, DAOs susceptible to majoritarian capture could compute over SBTs to bring maximally diverse members together in conversation and ensure minority voices are heard.

DAOs could also rely on SBTs to deter forms of strategic behavior such as “vampire attacks.” In such attacks, a DAO—typically with an associated DeFi protocol of economic value—free-rides off the R&D of another by copying their open-source code and subsequently luring users’ liquidity with a token. DAOs could deter free-riders by first creating a norm around souldropping (perhaps vesting SBTs) only to probable sybil-resistant Souls who delivered liquidity and then withholding souldrops to Souls who shifted their liquidity in a vampire attack. The same mechanism wouldn’t work with airdrops to wallets because a holder can spread liquidity across many wallets to obfuscate their liquidity trail.

DAOs could also use SBTs to make leadership and governance programmatically responsive to their communities. Leadership roles could dynamically shift as the composition of the community shifts—as reflected in the changing distribution of SBTs across member Souls. A subset of members could be elevated to potential officer roles based on their intersectionality and coverage across multiple communities within the DAO. Protocols that value community cohesion could use SBTs to keep intersectional Souls at the center. Alternatively, DAOs may opt for governance that elevates certain combinations of traits more than others, such as diversity among zip codes or participation among a subset of special hobby DAOs.

4.6 Measuring Decentralization through Pluralism

When analyzing real-world ecosystems, it is desirable to measure how decentralized the ecosystem actually is. To what extent is the ecosystem truly decentralized, and to what extent is the decentralization “fake” and the ecosystem de-facto dominated by one or a small set of coordinating entities? Two popular decentralization metrics are the Nakamoto coefficient proposed by Balaji Srinivasan, which measures how many distinct entities need to be combined to gather 51% of some resource, and the Herfindahl-Hirschman index used to measure market concentration for antitrust purposes, calculated by summing the squares of the market shares of the market participants. These approaches, however, leave open key questions of what are the correct resources to measure, how to deal with partial coordination, and the gray areas in what constitutes a “distinct entity.” For example, nominally independent firms may have many major shareholders in common, have directors who are friends with each other, or be regulated by the same government. In the context of token protocols, measuring decentralization of token holdings by looking at on-chain wallets is wildly inaccurate because many people have multiple wallets, and some wallets (e.g., exchanges) represent many people. Moreover, even if addresses could be traced back to unique individuals, those individuals could be socially correlated groups prone to accidental coordination (at best) or intentional collusion (at worst). A better

way of measuring decentralization would capture social dependencies, weak affiliations, and strong solidarities.

Miners and mining pool operators that together make up 90% of Bitcoin’s hashpower sitting together on a conference panel.

SBTs support a different way of measuring the level of decentralization (or pluralism) in a DAO, protocol, or network. ● As a first step, protocol could limit token voting to reasonably sybil-resistant (or SBT rich) Souls. ● As a second step, a protocol could examine the correlations between SBTs held by different Souls and discount votes by Souls (pooling them as only partially separate) if they share a large number of SBTs. (We explore the latter idea mathematically in greater detail in the context of quadratic funding in Appendix A, where we introduce a new primitive, called the “correlation score.”) ● As a third step, to zoom out and get a sense of the decentralization across the network, one could measure the correlations between SBTs held by Souls among and across different layers of the network stack—measuring correlations in voting, token ownership, governance-related communication, and even control over computational resources. SBTs allow us to begin to measure the decentralization of an interoperating and layered ecosystem

that is very difficult to measure at all today. There is still a large, open question of what formulas would best capture what we want to measure and be least vulnerable to manipulation. There are also many questions about how to examine the relationships of SBTs—weighting some SBTs more than others, discounting nested SBTs, or also factoring in the composition of transferable tokens within Souls. However, with a rich ecosystem of Souls and SBTs, a much larger amount of data would be available to make these calculations and move towards meaningful decentralization.

4.7 Plural Property

DAOs often own—or organize around owning—assets, both in the virtual and physical worlds. So far web3’s scope has largely been limited to a narrow class of property whose bundle of rights are wholly transferable: tokens, NFTs, artworks, first editions or rare manuscripts like the U.S. Constitution. But the emphasis on transferability has been to web3’s detriment, making it incapable of representing and supporting some of the simplest and ubiquitous property contracts today, such as apartment leases. Property rights are defined in the Roman legal tradition as bundles of rights to use (“usus”), consume or destroy (“abusus”), and profit (“fructus”). Rarely are all these rights jointly vested in the same owner. Apartment leases, for example, confer limited rights of use (“usus”) to the lessor, but not unfettered rights to destroy the apartment (“abusus”), sell it off (“fructus”), or even transfer use (subletting). Rights of real property (land) are typically encumbered by a range of restrictions on private use, grants of public rights of access, limits on rights of sale, and even rights of purchase by eminent domain. They are also typically encumbered with mortgages that transfer some financial value to lenders. The future of property innovation is unlikely to build on wholly transferable private property so far imagined web3. Rather innovation will hinge on the ability to decompose property rights to match features of existing property regimes, and code even richer elaborations. Corporations and other organizational forms evolved precisely to reconfigure property rights in even more creative ways—for example, granting employees access to proprietary facilities (“usus”), but reserving for managers rights to change or damage assets (“abusus”), while paying shareholders most financial benefit (“fructus”). SBTs have the flexibility to represent and proliferate such nuanced property rights of both physical and virtual assets, while encouraging new experiments. Here are just a few use cases: ● Permissioning access to privately or publicly controlled resources (e.g., homes, cars, museums, parks, and virtual equivalents). Transferable NFTs fail to capture this use case well because often access rights are conditional and non-transferable: if I trust you to enter my backyard and use it as recreational space, that does not imply that I trust you to sub-license that permission to someone else.

● Data Cooperatives where SBTs grant data access to researchers, while instantiating members’ rights to grant access (perhaps by quadratic vote) and bargain for economic rights to discoveries and intellectual property born out of research. We explore this further in

Section 4 on Plural Sensemaking.

● Experiments with local currencies with rules that make them more valuable to hold and spend by Souls who live in a particular region or are part of a particular community.

● Experiments in participation where SBTs create a continuous basis for less contextualized Souls (e.g., immigrants, adolescents) to gain influence within novel and broader networks. Such Souls would begin with narrow SBTs that pool them with their families or local communities. As their affiliations gradually diversify, they would gain broader SBTs that instantiate voting rights to influence broader networks—in the spirit of Danielle Allen’s idea of polypolitanism—a process that currently is mediated by arbitrary age and residence cut-offs.

● Experiments in market design, such as Harberger taxation and SALSA (self-assessed licenses sold at auction), where holders of an asset post a self-assessed price at which anyone else can buy the asset from them, and must periodically pay a tax proportional to the self-assessed price to maintain control. SBTs could be used to create more nuanced versions of SALSA—for example, where rights of participation are approved by the community to minimize strategic behavior from within or outside the community.

● Experiments in democratic mechanism design such as quadratic voting. Holders of SBTs representing membership in a community could quadratically vote on parameters such as incentives and tax rates. Ultimately, “markets” and “politics” are not separate design spaces; SBTs can be a major part of a technological stack that enables the entire space between the two categories to be explored. Provision of public goods through quadratic funding is another such intersection.

Of course, there are dystopian scenarios to consider. Immigration systems could be permissioned with migratory SBTs. Regulatory capture could be codified in nested community tokens, where homeowners have a disproportionate voting power and stall housing construction. SBTs could automate red-lining. As we discuss further below, these scenarios should be considered within the context of the current opaque-top-down permissions and discriminations. SBTs make discrimination more transparent and therefore potentially contestable.

4.8 From Private and Public Goods to Plural Network Goods

More generally, SBTs could allow us to effectively represent and manage assets and goods that are anywhere on the spectrum between being fully private and fully public. In reality, almost everything is on the spectrum: even goods for personal consumption have positive spillovers, such as making the

consumer better able to contribute to their family or community, and even the most globally available public goods (e.g. climate) are inevitably more useful to some people than others (e.g. Seychelles v. Siberia). Similarly, human motivation is rarely fully selfish or fully altruistic; there are many patterns of pre-existing cooperation, and some more present among certain communities over others. Yet mechanism design today assumes atomized, selfish agents without pre-existing cooperation, often making mechanisms vulnerable to innocent over-coordination,8 at best, and intentional collusion, at worst, by groups who are already cooperative. Thus, even the best public funding models, including Quadratic Funding (QF), can’t scale. QF encourages coordination by offering diminishing rewards to concentrated action of the few, but increasing rewards to collective action of the many; for example, a total of $1 contributed equally by 10 people is matched by $99 to generate $100 in total, while $10 contributed by a single person receives no match. Mathematically, this is accomplished by matching funds proportional to the square of the sum of the square roots of individual contributions (as we further elaborate in the Appendix). But even weak cooperation (say donating $1 to a cause) among large groups (say most citizens of China) would dominate the system and absorb all its matching funds because the premium QF puts on the number of unique contributors. As is, QF doesn’t discount coordination among correlated, special interests that may swamp a QF round, but instead rewards it. But rather than treating pre-existing cooperation as a bug we ought to “write over,” the key is to acknowledge it as reflecting partial cooperation that we should harness and compensate for. Afterall, we are in the business of encouraging cooperation. The trick is to make quadratic mechanisms work alongside pre-existing networks of cooperation, correcting for their biases and tendencies to over-coordinate. SBTs offer a natural way by allowing us to tip the scales in favor of cooperation across diﬀerences. As Nobel Laureate Elinor Ostrom famously highlighted, the problem is less coordinating public goods per se but rather one of helping communities made up of imperfectly cooperative but socially connected individuals overcome their social differences to coordinate at scale in broader networks. If SBTs represent community memberships that reflect a Soul’s partialities, favoring cooperation across differences simply means discounting cooperative rewards to similarly affiliated or correlated Souls—similarity measured by their shared SBTs. The assumption is that consensus between the diﬀerently affiliated better signals plural goods across broader networks, whereas consensus between the similarly affiliated more likely signals over-coordinated (or colluded) goods serving narrower interests. By revealing shared memberships across Souls, SBTs allow us to discount pre-existing cooperation and quadratically scale up plural goods that confer benefits widely across emergent networks—agreed upon by the most diverse members—rather than more narrow goods innocently over-coordinated (or intentionally colluded) by special interests. The precise formula for correlation discounting “optimally” depends on model details and has not yet been studied, but we provide a first pass for experimentation for

8 We say “innocent,” because highly-cooperative groups naturally will seek to advance their interests, which may very well be for their collective benefit.

further research in the Appendix.

§5 PLURAL SENSEMAKING

An example of plural network goods that are of increasing salience in a digital world are predictive models built off user data. Both artificial intelligence (AI) and prediction markets seek to predict future events based on data primarily elicited from people. But both paradigms are limited in different and nearly opposite ways. The dominant paradigm in AI eschews incentives, instead hoovering up (public or privately surveilled) data feeds and synthesizing them into predictions through proprietary large-scale, non-linear models—harnessing the default web2 monopoly on “usus” without any “fructus” flowing to data laborers. Prediction markets take the opposite approach, where people bet on outcome in the hopes of financial gains, relying entirely on economic incentives of financial speculation (“fructus”) without synthesizing the beliefs of bettors to produce composable models. At the same time, both of these paradigms yield conclusions that are characterized as “objective” truths; whereas AI models are portrayed as “universal” or “generally intelligent,” prediction markets are portrayed as summarizing all the beliefs of the market participants in a single number: equilibrium price. A more productive paradigm is to eschew these extremes, and instead draw on the virtues of both, while compensating for their weaknesses and enriching their breadth. We propose thoughtfully combining the complexity of non-linear AI models with the market incentives of prediction markets to transform passive data laborers into active data creators. With such provenance-rich information rooted in the sociality of data creators, we illustrate how DeSoc can unlock plural network(ed) intelligence more powerful than either approach.

5.1 Prediction Markets to Prediction Plurality

Prediction markets aim to aggregate beliefs based on wealth and risk preferences of those willing to bet—money talks. But this “survival of the fittest" isn’t a desirable way to aggregate beliefs. A zero-sum game where one trader’s gain is another’s loss assumes a generalized ability at prediction that wrests with “the smart” and not “the dumb.” While wealth may be a proxy for some forms of ability and expertise, predictions that account for other forms of relative expertise may be more reliable. Participants who have lost bets in a particular domain, may have more accurate beliefs in another domain. But prediction markets have the unfortunate effect of eliciting beliefs of those prone to gambling, which enriches those who win bets, impoverishes the rest, and discourages general participation of the risk-averse. There are better ways to elicit beliefs. Research suggests that while prediction markets generally outperform simple polling, they don’t outperform sophisticated team prediction polling, where people have incentives to share and discuss information. Under team deliberation models, members can be weighted based on factors like past performance and peer evaluation, and the team participates in semi-structured discussions to pool information that can’t be encapsulated simply in a buy or sell contract. Such team deliberation models can be further improved with quadratic rules to elicit exact probability estimates

from all participants (compared to prediction markets, which only elicit up-down views about the current price equilibrium).9 It has been demonstrated that the amount of contracts that people have an incentive to buy reflects their subjective probability assessment.10 Such markets also distribute the gains from participation much more equally, rewarding accuracy without bankrupting the rest and thus keeping everyone as participants for future rounds. SBTs could unlock a new class of rich models and experiments in predictive power and relative expertise. Whereas prediction markets elicit one number—the price of a contract—quadratic polling elicits each participant’s exact belief about the probability of an event. SBTs enable further computation over those beliefs in social context of the education credentials, memberships, and general sociality of a participant to develop better weighted (or non-linearly synthesized) predictive models, likely surfacing expert predictors at novel, unforeseen intersections. So even if a poll did not aggregate beliefs well, polls could be studied retroactively to uncover the characteristics of “more correct” participants and convene better tailored “experts” in future polls, perhaps in a deliberative team context. These mechanisms are closely related to those we advocate throughout this paper. In the same way that quadratic mechanisms discounted by correlation scores can transform poorly coordinated top-down public goods into powerful, bottom-up plural network goods, they can also transform governance systems based on zero-sum prediction markets that incent participants to hide their information (e.g., Futarchy) into more positive-sum plural sense-making that can encourage revelation and synthesis of new and better information.

5.2 Artificial Intelligence to Plural Intelligence

Large scale n on-linear “neural network” models (such as BERT and GPT-3) could also be transformed by SBTs. Such models hoover volumes of public or privately surveilled data feeds to produce rich models and predictions, such as code based on natural language prompts. Most surveilled data creators aren’t aware of their role in creating these models, retain no residual rights, and are viewed as “incidental” rather than as key participants. Moreover, data hoovering divorces models from their social context, which masks their biases and limitations and undermines our ability to compensate for them. These tensions have increasingly come to the fore with growing demand for data availability, new initiatives like “data sheets for data sets” that document data provenance, and privacy-preserving approaches to machine learning. Such approaches require giving meaningful economic and governance stakes to those who generate the data and incenting them to cooperate in producing models more powerful than what they could build alone. SBTs offer a natural way to program economic incentives for provenance-rich data while

9 Under a quadratic rule, team members can buy a contract that pays out $X conditional on an event occurring, but costs $(X^2)/2. For example, an individual who sets X=0.5 will receive $0.5 if the event occurs—paid by the poller—and will pay $0.125 regardless. 10 If an individual assesses probability p, their expected payoff is pX and cost is X^2/2. Taking the derivative with respect to X, the optimality condition is p=X, assuming risk neutrality, which is reasonable for small stakes (both the payoff and the cost may be arbitrarily scaled down or up and the same argument holds).

empowering data creators with residual governance rights over their data. In particular, SBTs allow carefully and proportionately targeted incentives for data (and data quality) at individuals and communities based on their characteristics. At the same time, model-makers can track the characteristics of the collected data and their social context—as reflected by SBTs—and find contributors that offset biases and compensate for limits. SBTs can also program bespoke governance rights to data creators, allowing them to form cooperatives that pool data and negotiate uses. This bottom-up programmability by data creators enables a future of plural intelligences, where model-makers can compete to negotiate uses over the same data to build different models. Thus, we move away from a paradigm of a detached monolithic “artificial intelligence” free from human origins, hoovering up provenance-free surveilled data to instead a Cambrian explosion of cooperatively constructed plural intelligences rooted in social provenance and governed by Souls. Over time, just as SBTs individuate a Soul, they also come to individuate models—embedding data provenance, governance and economic rights directly into the model’s code. Thus, plural intelligences—like humans—build a Soul embedded in human sociality. Or depending on how you look at it, humans evolve over time embedded in plural intelligences—each with a unique Soul, complementing and cooperating with other Souls. And, in this, we see the convergence of the prediction market and AI paradigms towards plural sense-making, combining widely distributed incentives and careful tracking of social context to create a diversity of models that combine the best of both approaches into a technology paradigm more powerful than either.

5.3 Programmable Plural Privacy

Plural intelligences raise important questions about data privacy. Afterall, to build such powerful intelligences requires pooling data across individuals from large data sets (e.g., health data), or capturing data that isn’t interpersonal but shared (e.g., a social graph). “Self-sovereign identity” advocates tend to treat data as private property: data about this interaction is mine and so I should be able to choose when and to whom to reveal it. However, even more than in the physical economy, the data economy is poorly understood in terms of simple private property. In simple two-way relationships, such as an illicit affair, the right to reveal information is usually symmetrical, often requiring mutual-permission and consent. As scholar Helen Nissenbaum highlights, the concern is not “privacy” as such but lack of integrity to c ontext in the sharing of information. The Cambridge Analytica scandal was largely about people revealing properties of their social graph and information about their friends, without their consent. Rather than privacy-as-transferable-property-right, a more promising approach is to treat privacy as a programmable, loosely coupled bundle of rights to permission access, alter or proﬁt from information. Under such a paradigm, every SBT—such as an SBT that represents a credential or access to a data store—would ideally also have an implied programmable property right specifying access to the underlying information constituting the SBT: the holders, the agreements between them, the shared property (e.g., data), and obligations to 3rd parties. For example, some issuers would choose to make SBTs wholly public. Some SBTs, such as a passport or health record, would be private in the self-sovereign sense,

with unilateral rights to disclose by Souls who carry the SBT. Others, such as SBTs that reflect membership of a data cooperative, would have multi-signature or more sophisticated community voting permissions, where all or a qualified majority of SBT holders must consent to disclosure. While there are current technical questions (can SBTs be programmed in such a way?) and important questions around incentive compatibility (explored further in Section 7)—we nonetheless think programmable plural privacy warrants further research and offers key advantages over alternative paradigms. Under our approach, SBTs have the potential to enable privacy as a programmable, composable right that can map upon the complex set of expectations and agreements we have today. Moreover, such programmability could help us reimagine new configurations, as there are an inﬁnite number of ways privacy—as a right to permission access to information—could be composed with “usus,” “abusus,” and “fructus” to create a nuanced constellation of access rights. For example, SBTs could permission computations over data stores—perhaps owned and governed by a plurality of Souls—using a specific privacy preserving technique. Some SBTs may even permission access to data in a way where certain computations can be made, but the results cannot be proven to third parties. A simple example is a vote: the voting mechanism needs to tally votes from every Soul, but votes should not be provable to anyone else to prevent vote buying. Communication is perhaps the most canonical form of shared data. Yet today’s communication channels lack both user control and governance (“usus” and “abusus”) and at the same time auction user attention (“fructus”) to the highest bidder—even if a bot. SBTs have the potential to steward healthier forms of the “attention economy” that empowers Souls to spam-filter inbounds from likely bots outside of their social graph, while elevating communication from real communities and desired intersections. Listeners could become more aware of who they are listening to and better able to assign credit to works that spur insights. Rather than optimizing for maximum engagement, such an economy could optimize for positive-sum collaborations and valuable co-creations. Such communication channels also are important for security; as noted above, “high bandwidth” communication channels are critical to building the security foundations of community recovery.

§6 DECENTRALIZED SOCIETY

Web3 aspires to transform societies broadly, rather than merely financial systems. Yet today’s social fabric—families, churches, teams, companies, civil society, celebrity, democracy—is meaningless in virtual worlds (often called the “metaverse”) without primitives representing human souls and the broader relationships they support. If web3 eschews persistent identities, their patterns of trust and cooperation, and their composable rights and permissions, we see, respectively, sybil attacks, collusion, and a limited economic realm of wholly transferable private property—all of which trends towards hyper-financialization. To skirt hyper-financialization—yet unlock exponential growth—we propose augmenting and bridging our sociality across virtual and physical realities, empowering souls and communities to encode rich

social and economic relationships. But simply building on trust and cooperation is not enough. Correcting for biases and tendencies to over-coordinate (or collude) among trust networks is essential to encouraging more intricate, diverse relationships that span greater social distances than before. We call this “Decentralized Society (DeSoc)”: a co-determined sociality, where Souls and Communities convene bottom-up, as emergent properties of each other to produce plural network goods across different scales.

We emphasize plural network goods as a feature of DeSoc, because networks are the most powerful engine of economic growth, yet the most susceptible to dystopian capture by private actors (e.g., web2) and powerful governments (e.g., Chinese Communist Party). Most significant economic growth results from increasing network returns, where every additional unit of input yields incrementally more output. Examples of simple physical networks include roads, electrical grids, cities, and other forms of infrastructure built off labor and other capital inputs. Examples of powerful digital networks include marketplaces, predictive models and plural intelligences built off data. In both cases, network economics diverges from neoclassical economics, which teaches decreasing returns—where every additional unit of input yields incrementally less output—and where private property yields the most efficient outcomes. Private property applied to an increasing returns context has the opposite effect—throttling network growth by rent extraction. A road between two cities can unlock increasing returns from gains from trade. But the same road privately owned can throttle growth if the owners choose to extract rent up to the value trading between the two cities. Public ownership over a network also has its own perils, being susceptible to regulatory capture or underfunding.

Networks with increasing returns are most efficient when treated neither as purely public nor purely private goods, but rather as partial and plural shared goods. DeSoc provides the social substrate to unbundle and reconfigure rights—rights of use (“usus”), rights to consume or destroy (“abusus”), and rights of profit (“fructus”)—and enable efficient governance mechanisms across these rights that augment trust and cooperation while checking for collusion and capture. We’ve explored several mechanisms throughout this paper, such as community-based SALSA and quadratic funding (and voting) discounted by correlation scores. This third way of partial and plural ownership avoids the Charybdis of private rent extraction and Scylla of public regulatory capture. In many ways, DeFi today is a decreasing returns private property paradigm retrofitted onto increasing returns networks. Built on the premise of trustlessness, DeFi is inherently limited to the realm of wholly transferable private property (e.g., transferable tokens) that mostly bundles “usus,” “abusus,” and “fructus.” At best, DeFi risks throttling network growth by rent extraction and at worst risks ushering in dystopian surveillance monopolies dominated by “whales'' who harvest and hoover up data in a race-to-the-bottom—much like web2.

DeSoc transforms DeFi’s race to control and speculate on the value of networks into a bottom-up coordination to build, participate, and govern them. At minimum, DeSoc’s social substrate can make DeFi

sybil-resistant (enabling community governance), vampire-resistant (internalizing positive externalities to build an open-source network), and collusion-resistant (preserving a network’s decentralization). With DeSoc’s structural corrections, DeFi can support and expand plural networks that confer benefits broadly—as agreed upon by the most diverse members—rather than further entrenching networks captured by narrow interests. Yet, the greatest strength of DeSoc is its network composability. Sustained increasing returns and network growth isn’t simply avoiding the perils of rent extraction, but also encouraging the proliferation and intersection of nested networks. A road may form a network between two cities. But cut off from broader cooperation, two cooperating cities will eventually hit a ceiling of diminishing returns—either because of congestion (roads and housing) or exhaustion (reaching the limits of the people they can serve). Only through technological innovation and growing broader, if looser, cooperation with neighboring networks for new sources of increasing returns can value continue to grow exponentially. Some cooperation will be physical, incrementally extending physical trade across space. But many more connections will be informational and digital. Over time, we will see new matrices of cooperation between physical and digital networks, reliant upon and extending the social interconnections they are built on. It is precisely this intersecting, partly nested structure of ever growing network cooperation across digital and physical worlds that DeSoc enables. Through composing networks and coordination, DeSoc emerges at the intersection of politics and markets—augmenting both with sociality. DeSoc empowers the vision of JCR Licklider—founder of ARPANET that created the internet—of “man-computer symbiosis” in an “intergalactic computer network” with dramatically increased social dynamism built on trust. Rather than build on DeFi’s trustless premise, DeSoc encodes trust networks that underpin the real economy today and enables us to harness them to generate plural network goods resilient to capture, extraction, or domination. With such augmented sociality, web3 can eschew short-term hyper-financialization in favor of an unbounded future of increasing returns across social distance.

6.1 Souls can go to Heaven…or Hell

While we have selectively highlighted the potential unlocked by DeSoc that we find promising, it is important to remember that almost any technology with such transformative potential will have a similar potential for destructive transformation: fire burns; the wheel steamrolls; the television brainwashes; cars pollute; credit cards trap in debt, and so on. Here, the same SBTs that could be used to compensate for in-group dynamics and achieve cooperation across differences could also be used to automate red-lining of disfavored social groups or even target them for cyber or physical attack, enforce restrictive migration policies, or make predatory loans. Many of these possibilities are less salient in the current web3 ecosystem because they aren’t meaningful concepts given the current substrate. Enabling upsides of DeSoc also enables these harms. Just as the downside of having a heart is that a heart can be broken, the downside of having a Soul is it can go to hell and the downside of having a society is that societies are often animated by hatred,

prejudice, violence and fear. Humanity is a great and often tragic experiment.

As we meditate on the possible dystopias of DeSoc, we should also contextualize these possibilities within other technological enabled dystopias. Web2 is architecture for opaque authoritarian surveillance and social control. Whereas web2 often relies on top-down artificial bureaucracies to confer identity (a “driver’s license”), DeSoc relies on horizontal (“peer-to-peer”) social attestations. Whereas DeSoc empowers Souls to encode their own relationships and co-create plural property, web2 intermediates social connections or monetizes them with opaque algorithms that can polarize, divide, and misinform. DeSoc sidesteps top-down, opaque social credit systems. Web2 forms the basis of them. DeSoc treats Souls as agents, whereas web2 treats Souls as objects. The risk of social control with DeFi—without any identity substrate—is less, at least in the near-term. But DeFi has its own dystopia. While DeFi overcomes explicit forms of centralization—where specific actors have an outsized level of formal power within a system—it has no built-in way to overcome implicit centralization through collusion and market power. Monopolies don’t always surface as the Standard Oils of the past. Collusion can even happen at higher and far-removed levels of an ecosystem. We see this today with the rise of a class of institutional asset managers (e.g., Vanguard, BlackRock, State Street, Fidelity, etc.) that are the largest shareholders of all the largest banks, airlines, car companies, and other major industries. Because such asset managers hold a stake across all rivals within an industry (i.e. a stake in every major airline), their incentive is to make the companies that they hold look like a competing industry but act like a monopolist that maximizes industry-wide profits and entrenchment at consumer and general-public expense.11 In DeFi too, the same “whales” and VCs accumulate larger shares across each level of the stack and across competitors within a stack, perhaps voting in token governance, or delegating it to the same class of delegates, who are also similarly correlated across the network. Without any social substrate for sybil-resistance and correlation discounts to force-function decentralization, we should also expect to see more monopolies funded by whales, as monopolists increasingly become the largest pool of available investment capital. As “the money class” and users diverge, we should expect to see (and already see) greater and greater levels of incentive misalignment and rent extraction. If DeFi applications that deal with private data emerge, we may well see similar dynamics, such as apps encourage bidding wars between multiple people who “own” data that is actually interpersonal (e.g., their social graph) to build monolithic private AIs that compete against humans, eschewing a future of competing plural AIs that augment humans. Thus, DeSoc does not need to be perfect to pass the test of being acceptably non-dystopian; to be a paradigm worth exploring it merely needs to be better than the available alternatives. Whereas DeSoc has possible dystopian scenarios to guard against, web2 and existing DeFi are falling into patterns that are inevitably dystopian, concentrating power among an elite who decide social outcomes or own most of the

11 See Posner, E. & Weyl, E. G., “Dismembering the Octopus,” Radical Markets: Uprooting Capitalism and Democracy for a Just Society, Princeton University Press, 2018.

wealth. The direction of web2 is deterministically authoritarian, accelerating the capacity of top-down surveillance and behavior manipulation. The direction of today’s DeFi is nominally anarcho-capitalist, but is already falling into network effect and monopoly pressures that risk its medium-term path becoming authoritarian in much the same way. DeSoc, in contrast, is stochastic social pluralism—a network of individuals and communities that come together, as emergent properties of each other, co-determining their own future. Looking at web2, the outgrowth of DeSoc can be analogized to the rise of popular participatory governments out of centuries of monarchy. Participatory governments didn’t inevitably give rise to democracy; it also led to the rise of communism and fascism. Similarly, SBTs don’t make digital infrastructure inherently democratic, but are democratic-compatible depending on what Souls and communities co-determine. Opening this possibility space is a marked improvement over web2’s authoritarianism and DeFi’s anarcho-capitalism.

§7 IMPLEMENTATION CHALLENGES

Privacy presents a key challenge for DeSoc. On the one hand, too many public SBTs may reveal too much information about a Soul, making them vulnerable to social control. On the other hand, too many purely private SBTs may also lead to private communication channels that eschew correlation discounting for governance and social coordination—presenting important incentive compatibility questions. Closely related to the issue of privacy is the issue of cheating: Souls may misrepresent their social solidarities, while coordinating through private or side channels. We cannot aspire to know all the possibilities and answers, but instead explore the nature of the challenge here and sketch a few promising paths for future research.

7.1 Private Souls

Blockchain-based systems are public by default. Any relationship that is recorded on-chain is immediately visible not just to the participants, but also to anyone in the entire world. Some privacy can be retained by having multiple pseudonyms: a family Soul, a medical Soul, a professional Soul, a political Soul each carrying different SBTs. But done naively, it could be very easy to correlate these Souls to each other. The consequences of this lack of privacy are serious. Indeed, without explicit measures taken to protect privacy, the “naive” vision of simply putting all SBTs on-chain may well make too much information public for many applications.

To deal with over-publicity, there are a number of solutions with different levels of technical complexity and functionality. The simplest approach is that an SBT could store data off-chain, leaving only the hash of the data on-chain.

On-chain data (fully public) Off-chain data, on-chain hash link (Owner chooses when to reveal)

The choice of how to store the off-chain data is left to the person; possible solutions include (i) their own devices, (ii) a cloud service trusted by them, or (iii) decentralized networks such as the Interplanetary File System (IPFS). Storing data off-chain lets us continue to have smart contracts that permission the right to write SBT data, but at the same time have separate permissions to read that data. Bob can choose to reveal the contents of any of his SBTs (or the data stores which they permission) only when he wishes to. This already gets us quite far, and has the further benefit of improving technical scalability because most data only needs to be handled by a very small number of parties. But to fully achieve properties like plural privacy, as well as more fine-grained forms of disclosure, we need to go further. Fortunately, many cryptographic technologies let us do that.

One powerful set of building blocks that enables new ways to partially reveal data is a branch of cryptography called “zero knowledge proofs.” While zero knowledge proofs are most frequently used today to enable privacy-preserving transfers of assets, they also can allow people to prove arbitrary statements without revealing any more information beyond the statement itself. For example, in a world where government documents and other attestations are cryptographically provable, someone could prove a statement like “I am a citizen of Canada, who is over 18 years old and has a university degree in economics and over 50,000 Twitter followers, and who has not yet claimed an account in this system.”

Zero-knowledge proofs can be computed over SBTs to prove characteristics about a Soul (e.g., that it has certain memberships). This technique can be extended further by introducing multi-party computation techniques such as garbled circuits, which could make such tests doubly private: the prover does not reveal who they are to the verifier, and the verifier does not reveal their verification mechanism to the prover. Instead, both parties make the computation together and only learn the output.

Another powerful technique is designated-veriﬁer proofs. In general, “data” is slippery: if I send a movie to you, I cannot technologically prevent you from recording and sending it to a third party. Workarounds like Digital Rights Management (DRM) have at best limited effectiveness, and often come at great costs to users. Proofs, however, are not slippery in the same way. If Amma wants to prove some property X about her SBTs to Bob, she can make a zero knowledge proof of the statement “I hold SBTs that satisfy property X, OR I have the access key to Bob’s Soul.” Bob would find this statement convincing: he knows that he did not make the proof, and so Amma must actually have SBTs that satisfy property X. But if Bob passes the proof along to Cuifen, Cuifen would not be convinced: for all he knows, Bob could have made the proof with his own key. This can be made even stronger with v eriﬁable delay functions (VDFs): Amma can make and present a proof that can only be made with the required SBTs right now, but anyone else will be able to make ﬁve minutes from now. This means it is possible to represent sophisticated access permissions to trustworthy proofs about data despite the impossibility of making the same kinds of selective permissions to the raw data itself, which may simply be copy and pasted. This may take us quite far nonetheless. Just as blockchains offer traceability in transactions that prevents someone from right-click copy-and-pasting a valuable NFT (and sybil attacking the original owner), similarly SBTs can offer traceability in social prevenance, which at minimum can reduce the value of copy-and-pasted data with unverified origins.

These off-chain data and zero-knowledge techniques are compatible with negative reputation—SBTs that are made visible even if the holder does not want them to be visible. Important examples of negative reputation include credit history, data about unpaid loans, negative reviews and complaints from business partners, and SBTs attesting to social connections relevant for coordination. Blockchains coupled with the same cryptography could offer a potential solution: Souls could be forced by smart contract logic to incorporate negative SBTs into a data structure like a Merkle tree that is stored off-chain, and any zero knowledge proof or garbled circuit computation would require them to introduce that information, because otherwise there would be a visible “hole” in the provided data that the verifier would recognize. The Unirep protocol is an example of how this might be implemented.

The point of these examples is not to show exactly how cryptographic technology can be used to solve all of the privacy and data permissioning problems with SBTs. Rather, it is to sketch out a few examples to show the power of such technologies. An important future research direction is to scope the exact limits of different kinds of data permissioning and the specific combinations of techniques that work

best to achieve the desired level of permissions. Another question is what types of plural property regimes are desirable to govern data, and how to properly unbundle access (“usus”), editing (“abusus”) and cash flow (“fructus”) rights.

7.2 Cheating Souls

If SBTs are the social substrate upon which plural property, network goods and intelligences are coordinated, one might be concerned that Souls will try to trick or cheat their way into communities to gain access to governance or property rights that we imagine SBTs permissioning. For example, if many applications depend on SBTs representing conference attendance, unscrupulous conferences could offer such SBTs in exchange for bribes. With enough bribes, humans (and bots) could generate a fake social graph that makes the account look like an authentic human Soul, richly differentiated by (fake) SBTs. Just as DAOs can be bribed, so can Souls and the on-chain voting mechanisms which they use. Conversely, if SBTs are used to discount coordination, Souls may avoid SBTs to maximize their influence. Why should we believe that the SBTs a Soul possess accurately reflect their true social commitments rather than simply how they choose to play this game? One argument is that the varying incentives to cheat may “balance out.” Souls may sort and self-identify into the networks that are important to them at the right scale, much like how Harberger taxes balance out the incentive to over-value and under-value assets to elicit approximately accurate market valuations. Souls will want to hold more SBTs to gain influence within their communities, but on the other hand will eschew SBTs from communities they care less about to score lower on correlation metrics and increase their influence in governance over broader networks. But it would be naive to assume that the two incentives—to gain access and maximize influence—always evenly cancel out, or even come close to canceling out, as though by magic. There may be many communities that use systems other than SBTs to gate access and governance. Or communities may—counter to our primary assumption about publicity—dole out private SBTs to reflect governance rights, but induce community members to keep these SBTs secret in broader decisions.

The problem of “gaming” should not be understated. It is a significant issue and resolving it is one of the most important foci for future research. Indeed, it is a major reason why open-sourcing many existing algorithms that prioritize or filter for human users is very challenging. To mitigate and deter SBT gaming, we suggest several norms and cryptographic directions:

The ecosystem of SBTs could bootstrap off “thick” community channels, where SBTs signal authentic off-chain community membership with strong social bonds and repeat interactions. This would make it easier for communities to filter and revoke SBTs of impersonators and bots. Such thick channels—which we often find in churches, workplaces, schools, meet-up groups, and organizations in civil society—would provide a more sybil-resistant social substrate to police gaming

(e.g., through bots, bribes, impersonation) in more “thin” social channels.

Nested communities could require SBTs to force context on potential collusion vectors “just below” them. For example, if a state were holding a funding round or vote, the state might require every participating citizen to also hold an SBT of a defined county and municipality.
The openness and cryptographic provability of the SBT ecosystem could itself be used to actively detect collusive patterns and penalize inauthentic behavior—perhaps discounting the voting power of collusive Souls, or obliging Souls to accept SBTs representing negative attestations. For example, if one Soul attests to the humanity of another Soul that turns out to be a bot, the case can be escalated and publicly verified, leading to that Soul having a large number of negative attestations. This already happens to an extent within the GitCoin QF ecosystem, where a range of signals are used to detect “collusive groups.”
ZK technology (eg. M ACI) could cryptographically prevent some attestations made by a Soul from being provable. This would make attempts to sell certain kinds of attestations non-credible, because the briber would have no way to tell whether or not the bribe recipient followed through on their side of the deal. There has been a large body of research on the use of such techniques for voting, but ultimately any non-financialized social mechanism may end up benefiting from similar ideas.
We could encourage whistleblowers as a way of making collusion of significant size unstable. Instead of detecting and penalizing incorrect or abusive behavior, we detect and penalize abusive patterns of collusion. This technique is risky to overuse because of the possibility of false-flag bribes, but it is nevertheless part of the toolkit.
We could use mechanisms from peer-prediction theory to encourage reporting to be honest in all cases except where collusion is extremely large. Instead of the conference attesting to attendees’ attendance, attendees could attest to each other’s attendance, so the number of participants that would need to be bribed to attest to a false claim becomes very large. The rewards need not be financial, but could be SBTs, making the rewards more useful to genuine community members than they are to attackers.
We could use correlation scores that focus on correlations where there is a large incentive to be honest if a group of Souls share a common interest. For example, the correlation scoring technique used in bounded pairwise quadrating funding uses quadratic funding donations themselves to determine how correlated two participants are, and therefore how much to discount their intersection. If two participants share many common interests, their incentive to express this fact to the QF mechanism is certainly diminished with correlation discounting, but it never becomes zero or negative.

§8 COMPARISONS AND LIMITATIONS

While the range of identity frameworks proposed is almost limitless, there are four particularly prominent and adjacent paradigms widely discussed in the web3 space that merit comparison: the dominant “legacy” identity ecosystem, the pseudonymous economy, proof of personhood, and verifiable credentials. Each paradigm highlights important contributions and challenges for future development of the social identity paradigm we advocate, and we use such limitations as a springboard for exploring future directions. All that considered, we also explain why we believe our social identity primitives of Souls and soulbound tokens are a more promising path forward for privacy regimes.

8.1 Legacy

Legacy identity systems rely on pieces of papers or identity cards issued and mediated by a 3rd party (a government, university, employer, etc). Provenance is established by calling up the 3rd party for a confirmation. While the legacy system has an interesting set of properties we should understand more deeply, such systems are wildly inefficient and do not lend themselves to composability or computation for rapid, efficient coordination. Moreover, these systems lack social context and makes Souls reliant on a centralized 3rd party to confirm membership to a community, rather than the embedding community. For example, most government issued IDs eventually trace back to a birth certificate issued on the authority of a medical doctor and family members, who are the ultimate source of truth and leave out many equally meaningful social connections that—taken together—offer far stronger validation. In fact, when centers of concentrated power seek strong identification (e.g., getting a security clearance from a major government) they rarely rely on such documents, instead turning to interviews in social networks. Thus such legacy identity systems tend to concentrate power in the issuer and in those who can undertake the due diligence to get stronger verification, who in turn become calcified and unreliable bureaucracies. A crucial design goal of DeSoc is ensuring that the security requirements of government IDs can be met and exceeded, allowing horizontal networks to make greater security available to all users and through a range of social substrates.

8.2 Pseudonymous Economy

The vision of a society based around combining reputation systems with zero knowledge proof mechanisms to preserve privacy has been most widely promoted by B alaji Srinivasan, who coined and popularized the phrase “pseudonymous economy.” His early version emphasizes the use of pseudonyms to avoid discrimination and evade “cancel culture” by social mobs that seek to harm a person’s reputation and break their social ties. It envisions people accumulating transferable zero-knowledge (ZK) attestations in their wallets and evading reputational attacks by transferring a subset of attestations to new wallets, or splitting the attestations amongst multiple wallets, presumably without traceability. In culling attestations to port, a person chooses the level of desired pseudonymity in the new account, weighing a tradeoff between more anonymity (porting fewer attestations) or more distribution to their social network (porting over more

attestations).

The practical difference between typical pseudonymous economy proposals and DeSoc is that we deemphasize identity separation as a primary way to protect participants from abuses and cancel culture. Some level of separation (e.g., different Souls between family, work, politics, etc.) may be healthy, but in general there are great disadvantages to relying on the ability to spin up new identities as a primary crutch against attacks. It makes reputation-staking for lending and provenance harder, and it composes poorly with governance mechanisms that try to correct for correlations or Sybils.

Rather than protecting victims by allowing them to re-emerge from attacks with a new–if diminished—identity, DeSoc would allow other approaches, such as contextualizing the attacker. “Cancellation” often arises precisely because statements and actions are taken out of context and viral signals travel through uncontextualized networks, when a person or bot has little social connection or context to a victim. In the same way that SBTs provide provenance to protect against deep fakes, a map of SBTs socially graphs a “hit piece’s” origin. “Hit pieces” essentially are artifacts arising outside of the victim’s communities (as reflected by shared SBT memberships), or lacking SBT attestations from the victim’s communities—which should cast doubt on the piece’s veracity. SBTs also empower victims to launch a defensive response to counteract the hit, curated and propagated from their network of trust (represented here by the patterns of co-holding of SBTs). By maintaining social context, people can maintain trust, even if they are under threat of cancellation, and hold attackers accountable. Improving provenance improves the social foundation of truth.

8.3 Proof of personhood (PoP)

Proof of Personhood protocols (PoP) aim to provide tokens of individual uniqueness, to prevent Sybil attacks and allow non-financialized applications. To do so, they rely on approaches such as global analysis of social graphs, biometrics, simultaneous global key parties, or some combination thereof. However, because PoP protocols seek to represent individual identities—-focused on achieving global uniqueness—rather than social identities mapping relationships and solidarities, PoP protocols are limited to applications that treat all humans the same. Most applications we are interested in—such as staking reputation—are relational and move beyond being a unique human to being a diﬀerentiated human.

Moreover, PoP protocols are not immune to sybil attacks. In almost all near-term foreseeable applications, PoP systems are effectively open to Sybil attacks, just at a slightly higher cost. Unless most people on the planet are registered for a PoP service and are participating in a particular validation exercise, an attacker can always recruit disinterested humans who are not yet participating to act as Sybils. While such mercenaries are not quite bots, the difference is superficial other than perhaps a small added expense.

Many PoP protocols aim to build a substrate for universal basic income or global democracy. While

we don’t share the same ambition, such protocols have spurred us to nonetheless consider how to build gradually towards coordinating plural network goods. In contrast to the binary, individualist and global nature of PoP, our approach aims to construct a rich, contextual and layered substrate for bottom-up reputation, property and governance that allows participation in a range of communities and networks, small and large.

8.4 Verifiable credentials

Verifiable credentials (VCs) are a W3C standard where credentials (or attestations) are zk-shareable at the holder’s discretion. VCs highlight the major limitations of our baseline privacy paradigm and motivate our discussion of privacy extensions above. Until SBTs have privacy extensions that narrow publicity, VCs and SBTs can be seen as natural complements: in particular, SBTs are initially public making them inappropriate for sensitive information like government-issued identification, while VC implementations have struggled with a recovery paradigm that could be addressed by community recovery. The two approaches combined can in the near-term be stronger than either alone. But VCs also have a key limitation: at least in their standardized form, VCs do not support most of the applications we have enumerated because of their unilateral privacy.

Unilateral zk-sharing isn’t incentive-compatible with our use cases, nor does it reflect our norms around privacy. Most of our applications depend on some level of publicity. But under zk-sharing, Souls can’t know another Soul possesses an SBT unless it is shared to them—making reputation-staking, credible commitments, sybil-resistant governance, and simple rental contracts (e.g., apartment lease) impossible to get off the ground as other commitments and encumbrances are not necessarily visible. More deeply, we are skeptical that unilateral shareability is usually the right privacy paradigm. Rarely does one party in a multi-party relationship have the unilateral rights to disclose the relationship without the consent of the other. Just as unilaterally transferable private property is not a rich property regime, simplistic unilateral shareability is not a very rich privacy regime. If two parties co-own an asset and choose to represent their relationship through a VC, such credential doesn’t allow for the mutual-consent and mutual-permissions. This problem travels to more complex cases of plural property and complex organizational forms and permissions, which are a feature of DeSoc.

§9 SOUL BIRTH

The path from the current web3 ecosystem to augmented sociality mediated by SBTs faces a classic cold start challenge. On the one hand, SBTs are not transferable. On the other hand, today's mix of wallets may not be the final home for SBTs because they lack community recovery mechanisms. But in order for community recovery wallets to work, they need a rich variety of SBTs across discrete communities to be secure. What comes first: SBTs or community recovery? Who are the early adopter communities? How do SBTs on different chains interoperate? We cannot aspire to know all the possibilities and answers, but

instead sketch a few promising paths for the reader to further explore within the current web3 and even web2 architecture.

9.1 Proto SBTs

Although the hallmark of SBTs is non-transferability, SBTs may also have another property which may prove more useful in bootstrapping: revocability. It’s possible that SBTs first gestate as revocable, transferable tokens, before growing into non-transferability. A token is revocable if an issuer can burn the token and re-issue it to a new wallet. Burning and re-issuing would make sense when, for example, keys are lost or compromised, and the issuer has an interest in ensuring the tokens are not financialized and sold off to a party—in other words, when the token signals authentic community membership. Employers, churches, meet-up groups, clubs with repeat off-chain interactions are well positioned to burn and re-issue tokens because they have a relationship with a person, and can easily check for impersonation by phone call, video-conference, or simple meeting in person. Single interactions, such as attendance to a concert or conference are poorly suited because community bonds are weaker.

Revocable, transferable tokens are a kind of proto-SBT—serving supportive, placental functions before Soul birth. These tokens buy time both for wallets to gestate secure, community recovery mechanisms and for a person to sufficiently accumulate proto-SBTs that can eventually be burned and re-issued into non-transferable SBTs. Under this pathway, the question is not, “what happens first: SBTs or community recovery?” Rather, SBTs and community recovery instantiate simultaneously, birthing a Soul.

9.2 Community Recovery Wallets

Although today’s wallets lack community recovery, they each have relative strengths and weaknesses in being homes—or perhaps gestational wombs—for SBTs. Proof of Personhood (PoP) protocols have the advantage of already experimenting with social dispute resolution mechanisms, which are the foundation of community recovery. Also, many DAOs use PoPs to facilitate governance, making them natural first issuers of SBTs. However, despite PoPs natural lead, PoP protocols haven’t yet earned broad trust to house valuable token assets, whereas custodial wallets have. Custodial wallets—despite their flaws of centralization—may thus offer a natural onramp for less sophisticated retail users. Such custodial wallets could also build tooling for retail communities to issue revocable tokens that later convert (or burn and reissue) into SBTs or even tooling for more “corporate” issuers—many of whom are looking for ways to build loyal customer bases in web3 but lack expertise in custody. Once community recovery mechanisms have been formalized and battle-tested, these custodial wallets could decentralize into community recovery, while custodians move on to providing other valuable services in DeSoc (like community management, SBTs issuances, etc.) For more sophisticated web3 users, decentralized non-custodial wallets (or non-custodial social recovery wallets like Argent and Loopring) are a natural starting point for bootstrapping community

recovery mechanisms. Non-custodial wallets have the advantage of being native web3 open-source, and the flexibility to pre-announce and experiment with mechanisms incrementally to a subset of voluntary, sophisticated users to battletest incentives and mix mechanisms (e.g.,mult-sig). All of these approaches—PoPs, custodial, and non-custodial—play an important role in experimenting and onboarding users with different degrees of sophistication and risk tolerance.

9.3 Proto-Souls

Norms can also shepherd Souls into existence. As we rethink tokens and wallets, we can also reframe how we think about certain classes of NFTs and tokens that are intended to signal membership. In particular, we can introduce a norm of not transferring NFTs and POAPs issued by reputable institutions that reflect attendance to a conference, work experience, or education credentials. Such transfers of membership tokens—if traded for value—could diminish the reputation of a wallet and perhaps discourage issuers from further issuing membership or POAP tokens to that wallet. Already in the non-custodial ecosystem, a significant number of users have achieved significant financial reputation and stake in their wallets, which could bootstrap as effective collateral for them not to abuse non-transferability expectations. While all these pathways have respective challenges, we hope that the variety of approaches increases the chance of convergence to our quasi-equilibrium state in the medium term through a small set of steps.

§10 CONCLUSION

As ambitious as we have been in imagining what DeSoc could enable, in many ways the above are just first steps. There is more than one road to DeSoc, including a number of non-blockchain based frameworks, such as Spritely, ACDC and Backchannel that rely on data stores tied to local machines rather than global ledgers. These frameworks may eventually offer even greater trust across social distance, because they can harness transitivity of trust relationships—like trusted introductions—rather than relying on SBTs issued by well-known, high-status institutions (like universities or DAOs). Furthermore the applications we describe above are just the beginning of what DeSoc can empower, not touching virtual worlds: their physics, society, and their complex intersection with the physical world. All this suggests that even the broad ambitions we paint above are just the beginning of what DeSoc may eventually become. On that path, however, many challenges and open questions remain. The above sketches require extensive red teaming and many of them are more suggestive than fully prescriptive. How can DAOs maintain their publicity of state while thoughtfully comparing patterns of Souls and correlations in SBTs to enforce Sybil protections and decentralization? How incentive compatible is acquiring SBTs in face of various schemes of correlation discounting? How much does privacy conflict with correlation discounting and other DeSoc mechanism designs? How can we measure inequality in a social and yet appropriately private (contextually integral) manner? How should inheritance work in the community recovery framework? Are there red lines that can be drawn or even baked into protocols to avoid dystopian scenarios? Or should we simply race to build the best scenarios first? These questions are just the beginning of what we

expect to be a research agenda spanning years that will co-evolve with the DeSoc ecosystem.

Yet the potential that DeSoc offers seems not just worth the price of navigating these tricky challenges, but perhaps necessary to ensure our survival. Albert Einstein told the 1932 disarmament conference that the failures of the “organizing power of man” to keep pace with “his technical advances” had put a “razor in the hands of a 3-year-old child.” In a world where his observation seems more prescient than ever, learning how to program futures that encode sociality—rather than writing over trust—seems a required course for human life on this planet to persist.

APPENDIX

Adjusting Quadratic Mechanisms for Pre-Existing Cooperation

Because quadratic mechanisms incent collaboration from a baseline of selfishness, they are vulnerable to groups who are already cooperative. If SBTs reflect community memberships that individuate a Soul to reflect their partialities, SBTs can help us discount pre-existing cooperation and tip the scales in favor of cooperation across diﬀerences. Here we provide an illustration of a first attempt at a refined quadratic model and offer future directions for research. This mechanism is not optimized and doubtless has vulnerabilities; it is meant as an illustrative example to spur experimentation and future research. While we illustrate with Quadratic Funding (QF), the same principles and formulas also apply to Quadratic Voting (where individual contributions are simply substituted with voice credits).

In QF, a community matches individual contributions to shared projects with funds in proportion to the square of the sum of the square roots of individual contributions. For fixed contribution levels, matching funds grow as the square of the number of individual contributors, but have diminishing returns to individual contributions. There are diminishing returns to concentrated individual action, but increasing returns to collective action. For example, if Abdu, Shou and Belle were non-cooperating individuals—contributing respectively 𝐴, 𝑆 and 𝐵 currency units—the matching funds to their donations in a QF program (for example, Gitcoin Grants) should be proportional (with scaling determined by available funds) to the square of the sum of the square roots of individual donations.

𝑆𝑖𝑚𝑝𝑙𝑒 𝑀𝑎𝑡𝑐ℎ ~ ( +

𝐵) − (𝐴 + 𝑆 + 𝐵)

Single Membership

Now suppose a simplified model where Abdu, Shou and Belle are differentiated by a single membership—workplace—and matching funds are available for startups, companies, and open-source projects (again, in the spirit of Gitcoin). Because people from the same workplace have a strong incentive to contribute to their own workplace to maximize matching funds to their company, we should expect them to coordinate. An extreme approach would be to assume that workers fully share goals and fully coordinate their behavior. Yet even in this simple case, there are several ways we might compensate in the formula.

A simple approach, which we call “clustering,” would put two co-workers “under the same square root” in the quadratic formula to offset their tendency to already coordinate. If Abdu and Shou were co-workers (but not Belle), Abdu and Shou’s contribution would be summed and square rooted together while Bob’s contribution would be square rooted alone, effectively giving his contribution more

weight:

𝐶𝑙𝑢𝑠𝑡𝑒𝑟 𝑀𝑎𝑡𝑐ℎ ~ (

𝐵) − 𝐴 − 𝑆 − 𝐵

If Abdu and Shou are perfectly coordinated, it’s always optimal for them to split their join contribution equally, so we can assume 𝐴 = 𝑆, letting us simplify:

2 = ( + 𝐵) − (2𝐴 + 𝐵)

In this case, it is easy to see how clustering leads to optimality (or welfare maximization) by the same argument as for QF more generally: if Abdu and Shou are perfectly coordinated, they effectively act as a single agent and the Clustering Matching formula is the QF formula for two agents—the joint Abdu-Shou agent and the Belle agent.

Another adjustment that also achieves optimality is what we call the “Offsetting Match:”

𝑂𝑓𝑓𝑠𝑒𝑡 𝑀𝑎𝑡𝑐ℎ ~ (

𝐵)

− 𝐴 − 𝑆 − 𝐵

The rationale in the Offsetting Match is that because Abdu and Shou are part of a perfectly coordinating size-2 group, we can reduce the weight of their votes by a factor of to compensate for the coordination. This leads to the same outcome as the Cluster Match as it is always optimal for a perfectly coordinated Abdu and Shou (𝐴 = 𝑆) to make equal contributions and in this case

𝑂𝑓𝑓𝑠𝑒𝑡 𝑀𝑎𝑡𝑐ℎ ~ ( 𝐴+ 𝐴 + 𝐵)

− 𝐴 − 𝐴 − 𝐵

2 = ( + 𝐵) − (2𝐴 + 𝐵)

Multiple Memberships

The previous example assumes Abdu, Shou and Belle have a single membership: workplace. Yet in almost all applications this would be a vast oversimplification. People have multiple community memberships, cooperative relationships, and even informal intersections. Abdu and Belle might be extended family, Shou and Belle might have attended the same school, or Shou and Abdu might be token-holders of the same layer 1 protocol, and so on. To facilitate cooperation across differences, these correlations in memberships between individuals need to be recognized in a less binary manner. We now consider

extending each of the approaches above to do this. We again focus on the simplest example sufficient to make the point; below we follow up with more general formulae.

We focus on an example where Abdu and Shou share an affiliation, Abdu and Belle share a different affiliation, and Shou has an affiliation with a group that includes other members, but none participating in this matching round. This is the complete set of affiliations.

To extend the Cluster Match to this case, we include a cluster for each group of shared affiliations and distribute the contributions of each individual among all of the groups they participate in equally with coefficients on their contributions that sum to one.

𝐶𝑙𝑢𝑠𝑡𝑒𝑟 𝑀𝑎𝑡𝑐ℎ ~ ( +

2 𝑆 2

− 𝐴 − 𝐵 − 𝐶

To extend the Offset Match, we have to solve for coefficients on each individual’s contribution to compensate for the coordination benefiting that individual. In particular, if we assume that Belle half internalizes Abdu’s value, that Abdu half internalizes Belle and a quarter internalizes Shou’s and Shou quarter internalizes Abdu’s, then we need to find coefficients solving α α α + 𝐵 + 𝑆 = 1 𝐴 2 4 α α + 𝐴 = 1 𝐵 α α + 𝐴 = 1 𝑆

The solution to this equation is α

= 4 , α = 9 , α = 10 . So

𝐴 11 𝐵 11 𝑆 11

𝑂𝑓𝑓𝑠𝑒𝑡 𝑀𝑎𝑡𝑐ℎ ~ ( +

10𝑆 11

2 − 𝐴 − 𝐵 − 𝐶

The Offset Match, while in some ways the simplest, is almost the most opaque, assigning to each individual a weight depending on their social centrality that offsets the power this grants.

General Formulae

For each individual 𝑖 = 1, …𝑁, let us define the number of affiliations she holds as 𝑇𝑖; in general we might give different weights to different affiliations, but at present we assume they are all equal. Let Σ be the set of all “affiliation groups,” projects of the set of holders of a given affiliation onto the set of participants in

the match, with typical element σ . Note that 𝑇 =

|Σ| ∑ 1

, where 1 is the indicator function. Denote the

𝑗 𝑖

𝑗=1

𝑖∈σ · 𝑗

contribution of individual 𝑖 as 𝑐 . Then the general formula for the Cluster Match is 2

|Σ| ⎛

|σ | 𝑁 𝑗 𝑐 ⎞

𝐶𝑙𝑢𝑠𝑡𝑒𝑟 𝑀𝑎𝑡𝑐ℎ ~ ⎜ ∑ 𝑗=1 ⎝

∑ 𝑖=1

𝑖 𝑇 ⎟ 𝑖 ⎠

− ∑ 𝑐 𝑖 𝑖=1

Define the Correlation Score between any ordered pair of individuals 𝑖 and 𝑘 to be

|Σ| ∑ 1 𝑖∈σ

1 𝑘∈σ

𝑠 𝑖,𝑘

𝑗=1 𝑗 𝑗 𝑇 𝑖

The Offset Match is then derived by the offset coefficients, α that solve the system of equations, one for each individual 𝑖: 𝑁 α + ∑ α 𝑠 = 1

𝑖 𝑘≠𝑖

𝑘 𝑘,𝑖

This will generically yield a unique solution for the vector α, which is roughly an inverse measure of the network centrality of individuals in the solidarity network. Then 𝑁 2 𝑁 𝑂𝑓𝑓𝑠𝑒𝑡 𝑀𝑎𝑡𝑐ℎ ~ (∑ α 𝑐 ) − ∑ 𝑐

One appealing feature of this solution is that it will generally lead to optimality assuming that solidarity correctly measures effective internalization of utility. A less appealing feature is that it seems unlikely to be particularly “robust:” in particular and in contrast to other cases, it will not always be optimal for any individual to give all her contributions through the match rather than externally, given the penalties.

Pairwise Matching

A third mechanism, which we call “Pairwise Matching,” suggested by Buterin (2019) takes a different approach. Pairwise Matching has the disadvantage that it does not achieve optimality but instead focuses on bounding losses from specific attacks, but it has the important advantage that it does not require an extrinsic source to specify who is coordinating and who is not; instead, this information is extracted from the contribution values themselves.

Pairwise Matching can only be meaningfully defined in the context of multiple projects and a

per-pair matching cap, 𝑀. For every pair of agents (𝐴, 𝐵), if they contribute 𝑥 and 𝑥 project 𝑃, they get a subsidy12

to the same

2𝑀 𝑥 𝑥

𝑀𝑎𝑡𝑐ℎ 𝐴𝐵→𝑃

𝑀 + 𝐶𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑖𝑜𝑛𝑆𝑐𝑜𝑟𝑒 𝐴𝐵

Where 𝑀 is a parameter of the system and

𝐶𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑖𝑜𝑛𝑆𝑐𝑜𝑟𝑒 = 𝐴𝐵

∑ 𝑎𝑙𝑙 𝑝𝑟𝑜𝑗𝑒𝑐𝑡𝑠 𝑃

The 𝐶𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑖𝑜𝑛𝑆𝑐𝑜𝑟𝑒 is intended to reflect to what extent two participants contribute to the same projects. If two participants 𝐴 and 𝐵 both contribute 𝑥 to some project, then 𝐶𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑖𝑜𝑛𝑆𝑐𝑜𝑟𝑒 increases by x. If they contribute different amounts, 𝐶𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑖𝑜𝑛𝑆𝑐𝑜𝑟𝑒 increases by the geometric mean of their two contributions. If 𝐴 and 𝐵 have a low 𝐶𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑖𝑜𝑛𝑆𝑐𝑜𝑟𝑒, we assume that they are highly independent agents, and give them close to the maximum subsidy whenever they do contribute to some project together. But if 𝐴 and 𝐵 contribute to the same project frequently and/or in large amounts, we assume that they are highly coordinated and are acting somewhat more like a single agent, and discount the subsidies to projects that they co-fund.

In the limiting case where 𝑥 → 0 for all agents and projects, the correlation scores are negligible, and so the above formula is equivalent to simple quadratic funding: 𝑀𝑎𝑡𝑐ℎ simplifies to 2 𝑥 𝑥 . In the three-agent case, where three agents contribute 𝐴, 𝑆 and 𝐵, this simplifies to:

𝑇𝑜𝑡𝑎𝑙𝑀𝑎𝑡𝑐ℎ = 𝑀𝑎𝑡𝑐ℎ + 𝑀𝑎𝑡𝑐ℎ + 𝑀𝑎𝑡𝑐ℎ 𝑃 𝐴𝑆 →𝑃 𝐵𝑆 →𝑃 𝐴𝐵 →𝑃 = 2 + 2 + 2

= ( +

𝐵) − (𝐴 + 𝑆 + 𝐵)

But if a pair of agents contributes many times or in large amounts to the same projects, the correlation score of that pair increases, until eventually any additional shared contributions to a new project are mostly taking subsidies away from other shared contributions that the same pair of agents has already made. As total matches approach infinity, the total subsidy per pair of agents approaches

𝑙𝑖𝑚

2𝑀𝑇 = 2𝑀.

𝑇 →∞ 𝑀+𝑇

12 The original description differs slightly in that it uses M instead of 2M. Technically, 2M is correct if we sum over unordered pairs of agents, and M is correct if we sum over ordered pairs. Here, we are summing over unordered pairs.

A key design goal of this formula was to bound the losses from incorrectly identifying a colluding group as independent agents. In Simple Matching, losses are unbounded: 𝑁 fake or colluding agents controlled by the same real-world actor can each contribute 𝑉 to a fake project, and extract a subsidy of 𝑉 * (𝑁 − 𝑁). In Cluster Matching, a similar unbounded extraction is possible if the clustering mechanism misindentifies even one colluding group as being completely independent. In Pairwise Matching, in contrast, losses from 𝑁 fake or colluding agents are always bounded above by 2 − 𝑁), where 𝑀 is a parameter of the system.

Note that Pairwise Matching does not achieve optimality: colluding actors still have the incentive to somewhat over-report how much they value certain projects, and can even extract some funds by contributing to a fake project controlled by themselves. Rather, this approach is intended to be a second-best, optimized for the case where limited outside information is available about which actors are actually colluding.

That said, Pairwise Matching can be used as a philosophical template for how to account for pre-existing coordination without over-penalizing it: instead of the correlation score only including values for that particular quadratic funding system, it could attempt to include similar terms for all instances where those two actors gained a benefit by cooperating. If benefits from cooperation are valued correctly, cooperating further would never be net-harmful for any pair of agents; rather, the net gains from further cooperation would simply approach zero.

A Beginner's Guide to Optimism

delabs@newsletter.paragraph.com (Real Block) — Sat, 21 May 2022 07:33:44 GMT

https://newsletter.banklesshq.com/p/a-beginners-guide-to-optimism?s=r

Recently, The second largest EVM-compatible L2 chain Optimism announced their first token airdrop. 🤯

👉 Here’s the eligibility criteria for airdrop #1.

👉 Check here to see if your address qualified

We predicted the Optimism Airdrop last year in our Airdrop Guide, if you’re a Premium Subscriber we expect you benefited from this one! (review the other airdrops we predicted here)

At present, Optimism is a vibrant ecosystem with close to $700m in total locked value and 108 dapps deployed.

Optimism is like having your cake and eating it too: cheap, quick transactions while maintaining the primary security guarantees of the base Ethereum chain.

It’s the best of both worlds. Ethereum is scaling through rollups.

With news of its token launch, activity on Optimism is set to explode.

If you’re never heard of Optimism, it’s not too late. In fact, as we learned from the Optimism team in today’s episode there will be many future Optimism airdrops to come!

Today, William takes us on an Optimism 101 tutorial. Let’s jump in.

- RSA

P.S. Don’t miss another airdrop! Upgrade to Bankless Premium and get access to the Ultimate Guide to Airdrops now! 🚀

🙏** Sponsor: **Polygon Studios—Fostering culture across Gaming, NFTs, and the Metaverse✨

🎥 NEW EPISODE: ALL ABOUT THE OPTIMISM AIRDROP

Apple | Spotify | YouTube | RSS Feed

Tactic Tuesday

Bankless Writer: William M. Peaster, Bankless contributor and Metaversal writer

Optimism is one of the most exciting layer two (L2) Ethereum scaling solutions we’ve seen yet. This Bankless tactic will demonstrate how novice crypto users can dive deeper into this L2 to enjoy super fast and super cheap Ethereum-based transactions.

Goal: Learn how to start exploring Optimism
Skill: Beginner
Effort: 25 minutes
ROI: Up to +25% APY in Optimism’s DeFi scene

Optimistic about crypto’s future? Then Optimism’s for you

Rollups and validiums and volitions, oh my!

Ethereum’s ecosystem of layer two (L2) scaling solutions is blooming in all directions right now. This “endgame” approach to blockchain scaling is taking crypto mainstream by making transactions extremely inexpensive and extremely fast.

Though the L2 scene is still very young, one of its earliest stars is Optimism. The Optimism project derives its name from its rollup style, which is known as an “optimistic rollup.”

How Optimism Works

Simply put, this means Optimism is an L2 that “rolls” off-chain transactions into batches, and the network then assumes these constituent transactions are valid unless they’re challenged via what are known as fraud proofs.

Optimism’s TVL over the past 90 days - Image via L2Beat

So while Optimism ultimately posts data onto Ethereum, it executes Ethereum-based transactions off-chain. This way, Optimism achieves significant transaction efficiency and security guarantees at the same time. Bypassing mainnet gas costs and transaction congestion while enjoying mainnet quality security is the Optimism way.

Yet beyond fast and cheap transactions, Optimism is also notable because it’s currently the only L2 that offers full Ethereum Virtual Machine (EVM) equivalence.

Accordingly, Optimism is the first L2 to fully comply with Ethereum’s protocol spec. This EVM equivalence mitigates the need for a compiler and lets Optimism allow DeFi and NFT projects to 1-click deploy to Optimism and thereafter still use all the great Ethereum L1 tooling that’s out there, e.g. Hardhat, Vyper, and beyond.

A brief history of Optimism

Jan. 2019: The Optimism team’s precursor, Plasma Group, introduced themselves and a spec for a Plasma Cash scaling solution.
Feb. 2019: Plasma Group introduced a general purpose Plasma implementation.
July 2019: Plasma Group unveiled the Optimistic Virtual Machine (OVM), a “virtual machine designed to support all L2 protocols.”
Oct. 2019: Plasma Group released Unipig.exchange, a test optimistic rollup DEX implementation in collaboration with Uniswap.
Jan. 2020: Plasma Group rebranded to Optimism, a public benefit corporation (PBC) focused on scaling Ethereum.
Feb. 2020: Optimism open-sourced the OVM.
May 2020: Derivatives dapp Synthetix released a demo of its protocol on the OVM.
Jan. 2021: Optimism conducted its mainnet soft launch.
July 2021: Uniswap V3 launched on Optimism.
July 2021: Optimism kicked off its retroactive public goods funding program, i.e. the team committed to allocating the proceeds of operating the L2 before its total decentralization to public goods funding experiments.
Oct. 2021: Optimism unveiled full EVM equivalence.
Dec. 2021: Optimism’s creators removed the L2’s allowlist, opening the way for dapps to permissionlessly deploy to the network.
Mar. 2022: The Optimism team revealed Cannon, the network’s next-gen fault proof system.
Apr. 2022: Optimism introduced the OP token to pivot the L2 into community ownership.

How to get started with Optimism

Creating an Optimism wallet

Since Optimism is EVM-compatible, it’s really simple to add an Optimism account to your existing Ethereum wallet(s). For example, let’s say you have a MetaMask wallet. Adding Optimism is then as easy as going to Chainlist, connecting your wallet, and clicking on the Optimism option. Then in MetaMask you would toggle between Ethereum and Optimism as needed using the “Networks” button.

Getting money onto Optimism

Looking to move money from Ethereum to Optimism? You’re in luck!

The Optimism team just unveiled a new streamlined bridge UI that aggregates third-party bridges into one seamless bridging portal. You can choose a chain, a debit card, or a centralized crypto exchange to move funds onto Optimism, plus you can choose from multiple different Optimism-to-Ethereum withdrawal routes too.

Whatever you want, whenever you want it.

Optimism starter pack

Here are some resources you can use to help you more easily navigate the Optimism ecosystem.

TOOLS 🔨

READ 📚

WATCH 📺

METAVERSAL 🎨

Trying NFTs on Optimism

Top Optimism apps

The 10 largest Optimism dapps right now - Image via DeFi Llama

1. Synthetix

With +$200M total value locked (TVL) on Optimism, synthetic assets protocol Synthetix is presently the largest dapp on the L2. No surprise there, though, as Synthetix was one of the first dapps to embrace Optimism, so its first-mover advantage has translated into considerable early inertia on the L2.

2. Uniswap

Uniswap is the web3 standard for decentralized exchanges. When the DEX launched on Optimism last summer, the arrival kickstarted a whole new wave of interest in using Optimism’s DeFi scene. If you’re wanting to make crypto trades affordably, Uniswap V3 on Optimism is one of your best bets right now.

3. Perpetual Protocol

Perpetual Protocol is an on-chain perpetual futures DEX that is now live on Ethereum, Optimism, and Gnosis Protocol. If you’re looking to trade perpetual swaps in affordable fashion, Perpetual Protocol is certainly an option worth considering these days.

Bonus projects

Other notable projects deployed on Optimism include the following dapps:

Stargate: An omnichain interoperability protocol.
Lyra: An options trading protocol.
Synapse: A cross-chain bridging protocol.
Hop Protocol: A cross-chain bridging protocol.
ZipSwap: A fork of the Uniswap DEX protocol.
Curve: One of the most popular DEXes in DeFi.
Arrakis Finance: A liquidity management protocol.

Conclusion

Optimism is one of the top L2s right now, and the OP token is the biggest L2 token release we’ve seen to date.

We’re all still wrapping our heads around what OP means for the cryptoeconomy, but make no mistake: this is a huge milestone that hails the acceleration of Ethereum’s L2 era.

Optimism is already very fast and affordable, but it’ll need to become very decentralized over time to reach its full potential. The OP release represents a big step forward in that direction.

If you think crypto has a bright future, then trying Optimism in the here and now is a great way to prepare for all the optimistic L2 advances that are to come!

Action steps

🔴 Explore the ecosystem of Optimism projects
🌍 Read our last tactic A beginner’s guide to Terra if you missed it

Do 'Trust Models' Deserve Their Title?

delabs@newsletter.paragraph.com (Real Block) — Thu, 05 May 2022 03:45:49 GMT

One of the most valuable properties of many blockchain applications is trustlessness: the ability of the application to continue operating in an expected way without needing to rely on a specific actor to behave in a specific way even when their interests might change and push them to act in some different unexpected way in the future. Blockchain applications are never fully trustless, but some applications are much closer to being trustless than others. If we want to make practical moves toward trust minimization, we want to have the ability to compare different degrees of trust. First, my simple one-sentence definition of trust: trust is the use of any assumptions about the behavior of other people. If before the pandemic you would walk down the street without making sure to keep two meters' distance from strangers so that they could not suddenly take out a knife and stab you, that's a kind of trust: both trust that people are very rarely completely deranged, and trust that the people managing the legal system continue to provide strong incentives against that kind of behavior.

image

One of the most valuable properties of many blockchain applications is trustlessness: the ability of the application to continue operating in an expected way without needing to rely on a specific actor to behave in a specific way.

Even when their interests might change and push them to act in some different unexpected way in the future.

Blockchain applications are never fully trustless, but some applications are much closer to being trustless than others. If we want to make practical moves toward trust minimization, we want to have the ability to compare different degrees of trust.

First, my simple one-sentence definition of trust: trust is the use of any assumptions about the behavior of other people. If before the pandemic you would walk down the street without making sure to keep two meters' distance from strangers so that they could not suddenly take out a knife and stab you, that's a kind of trust: both trust that people are very rarely completely deranged, and trust that the people managing the legal system continue to provide strong incentives against that kind of behavior.

When you run a piece of code written by someone else, you trust that they wrote the code honestly (whether due to their own sense of decency or due to an economic interest in maintaining their reputations), or at least that there exist enough people checking the code that a bug would be found.

Not growing your own food is another kind of trust: trust that enough people will realize that it's in their interests to grow food so they can sell it to you. You can trust different sizes of groups of people, and there are different kinds of trust.

For the purposes of analyzing blockchain protocols, I tend to break down trust into four dimensions:

How many people do you need to behave as you expect?
Out of how many?
What kinds of motivations are needed for those people to behave? Do they need to be altruistic, or just profit seeking? Do they need to be uncoordinated?
How badly will the system fail if the assumptions are violated?

For now, let us focus on the first two. We can draw a graph:

image

The more green, the better. Let us explore the categories in more detail:

1 of 1: there is exactly one actor, and the system works if (and only if) that one actor does what you expect them to. This is the traditional "centralized" model, and it is what we are trying to do better than.
N of N: the "dystopian" world. You rely on a whole bunch of actors, all of whom need to act as expected for everything to work, with no backups if any of them fail.
N/2 of N: this is how blockchains work - they work if the majority of the miners (or PoS validators) are honest. Notice that N/2 of N becomes significantly more valuable the larger the N gets; a blockchain with a few miners/validators dominating the network is much less interesting than a blockchain with its miners/validators widely distributed. That said, we want to improve on even this level of security, hence the concern around surviving 51% attacks.
1 of N: there are many actors, and the system works as long as at least one of them does what you expect them to. Any system based on fraud proofs falls into this category, as do trusted setups though in that case the N is often smaller. Note that you do want the N to be as large as possible!
Few of N: there are many actors, and the system works as long as at least some small fixed number of them do what you expect them do. Data availability checks fall into this category.
0 of N: the systems works as expected without any dependence whatsoever on external actors. Validating a block by checking it yourself falls into this category.

While all buckets other than "0 of N" can be considered "trust", they are very different from each other!

Trusting that one particular person (or organization) will work as expected is very different from trusting that some single person anywhere will do what you expect them to.

"1 of N" is arguably much closer to "0 of N" than it is to "N/2 of N" or "1 of 1". A 1-of-N model might perhaps feel like a 1-of-1 model because it feels like you're going through a single actor, but the reality of the two is very different: in a 1-of-N system, if the actor you're working with at the moment disappears or turns evil, you can just switch to another one, whereas in a 1-of-1 system you're screwed.

Particularly, note that even the correctness of the software you're running typically depends on a "few of N" trust model to ensure that if there's bugs in the code someone will catch them.

With that fact in mind, trying really hard to go from 1 of N to 0 of N on some other aspect of an application is often like making a reinforced steel door for your house when the windows are open.

Another important distinction is: how does the system fail if your trust assumption is violated? In blockchains, two most common types of failure are liveness failure and safety failure.

A liveness failure is an event in which you are temporarily unable to do something you want to do (eg. withdraw coins, get a transaction included in a block, read information from the blockchain).

A safety failure is an event in which something actively happens that the system was meant to prevent (eg. an invalid block gets included in a blockchain).

Here are a few examples of trust models of a few blockchain layer 2 protocols. I use "small N" to refer to the set of participants of the layer 2 system itself, and "big N" to refer to the participants of the blockchain; the assumption is always that the layer 2 protocol has a smaller community than the blockchain itself.

I also limit my use of the word "liveness failure" to cases where coins are stuck for a significant amount of time; no longer being able to use the system but being able to near-instantly withdraw does not count as a liveness failure.

Channels (incl state channels, lightning network): 1 of 1 trust for liveness (your counterparty can temporarily freeze your funds, though the harms of this can be mitigated if you split coins between multiple counterparties), N/2 of big-N trust for safety (a blockchain 51% attack can steal your coins)
Plasma (assuming centralized operator): 1 of 1 trust for liveness (the operator can temporarily freeze your funds), N/2 of big-N trust for safety (blockchain 51% attack).
Plasma (assuming semi-decentralized operator, eg. DPOS): N/2 of small-N trust for liveness, N/2 of big-N trust for safety.
Optimistic rollup: 1 of 1 or N/2 of small-N trust for liveness (depends on operator type), N/2 of big-N trust for safety.
ZK rollup: 1 of small-N trust for liveness (if the operator fails to include your transaction, you can withdraw, and if the operator fails to include your withdrawal immediately they cannot produce more batches and you can self-withdraw with the help of any full node of the rollup system); no safety failure risks
ZK rollup (with light-withdrawal enhancement): no liveness failure risks, no safety failure risks

Finally, there is the question of incentives: does the actor you're trusting need to be very altruistic to act as expected, only slightly altruistic, or is being rational enough? Searching for fraud proofs is "by default" slightly altruistic, though just how altruistic it is depends on the complexity of the computation (see the verifier's dilemma), and there are ways to modify the game to make it rational.

Assisting others with withdrawing from a ZK rollup is rational if we add a way to micro-pay for the service, so there is really little cause for concern that you won't be able to exit from a rollup with any significant use.

Meanwhile, the greater risks of the other systems can be alleviated if we agree as a community to not accept 51% attack chains that revert too far in history or censor blocks for too long.

Conclusion: when someone says that a system "depends on trust", ask them in more detail what they mean! Do they mean 1 of 1, or 1 of N, or N/2 of N? Are they demanding these participants be altruistic or just rational? If altruistic, is it a tiny expense or a huge expense?

And what if the assumption is violated - do you just need to wait a few hours or days, or do you have assets that are stuck forever? Depending on the answers, your own answer to whether or not you want to use that system might be very different.

Originally published as “Trust Models”

Enter the Blockchain Writing Contest

Even when their interests might change and push them to act in some different unexpected way in the future.

Blockchain applications are never fully trustless, but some applications are much closer to being trustless than others. If we want to make practical moves toward trust minimization, we want to have the ability to compare different degrees of trust.

For the purposes of analyzing blockchain protocols, I tend to break down trust into four dimensions:

How many people do you need to behave as you expect?
Out of how many?
What kinds of motivations are needed for those people to behave? Do they need to be altruistic, or just profit seeking? Do they need to be uncoordinated?
How badly will the system fail if the assumptions are violated?

For now, let us focus on the first two. We can draw a graph:

image

The more green, the better. Let us explore the categories in more detail:

1 of 1: there is exactly one actor, and the system works if (and only if) that one actor does what you expect them to. This is the traditional "centralized" model, and it is what we are trying to do better than.
N of N: the "dystopian" world. You rely on a whole bunch of actors, all of whom need to act as expected for everything to work, with no backups if any of them fail.
N/2 of N: this is how blockchains work - they work if the majority of the miners (or PoS validators) are honest. Notice that N/2 of N becomes significantly more valuable the larger the N gets; a blockchain with a few miners/validators dominating the network is much less interesting than a blockchain with its miners/validators widely distributed. That said, we want to improve on even this level of security, hence the concern around surviving 51% attacks.
1 of N: there are many actors, and the system works as long as at least one of them does what you expect them to. Any system based on fraud proofs falls into this category, as do trusted setups though in that case the N is often smaller. Note that you do want the N to be as large as possible!
Few of N: there are many actors, and the system works as long as at least some small fixed number of them do what you expect them do. Data availability checks fall into this category.
0 of N: the systems works as expected without any dependence whatsoever on external actors. Validating a block by checking it yourself falls into this category.

While all buckets other than "0 of N" can be considered "trust", they are very different from each other!

Trusting that one particular person (or organization) will work as expected is very different from trusting that some single person anywhere will do what you expect them to.

Particularly, note that even the correctness of the software you're running typically depends on a "few of N" trust model to ensure that if there's bugs in the code someone will catch them.

With that fact in mind, trying really hard to go from 1 of N to 0 of N on some other aspect of an application is often like making a reinforced steel door for your house when the windows are open.

Another important distinction is: how does the system fail if your trust assumption is violated? In blockchains, two most common types of failure are liveness failure and safety failure.

A liveness failure is an event in which you are temporarily unable to do something you want to do (eg. withdraw coins, get a transaction included in a block, read information from the blockchain).

A safety failure is an event in which something actively happens that the system was meant to prevent (eg. an invalid block gets included in a blockchain).

Channels (incl state channels, lightning network): 1 of 1 trust for liveness (your counterparty can temporarily freeze your funds, though the harms of this can be mitigated if you split coins between multiple counterparties), N/2 of big-N trust for safety (a blockchain 51% attack can steal your coins)
Plasma (assuming centralized operator): 1 of 1 trust for liveness (the operator can temporarily freeze your funds), N/2 of big-N trust for safety (blockchain 51% attack).
Plasma (assuming semi-decentralized operator, eg. DPOS): N/2 of small-N trust for liveness, N/2 of big-N trust for safety.
Optimistic rollup: 1 of 1 or N/2 of small-N trust for liveness (depends on operator type), N/2 of big-N trust for safety.
ZK rollup: 1 of small-N trust for liveness (if the operator fails to include your transaction, you can withdraw, and if the operator fails to include your withdrawal immediately they cannot produce more batches and you can self-withdraw with the help of any full node of the rollup system); no safety failure risks
ZK rollup (with light-withdrawal enhancement): no liveness failure risks, no safety failure risks

Meanwhile, the greater risks of the other systems can be alleviated if we agree as a community to not accept 51% attack chains that revert too far in history or censor blocks for too long.

Originally published as “Trust Models”

How a Chinese Stablecoin Is Changing the Way the World Trades

delabs@newsletter.paragraph.com (Real Block) — Thu, 28 Apr 2022 06:23:36 GMT

China is now the largest trading partner of most countries in the world, which are buying more products from China than from any other nation. China has also become a major destination for products from those countries.

Historically, the vast majority of cross-border B2B and B2C trades have been settled predominantly in U.S. dollars (USD). However, recent trends indicate more and more trades are settled in Chinese yuan (CNY) – more specifically in offshore Chinese yuan (CNH). These free-floating reserves of Chinese yuan (also known as renminbi) are traded in offshore centers including Hong Kong, Singapore, London and Luxembourg. Last year there was a 76% increase in the value of transactions handled in the Chinese currency to RMB 80 trillion (around US$12.5 trillion) while the number of transactions increased by 51.5% to 3.34 million transactions.

A report by the International Monetary Fund in March 2022 noted the “stealth erosion” of the dollar’s dominance as a currency reserve. In the past decade, various countries have started to gradually shift away from it, and some of them have already implemented local currency settlements for bilateral trades. It is not a coincidence the yuan has appreciated against the dollar by more than 12% since September 2019 and continues to offer higher, real yields as well as a range of attractive investment opportunities, as reported by the Asian Times in April 2022. Exposure to CHN is also a part of a safe asset diversification strategy for investors looking for dynamic new alternatives. For residents of emerging/underdeveloped economies where inflation is rampant, it’s a powerful tool to hedge against the depreciation of the local currency.

In parallel with this move away from the U.S. dollar and toward the offshore Chinese yuan as a settlement currency, there are strong forces at work accelerating a global trend of moving away from SWIFT transfers by traditional banks and toward innovative cryptocurrency transfers.

However, the use of cryptocurrencies to settle trades or to invest has been hampered by price volatility. The inherent risk of price fluctuation with traditional cryptocurrencies can be circumvented by using stablecoins pegged to a fiat currency.

CNHC is one of these stablecoins, and it is increasingly being used by exporters and importers to settle their transactions with China. It is backed 1:1 by offshore CNH deposits held by a custodian bank in Singapore.

CNHC facilitates B2B/B2C cross-border trade settlement with slashed forex costs and 24/7 availability. Transactions are compliant and traceable. Most importantly, users do not need a RMB-denominated bank account to hold and trade CNH.

CNHC is already used by hundreds of companies in Asia, Africa and Latin America to settle international trade. By the end of 2021, the total monthly transaction volume of CNHC had reached CNH 200 million.

Earlier this year, the Hoover Institution in Washington, D.C., a distinguished American think-tank, released a report titled “Digital Currencies – The US, China and the World at a Crossroads.” In this report, the Institute specifically mentioned CNHC and how it is gaining traction both from its end users but also from a policy standpoint within the Chinese government. The report noted, “... China’s government could leave an open door for yuanization with RMB stablecoins such as CNHC. This could potentially set up a proxy competition in some emerging-market economies between US dollars and RMB stablecoins.”

The way that global trade is being settled is evolving at an accelerated pace. Small and mid-sized enterprises (SME) are frustrated with high costs, long delays and politics dragging down their activities. They are looking for a new way to transact without being held hostage by geopolitical interests or sky-high fees by traditional payment services providers. Stablecoins such as CHNC not only offer new ways to diversify portfolios and manage liquidity; they are also the future way to settle cross-border trade. The high rate of adoption of CNHC for trading purposes shows this future is rapidly becoming reality.

Go-to-Market in Web3: New Mindsets, Tactics, Metrics | Future

delabs@newsletter.paragraph.com (Real Block) — Tue, 08 Feb 2022 06:53:44 GMT

Every company faces some version of the “cold start problem”: How do you get started from nothing? How do you acquire customers? How do you create network effects — where your product or service becomes more valuable to its users as more people use it — that create incentives for even more customers to sign up?

In short, how do you “go to market” and convince potential customers to spend their money, time, and attention on your product or service?

The response by most organizations in web2 — the Internet era defined by large centralized products/services like Amazon, eBay, Facebook, and Twitter, in which the vast majority of value accrues to the platform itself rather than to the users — is to invest significantly in sales and marketing teams as part of a traditional go-to-market (GTM) strategy that focuses on generating leads and acquiring and retaining customers. But in recent years, a whole new model of organization-building has emerged. Rather than being controlled by corporations — with centralized leadership making all decisions about the product or service, even when using consumers’ data and free, user-generated content — this new model leverages decentralized technologies and brings users into the role of owners through the digital primitive known as tokens.

This new model, known as web3, changes the entire idea of GTM for these new kinds of companies. While some traditional customer acquisition frameworks are still relevant, the introduction of tokens and novel organizational structures such as decentralized autonomous organizations (DAOs) requires a variety of go-to-market approaches. Since web3 is still new to so many, yet there’s tremendous building in the space, in this article I share some new frameworks for thinking about GTM in this context, as well as where different types of organizations may exist in the ecosystem. I’ll also offer some tips and tactics for builders looking to create their own web3 GTM strategies as the space continues to evolve.

The catalyst of new go-to-market motions: tokens

The concept of the customer acquisition funnel is core to go-to-market, and is very familiar to most businesses: going from awareness and lead generation at the top of the funnel to converting and retaining customers at the bottom of the funnel. Traditional web2 go-to-market therefore attacks the cold-start problem through this very linear lens of customer acquisition, encompassing areas such as pricing, marketing, partnerships, sales channel mapping, and sales force optimization. Success metrics include time to close a lead, site click-through rate, and revenue per customer, among others.

Web3 changes the whole approach to bootstrapping new networks, since tokens offer an alternative to the traditional approach to the cold-start problem. Rather than spending funds on traditional marketing to entice and acquire potential customers, core developer teams can use tokens to bring in early users, who can then be rewarded for their early contributions when network effects weren’t yet obvious or started. Not only are those early users evangelists who bring more people into the network (who would like to similarly be rewarded for their contributions), but this essentially makes early users in web3 more powerful than the traditional business development or salespeople in web2.

For example, lending protocol Compound [full disclosure: we’re investors in this and some of the other organizations discussed in this piece] used tokens to incentivize early lenders and borrowers by providing extra rewards in the form of COMP tokens for participating, or “bootstrapping liquidity,” with a liquidity mining program. Any users of the protocol, whether a borrower or lender, received COMP tokens. After the program launched in 2020, total value locked (TVL) in Compound jumped from ~$100M to ~$600M. It’s worth noting that while token incentivization attracts users, it alone is not enough to make them “sticky”; more on this later. While traditional companies do incentivize employees through equity, they rarely financially incentivize customers in a long-term way (other than through acquisition discounts or referral bonuses).

To summarize: In web2, the primary GTM stakeholder is the customer, typically acquired via sales and marketing efforts. In web3, an organization’s GTM stakeholders include not just their customers/users, but also their developers, investors, and partners. Many web3 companies therefore find community roles to be more critical than sales and marketing roles.

The web3 go-to-market matrix

For web3 organizations, GTM strategies depend on where an organization fits in the below matrix, according to its organizational structure (centralized vs. decentralized) and economic incentives (no token vs. token):

Go-to-market differs in each of the quadrants, and can span everything from traditional web2-style strategies to emerging and experimental strategies. Here, I’ll focus on the upper right quadrant (decentralized team with token) and contrast it with the lower left quadrant (centralized team with no token) to illustrate the difference between web3 and web2 GTM approaches.

Decentralized with token

First, let’s look at the upper right quadrant. This includes organizations, networks, and protocols with unique web3 operating models, which in turn require novel go-to-market strategies.

Organizations in this quadrant follow a decentralized model (although they usually start with a core development team or operational staff) and use token economics to attract new members, reward contributors, and align incentives among participants. (For a deeper discussion of web3 business models and the seeming paradox of capturing value, check out this talk from a16z Crypto Startup School.)

The fundamental difference between the web3 organizations in this quadrant and those using a more traditional GTM model involves the key question: What is the product? Whereas web2 companies and those in the lower-left quadrant largely must start with a product that will attract customers (“come for the tools, stay for the network”), web3 companies approach go-to-market through the dual lenses of purpose and community.

Having a product and a solid technical foundation is still important, but it doesn’t have to come first.

What these organizations do need is a clear purpose that defines the reason they exist. What is the problem that they uniquely are trying to solve? This also means more than just raising money based on a white paper and founding team. It means having a strong community — not just being “community-led” or “community-first,” but also being community-owned — blurring the distinction between owner, shareholder, and user. What allows for long-term success in web3 is clear purpose, having an engaged and high-quality community, and matching the right organizational governance to that purpose and community.

Now let’s go deeper into the go-to-market motions in the two major categories of web3 organizations in the upper right quadrant: (1) decentralized applications; and (2) Layer 1 blockchains, Layer 2 scaling solutions, and other protocols.

GTM motions for decentralized applications

“Decentralized applications” covers use cases such as decentralized finance (DeFi), non-fungible tokens (NFTs), social networks, and gaming.

Decentralized Finance (DeFi) DAOs

One major category of decentralized applications are decentralized finance (DeFi) applications, such as decentralized exchanges (e.g., Uniswap or dYdX) or stablecoins (e.g., MakerDAO’s Dai). While they might have similar go-to-market motions as a standard, non-decentralized application, value accrues differently due to the organizational structures and token economics.

Many DeFi projects follow a path where the protocol is first developed by a centralized development team. Following the launch of its protocol, the team often seeks to decentralize the protocol in order to increase its security and to distribute management of its operation to a decentralized group of token holders. This decentralization is typically accomplished through the simultaneous issuance of a governance token; the launch of a decentralized governance protocol (typically a decentralized autonomous organization, or DAO); and the granting of control over the protocol to the DAO.

This decentralization process can involve many different structures and entity forms. For instance, many DAOs do not have any legal entity affiliated with them and operate solely in the digital world, while others use multi-signature (“multisig”) wallets that act at the direction of the DAO. In certain cases, nonprofit foundations are established to oversee future development of the protocol at the direction of the DAO. In nearly all cases, the original developer team continues to operate, in order to act as one of many contributors to the ecosystem created by the protocol as well as to develop supplemental or ancillary products and services. (This white paper contains more details on legal frameworks for DAOs, from taxation and entity formation to operational issues and considerations.)

Here are two popular DeFi examples:

MakerDAO started as a DAO in March 2015, established a foundation in June 2018, and retired its foundation in July 2021. MakerDAO has a stablecoin, Dai, whose purpose is to enable its users to transact in a fast, low-cost, borderless, and transparent way with a stable unit of value. This could be through purchasing goods and services or engaging with other DeFi applications. It also has a governance token, MKR. The DAO approves various governance changes as well as certain parameters of the protocol’s operation, including the collateralization ratios the protocol uses to mint DAI.
The Uniswap protocol was launched by a centralized company, but is now owned and governed by the Uniswap DAO, which is controlled by UNI token holders. Uniswap Labs, the creator of the protocol, operates one interface to the Uniswap protocol and is one of many developers contributing to the protocol’s ecosystem.

So what does go-to-market look like here? Take the example of Dai, the algorithmic stablecoin issued and governed by MakerDAO. One goal for most algorithmic stablecoin issuers such as MakerDAO is to generate more usage of their stablecoin in the financial ecosystem. The go-to-market motion is therefore to have it: 1) listed on cryptocurrency exchanges for retail and institutional trading; 2) integrated into wallets and applications; and 3) accepted as payment for goods or services. Today, there are over 400 Dai markets, it is integrated into hundreds of projects, and it is accepted as a form of payment through major commerce solutions like Coinbase commerce.

How did they do it? MakerDAO initially accomplished this through a more traditional business development team that was driving many early partnerships and integrations. However, as it increased its decentralization, the business development function became the responsibility of the growth core unit, a sub-community of Maker token holders often referred to as a SubDAO. Additionally, since MakerDAO is decentralized and its protocol’s operation is trustless and permissionless, anyone can generate or buy Dai using the protocol. And because Dai’s code is open source, developers can integrate it into their apps in a self-service manner. As time went on and the protocol became more self-service — with better developer documentation and more integration playbooks — other projects were able to build off that at scale.

Go-to-market metrics for DeFi DAOs: With new go-to-market strategies for web3 come new ways of measuring success. For DeFi apps, the canonical success metric is the aforementioned total value locked (TVL). It represents all the assets using a protocol or network for things like trading, staking, and lending.

However, TVL is not an ideal metric to measure long-term organizational health and success. Although new DeFi protocols can copy open-source code, offer high yields, and attract significant financial inflows and TVL, this is not necessarily sticky — traders often leave as soon as the next project pops up.

The more critical metrics to track, therefore, are areas such as number of unique token holders; community engagement frequency and sentiment; and developer activity. Additionally, since protocols are composable — able to be programmed to interact with and build on each other — another key metric here is integrations. Number of and type of integrations track how and where the protocol is used in other applications, such as wallets, exchanges, and products.

Social, culture, and art DAOs

For social, culture, and art DAOs, go-to-market means building a community with a specific purpose — sometimes even starting as a text chat between friends — and growing it organically by finding other people who believe in that same purpose. But isn’t this “just a group chat” or just like traditional crowdfunding on Kickstarter, for instance?

No, because while organizers of traditional web2 crowdfunding projects may also have a clear purpose, they have to be much more clear about the means of achieving that purpose top-down. The project originators typically outline a detailed breakdown of how funds raised will be used, a clear product roadmap, and a comprehensive timeline. In the web3 model, the purpose is paramount, but the methods are often figured out later — including how funds will be used, the product roadmap, and the timeline.

For instance, with ConstitutionDAO, the purpose was buying a copy of the U.S. Constitution; for Krause House, the purpose is buying an NBA team and pioneering fan governance of a team; for LinksDAO, it is creating a virtual country club with a community of golf enthusiasts; and for PleasrDAO, it is for collecting, displaying, and creatively adding/sharing back to the community NFTs to represent culturally significant ideas and movements.

In the case of ConstitutionDAO, which raised $47M from a community of strangers that came together around this purpose, the entire process came together in a matter of weeks, and started with a clear purpose and raising money for that specific purpose only. ConstitutionDAO did not have much else — no clear roadmap, execution plan, or even a token at that point (it was created after the bid was unsuccessful). Individuals who contributed financially were so aligned with the purpose, and motivated by the community, that they simply wanted to contribute and spread the word, filling Twitter with emoji scrolls that became a meme.

Friends with Benefits is a token-gated social DAO that started as a token-gated Discord server for web3 creatives. In addition to a minimum buy-in of $FWB tokens, which represents membership in the DAO, potential members must apply to FWB through a written application. The community grew, connected in various Discord channels, ran IRL events, and eventually realized that one of the products they could build was a token-gated events app. FWB gives creatives a real stake in the community, while the DAO framework enables large-scale coordination of this decentralized social group to do things like allocate budget and accomplish projects ranging from publishing content to producing events.

**Go-to-market metrics for social DAOs: **One of the key measures of health of a DAO is quality engagement of the community, which can be measured through the primary communications and governance platforms it uses. For example, a DAO can track channel activity on Discord; member activation and retention; attendance on community calls, governance participation (who is voting on what, and how often); and actual work being done (number of paid contributors).

Other metrics might be net-new relationships built, or measuring trust developed among DAO community members. Although some tools and frameworks do exist here, social DAO metrics are still an emerging space, so we’ll see more tools emerge and evolve here as the space evolves.

Game DAOs

Today, most web3 games, whether play-to-earn, play-to-mint, move-to-earn, or another type, closely resemble popular web2 counterparts — but with two key distinctions: ****

The use of in-game assets native to open, global blockchain platforms rather than the closed, controlled economies found in traditional pay-to-own and free-to-play titles; and
The ability of game players to become true stakeholders and have a say in the governance of the game itself.

In web3 gaming, go-to-market strategy is built through platform distribution, player referrals, and partnerships with guilds. Guilds such as Yield Guild Games (YGG) allow new players to start playing a game by loaning them game assets that they might otherwise not be able to afford. Guilds choose what games to support by looking at three factors: the quality of the game; the strength of the community; and the robustness and fairness of the game economy. Game, community, and economic health must all be maintained in tandem.

While developers of blockchain-based games might have a lower ownership percentage and/or take rate, by incentivizing players as owners the developers are helping grow the overall economy for all.

But unlike in web2, purpose and community lead. For instance, Loot, a game that started with content first before moving to gameplay, is an example of purpose and community, rather than product, driving GTM. Loot is a collection of NFTs, each known as a Loot bag, which have a unique combination of adventure gear items (examples include a dragonskin belt, silk gloves of fury, and an amulet of enlightenment). Loot essentially provides a prompt — or building block primitive — upon which games, projects, and other worlds can be built. The Loot community has created everything from analytics tools to derivative art, music collections, realms, quests, and more games, inspired by their Loot bags.

The key idea here is that Loot grew not due to an existing product that users flocked to, but because of the idea and lore it represented — an open, composable network that welcomed creativity and incentivized users through tokens. The community makes the product — it’s not the network making the product in hopes it will attract a community. As such, a key metric here would be the number of derivatives, for instance, which could be considered even more valuable here than traditional metrics would.

GTM motions for Layer 1 blockchains and other protocols

In web3, Layer 1 refers to the underlying blockchain. Avalanche, Celo, Ethereum, and Solana are all examples of Layer 1 blockchains. These blockchains are all open source, so anyone can build on top of them, replicate or alter them, and integrate with them. Growth of these blockchains comes from having more applications built on top of them.

Layer 2 refers to any technology that operates on top of an existing Layer 1 to help solve scalability challenges with Layer 1 networks. One type of Layer 2 solution is a rollup. Layer 2 rollups do just that — they “roll up” transactions off chain and then post the data back onto the Layer 1 network via a bridge. There are two primary categories of Layer 2 rollups. The first, optimistic rollups, “optimistically” assume the transaction is honest and not fraudulent via a fraud proof. The second, zk rollups, use “zero knowledge” proofs to determine the same. The majority of these Layer 2 solutions are currently being developed for Ethereum and do not yet have their own token, but we will discuss them here as their go-to-market success metrics are similar to those of the other networks in this category.

Additionally, protocols can be built on top of other L1s or L2s, with the Uniswap protocol, for example, supporting Ethereum (L1), Optimism (L2), and Polygon (L2).

Growth of Layer 1 blockchains, Layer 2 scaling solutions, and these other protocols can come from forks, which are when a network is replicated and then altered. For example, Ethereum, a Layer 1 blockchain, was forked by Celo. Optimism, a Layer 2 scaling solution, was forked by Nahmii and Metis. And Uniswap was forked to create SushiSwap. While this may initially seem negative, the number of forks that a network has can actually be a measure of success — it shows that others want to copy it.

* *

These examples and mindsets all focus on the upper right quadrant, decentralized networks with tokens — broadly speaking, the current most advanced examples of web3. However, depending on the type of organization, there is still a fair amount of blending of web2 GTM strategies and emerging web3 models. Builders should understand the range of approaches as they begin to develop their go-to-market strategy, so let’s now take a look at a hybrid model that blends web2 GTM with web3 GTM strategies.

Centralized and no token: The web2-web3 hybrid

Many of the companies in this lower left quadrant (centralized team with no token) provide entry points and interfaces for users to access web3 infrastructure and protocols.

In this quadrant, there is significant overlap in go-to-market strategies between web2 and web3 — especially in the areas of SaaS and marketplaces.

Software-as-a-service

Some companies in this quadrant follow the traditional software-as-a-service (SaaS) business model, for example Alchemy, which provides nodes-as-a-service. These companies offer infrastructure-on-demand through various tiers of subscription fees, determined by considerations such as amount of storage needed, whether nodes are dedicated or shared, and monthly request volume.

The SaaS business model generally requires a traditional web2 go-to-market motion and incentives. Customer acquisition is through a combination of product-led and channel-led strategies:

Product-led user acquisition is focused on getting users to try the product itself. For example, one of Alchemy’s products is Supernode, an Ethereum API targeted at any organization that is building on Ethereum but that doesn’t want to manage its own infrastructure. In this case, customers would try Supernode via a free tier or freemium model, and those customers would recommend the product to other potential customers.

In contrast, channel-led user acquisition is focused on segmenting out different customer types (for example, public-sector vs. private-sector customers), and having sales teams aligned to those customers. In this case, a company might have a sales team focused solely on public-sector customers such as government and education, and would deeply understand the needs of that type of customer.

I’m providing an overview in this article to help explain the difference between web2 and web3 go-to-market strategies, but it’s important to note that developer-focused outreach and developer relations — including developer documentation, events, and education — is also very important here.

Marketplaces and exchanges

Other companies in this quadrant lean on the relatively familiar-to-consumer models of marketplaces and exchanges, such as peer-to-peer horizontal NFT marketplace OpenSea and cryptocurrency exchange Coinbase. These businesses generate revenue — the “take” — based on a transaction fee (typically a percentage of the transaction), which is similar to the business models of classic web2 marketplaces such as eBay and Amazon.

For these types of companies, revenue growth comes from growing the number of listings, the average dollar value of each listing, and the number of users of the platform — all of which lead to increased transaction volume, while benefiting users in terms of variety, marketplace liquidity, and more.

A key go-to-market motion here is increasing channel distribution by partnering with other platforms to show a selection of items. This is similar to the Amazon affiliate program, in which bloggers can link to their favorite items, and any purchases made through those links give the blogger a commission. But a key difference from web2 is that web3 structures allow for royalty distributions back to the creator in addition to the affiliate fee. For example, OpenSea offers the traditional affiliate sales channel through their White Label program, in which purchases made through a referral link give a percentage of the sale to the affiliate, but it also allows for royalties, in which creators can continue to earn a percentage of any secondary sales. (This web3 feature is uniquely made possible by crypto because smart contracts can encode the percentage arrangement up front, blockchain tracks provenance, and more.)

Since creators now have an opportunity to continue to monetize their work through the secondary markets — value they previously could not see, let alone capture, in web2 systems — they are incentivized to continue to promote the marketplace. Creators become evangelists as well.

GTM tactics

Now that I’ve shared an overview of key mindsets and example use cases, let’s take a look at specific go-to-market tactics often seen in web3 organizations. These are the core ingredients, not a complete playbook, but can still help builders entering and exploring the space understand the tactics and options.

Airdrops

An airdrop is when a project distributes tokens to users to reward certain behavior that the project wants to incentivize, including testing the network or protocol. These can be distributed to all existing addresses on a given blockchain network, or targeted (such as to specific key influencers); often, they are used to solve the cold start problem — to bootstrap early adoption, award or incent early users, and more.

In 2020, Uniswap airdropped 400 UNI to anyone who had used the platform. In September 2021, dYdX airdropped DYDX to users. More recently, ENS conducted an airdrop to anyone with an ENS domain (a decentralized .eth domain); the airdrop was conducted in November 2021, but anyone who owned an ENS domain before October 31, 2021, was/is eligible (until May 2022) to claim $ENS tokens, which provide holders with governance rights with respect to the ENS protocol.

In the non-fungible token space, airdrops for NFT projects are also growing in popularity to help with giving more people access and other reasons. One recent notable airdrop was from the Bored Ape Yacht Club, a collection of 10,000 unique NFTs; on August 28, 2021, BAYC created the corresponding Mutant Ape Yacht Club. Each of the BAYC token holders received a mutant serum, allowing them to mint 10,000 “mutant” apes, and additionally a new 10,000 mutant apes became available for new entrants. Because there were different types of serums, serums could only be used once, and since a Bored Ape could not use multiple serums of the same tier, serums added a new scarcity model.

The rationale behind the creation of the MAYC was to “reward our ape holders with an entirely new NFT” — a “mutant” version of their ape — while also allowing newcomers into the BAYC ecosystem at a lower tier of membership. This maintains accessibility to the broader community, while not diluting the exclusivity of the original set or having those original owners feel like their contributions were downgraded. (Another way of addressing accessibility is with NFT fractionalization, where an NFT has multiple owners.) The MAYC floor price, or lowest listed price for a MAYC, is consistently lower than the BAYC floor price, but owners essentially have the same benefits.

These airdrops were done retroactively to reward NFT holders or network and protocol users (as was the ENS airdrop), but airdrops can also be used as a *proactive *GTM motion to generate awareness for a specific project and to encourage people to check it out. Since information is public on the blockchain, a new project can airdrop to, for example, all the wallets using a specific marketplace, or all the wallets holding a specific token.

In any case, projects should clearly articulate their overall token distribution, breakdown, and plans before conducting the airdrop. There are many examples of airdrops being used for nefarious purposes and of airdrops gone wrong. In addition, airdrops of tokens can be deemed to be securities offerings in the United States, so projects should consult counsel prior to engaging in any such activity.

Developer grants

Developer grants are grants made from a protocol’s treasury to individuals or teams who are contributing in some way to improving the protocol. This can serve as an effective GTM mechanism for DAOs, since developer activity is such an integral part of a protocol’s success. Examples of projects and protocols with developer grants include Celo, Chainlink, Compound, Ethereum, and Uniswap.

But grants can be given for everything from protocol development to bug bounties, code audits, and other activities beyond coding. Compound even has a type of grant related to business development and integrations, funding any integrations that grow the usage of Compound. An example of this is their funding of a grant that integrated Compound with Polkadot.

Memes

Viral images with text overlays are another GTM tactic for web3 organizations. Given the complexity and breadth of the cryptocurrency ecosystem and the short attention spans of social media users, memes allow information to be rapidly conveyed. Memes can also signal belonging, community, goodwill, and more in a highly information-dense way.

The NFT project Pudgy Penguins, a collection of 8,888 penguins, started due to its meme-ability. The primary drop of the collection sold out in 20 minutes, and the collection was featured in major media outlets, which in turn helps mainstream such projects. The social display and community element of “PFP” (profile picture) collections — in web3 this is coming about as NFTs displayed as an owner’s profile picture on social media — also allow for this virality. Twitter recently rolled out a feature allowing users to prove their ownership of an NFT via hexagonal-shaped profile pictures linking to OpenSea’s API.

Owners with large social media followings generate awareness of a project when they change their profile picture to one from that project, and project owners typically follow all other owners of the same project. These moves can in turn also beget other memes, as in the case of Crypto Covens and the “web2 me vs. web3 me” meme where users came to display their witches alongside their actual faces, signaling identity, belonging, and more.

***

So what does this all mean for web3 founders? The biggest mindset shift is moving from planning to something more like gardening.

In web2 companies, founders not only set a top-down vision but are responsible for growing a team and planning and executing against that vision. In web3, founders take on more the role of a gardener, helping cultivate and nurture potentially successful products but also setting up the space for it all to happen. While web3 founders still set the purpose of the organization, and its initial governance structure, the governance structure itself might quickly lead to new roles for them. Instead of optimizing for headcount growth or revenue and profitability, founders might be optimizing for protocol usage and quality of community. In addition, following any decentralization, founders must adapt to environments in which no hierarchical power structures exist, and where they are one of many actors championing the success of a given project. As such, prior to decentralizing, founders should ensure that they are setting up their project for success in such an environment.

I witnessed some of this firsthand when I was chief of staff to Tony Hsieh, former CEO of Zappos.com, an e-commerce company now owned by Amazon. The company experimented with more decentralized (compared to only top-down) governance structures beginning in 2014, including the self-organized management system known as “holacracy.” Holacracy involved a hierarchy of work rather than of people, and had mixed results. But Hsieh offered a useful metaphor when comparing his role as being the cultivator of a greenhouse of plants (in the holacracy model), rather than being the best plant. He had said he needed to be the “architect of the greenhouse” — setting the right conditions to enable all the* other* plants to flourish and thrive.

Today, Alex Zhang, Mayor of Friends with Benefits (FWB), the social DAO with a fungible token, echoes the sentiment, describing that his job “is not to set a top-down vision” but to facilitate the creation of “frameworks, permits, and regulations for community members” to approve and to build on top of. Where a web2 leader would be focused on updating the product roadmap and driving toward new product launches, Zhang considers himself more of a gardener rather than a top-down builder. His role includes watching the FWB “neighborhood” (in this case, Discord channels) and curating it by retiring channels with little traction and helping support and grow channels that have momentum. By creating a framework for these channels — and playbooks for channel success (such as a mix of activity, clear leadership, and governance structures) — Zhang becomes more of an educator and communicator.

In the case of founders of NFT projects, their role is primarily as originators and temporary stewards of intellectual property (IP). Yuga Labs, the creators of Bored Ape Yacht Club, wrote, “We see ourselves as temporary stewards of IP that is in the process of becoming more and more decentralized. Our ambition is for this to be a community-owned brand, with tentacles in world-class gaming, events, and streetwear.” Owning an NFT — whether it’s an image, a video or sound clip, or another form — conveys to the owner all the rights associated with the NFT. As the NFT is bought and sold, that ownership is transferred — and as ecosystems grow around the NFT, those benefits go to the NFT owner, not just the founding team of the NFT project.

NFT ownership can also be about community-driven licensing and community-driven content (unlike traditional IP franchises). An example here is Jenkins The Valet, an NFT avatar from the BAYC collection (specifically, Ape #1798) that signed with Creative Artists Agency (CAA) for representation across various forms of media. Jenkins was created by Tally Labs, the group that owns Ape #1798. Tally Labs decided to imbue the ape with its own brand and backstory, and turned the notion around of an NFT’s statistical rarity being the main determinant of its price and success. They then created a way for others to participate in creating content around Jenkins through a “writer’s room” NFT, where, for example, community members were able to vote on the genre of the first book.

So much more is possible here; we have yet to see what more is possible as more people embrace crypto and decentralized technologies and web3 models. Traditional web2 GTM frameworks are a useful reference, and offer some helpful playbooks — but they are just a few of the many frameworks available for web3 organizations. The key difference to remember is that the goals, growth, and success metrics of web2 and web3 are often not the same. Builders should start with a clear purpose, grow a community around that purpose, and match their growth strategies and community incentives — and with them, the go-to-market motions — accordingly. We will see a variety of models emerge, and look forward to observing and sharing more here.

Thanks to Justin Paine, Porter Smith, and Miles Jennings for their contributions to this article.

Maggie Hsu is a partner at Andreessen Horowitz leading go-to-market for the crypto portfolio. She previously led go-to-market for Amazon Managed Blockchain at Amazon Web Services.

Posted February 4, 2022

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Conviction Voting: A Novel Continuous Decision Making Alternative to Governance

delabs@newsletter.paragraph.com (Real Block) — Tue, 04 Jan 2022 06:55:51 GMT

A Commons Stack Component Explainer

This article is one of a series of component explainers for the Commons Stack infrastructure. One of the least understood yet most talked about pieces of the Commons Stack is the Conviction Voting (CV) governance module. We’ll take a closer look at this decision making mechanism, discussing why we need it, how it works, and where it fits into our tech stack for scalable commons stewardship.

The ultimate governance question: how do we make good decisions as a collective?

Conviction Voting — Why Do We Need It?

As we move into a future of automation, we want to ensure that human needs remain a key input of the socio-technical systems we are creating.

As we explored in our introduction to the Commons Stack, commons stewardship starts with managing shared resources in order to achieve mutual community goals. But how do we, as a collective, decide how those resources should be allocated? **Conviction Voting offers a novel decision making process that funds proposals based on the aggregated preference of community members, expressed continuously. In other words, **voters are always asserting their preference for which proposals they would like to see approved, rather than casting votes in a single time-boxed session. A member can change their preference at any time, but the longer they keep their preference for the same proposal, the “stronger” their conviction gets. This added conviction gives long standing community members with consistent preferences more influence than short term participants merely trying to influence a vote. Conviction Voting sidesteps sybil attacks, provides collusion resistance, and mitigates many of the attack vectors of time-boxed voting mechanisms.

An early conviction voting display prototype, demonstrating the growth and decay of aggregated conviction for a proposal from several members in a community.

As we move into a future of automation, we want to ensure that human needs remain a key input to the socio-technical systems we are creating. We’re generating an ever-growing deluge of data and relying on complex algorithms to analyze it and make suggestions for us, but so far we’ve struggled to capture human needs in these rich temporal data flows. Continuously sampling preferences through Conviction Voting will provide us with instantaneous data that allows us to account for people’s needs in our future decision making processes — especially as we use DAOs to experiment with new forms of real-time ‘cyber-physical’ governance.

The concept of Conviction Voting is designed from mathematical first principles specifically for the allocation of funds. It was derived from the paper on ‘Social Sensor Fusion’ by Dr. Michael Zargham, where humans are the “social sensors” reacting to proposals in their communities, each broadcasting continuously evolving preferences that are “fused” into an aggregated social signal. The design and functionality of our Conviction Voting module draws on decades of research on multi agent coordination problems and behavioral economics, with all the mathematical rigor that BlockScience is well known for.

Turning group decision making into a streamlined, continuous process would allow for the real-time feedback of human needs into our governance systems.

How Does Conviction Voting Work?

We need to be thinking outside the ‘time-box’ with complex system design.

Conviction Voting differs from other decision making mechanisms in that it does not order proposals in an A vs B fashion (like pairwise comparisons in Colony’s Budget Box, for example) — instead, the community entertains all nominated proposals at any given time. So a person could put half of their voting power behind proposal A, a quarter behind proposal B, and divide the remaining quarter between proposals C and D. You can think of each proposal as a bucket and your token-weighted opinion as a tap, pouring your preferences into selected proposals in the proportions that you choose.

A sketch demonstrating how a member might allocate their preference between 5 tabled proposals.

The longer you hold a preference for a certain proposal, the more that bucket fills up with your conviction. Your conviction grows according to a half life decay curve, giving more weight to that preference over time, up** **to a certain limit. If you decide to switch your preference to a new bucket, your conviction drains out of the previous proposal according to the decay function, as if there were a small hole in the bottom of each bucket. By using decay curves to define the accumulation and reduction of conviction, we introduce temporal dynamics into these systems, moving us closer to how systems work in nature. By dampening abrupt token movements, we eliminate the need for arbitrary token lock periods to avoid last minute vote swings. To get a grasp on how conviction accumulation would work, play around with our basic Conviction Voting applet we created to test out some initial system parameters, or check out this math-oriented HackMD created for ETHParis by DappLion.

As with all of our components, we took a biomimetic approach to the design of Conviction Voting. The analogy of the human brain can be used to understand the CV mechanism, where the increasing collective preference for a proposal can be compared with increasing action potential in a neuron. When the collective preference for a proposal reaches a preset threshold, the proposal is approved, just like the neuron fires when its action threshold is reached. This is how we can transform a continuous data stream of individual preferences into discrete acceptance of proposals in a manner similar to that found in nature. When we aggregate the opinions of a community in this way, we create a rich temporal data stream of collective preference for use in group decision making.

This graph shows community conviction growing for different proposals, each represented by different colors. The data comes from a cadCAD simulation of a Conviction Voting environment. Proposals are triggered once they reach the dotted line threshold, and have been live for 7 days.

Exploring Issues In On-Chain Voting

It is important to note several key differences between traditional voting and on-chain voting. In the absence of identity in blockchain networks, we cannot utilize one-person-one-vote systems, nor would we want to, as they can lead to a tyranny of the majority. Instead, we see one-token-one-vote systems, which allows voters to display the intensity of their preference. At this point in the crypto space, that means total plutocracy — this is a recognized problem and can be ameliorated by several mechanisms, among them Quadratic Voting, which reduces the impact of wealth on voting power. Alternatively, community members could be granted some set number of votes per month allocated to them via a token drip, to even out the distribution of voting power.

Pioneers in the blockchain space are experimenting wildly with new tools for human collaboration, but we must always question whether we are carrying unnecessary baggage from our legacy voting systems. What further assumptions can we drop to further streamline distributed decision making at scale? How about the assumption that voting needs to be time-boxed at all?

Attack Vectors Present In On-Chain Time-Boxed Voting:

Vote buying**, ****plutocracy ****and **sybil attacks are tactics that a wealthy bad actor can use to unfairly influence a voting process. Respectively, these terms refer to 1) bribing other voters to vote a certain way, 2) purchasing a significant amount of tokens to amplify one’s vote, or 3) splitting up their token holdings among many accounts to gain undue influence over a decision. These issues plague many of today’s on-chain voting systems.
Last minute vote swings** — as seen in multiple on-chain voting scenarios, time-boxed voting is particularly susceptible to manipulation in the moments before it ends. Strategic voters wait to view early results before weighing in with their vote at the end of the session to tip the balance in their favor. This is partially addressed through mechanisms such as wait for quiet voting, **which extends the duration of a vote in case of a last minute change in outcome (though this approach is vulnerable to filibustering as an attack vector) or PLCR voting, which keeps the results of a vote secret until polls close, but also introduces extra UX difficulties and potential liquidity complications caused by arbitrary token lock periods.
On-chain voter apathy — if we thought our voter turnout for political elections was bad, participation in on-chain voting has so far been even worse, with as few as 3.8% of voting tokens participating in the most recent Aragon AGP vote. As it turns out, despite all our talk about decentralized governance, not that many people are actively engaging in it! On-chain voting systems have difficulty with smooth user experience, where voters can be required to send multiple transactions to confirm a vote within narrow time periods, all on clunky blockchain user interfaces. This low turnout of voters could easily lead to results that do not accurately represent community sentiment, which is arguably a massive flaw in these new decentralized decision making systems. So let’s continue to search for improvements!

An early concept design for a Conviction Voting interface

How Conviction Voting Can Help Address These Attack Vectors:

With a continuous voting mechanism, attackers will find that ‘vote buying’ becomes ‘vote renting’. To significantly influence a continuous stream of preference broadcasting, an attacker would need to continually expend funds to bend the system towards their desired outcomes, rather than purchasing the votes once to obtain their desired outcomes indefinitely. In other words, CV significantly raises the costs of influencing the system over long periods of time, thus reducing the vote buying attack vector and increasing collusion resistance. Conviction Voting also empowers token holders who have been persistent in their preference, since votes for a proposal gains ‘conviction’ as time passes. This ensures that long standing minority opinions are given additional weight to reduce the volatility introduced by new inflows of wealth into established communities. What’s more, Conviction Voting is sybil-resistant, as it removes the opportunity for large token holders to gain undue influence by splitting up their token holdings into multiple accounts.
Most last minute vote swings are caused by frictionless token movements, i.e. the ability to allocate large amounts of tokens at any point during the time-boxed vote. By restricting preference/token allocation using decay curves, we eliminate large token holders’ ability to influence votes at the last minute, and instead reward voters who display consistent, long held preferences. Through this design we can eliminate the necessity of clunky token locks that threaten system liquidity, and instead replace them with dynamic flows represented by these decay functions.
To address on-chain voter apathy, we want to make voting as easy as possible. When a member joins the community, they will be requested to assert percentages of their preference towards existing proposals, adding up to 100% in total. Using something like the ERC-888 token standard, we can **allow tokens to be automatically asserted towards proposals, without affecting token liquidity with staking locks. Since your preferences are expressed as a percentage of your token holdings, any change to your token holdings (through buying or selling) automatically updates the weight of your preference. Conviction Voting also **eliminates the need for **complicated commit-reveal schemes, and instead allows a user to check in and update their preferences at any time, freeing users from having to check in constantly or risk “missing” a vote. Founding community members — we call them ‘hatchers’ — will be incentivized to vote consistently by unlocking vested tokens that they own according to the amount of work done in the community, something we are calling KPI-based vesting (i.e. how many proposals are passed and completed and how much funds flow through the funding pool). We are also interested in implementing liquid democracy in the future to allow those who would rather delegate their vote to more knowledgeable, trusted members of their communities, further cutting down on cognitive overhead for voters.

Watch Conviction Voting in action! Pulled from our early CV model in cadCAD, this diagram shows token holders arranged on the left, asserting their preferences towards the various proposals arranged on the right. The darker the line, the heavier the token weight. Blue proposals are acquiring conviction, yellow are live proposals that have been approved, and green are proposals that have been approved and completed.

Where Does Conviction Voting Fit Into the Commons Stack?

The Conviction Voting component sits between the Augmented Bonding Curve, where voting tokens are acquired, and the Giveth Proposal Engine, which includes concrete Milestones and fund allocation for an approved proposal, once sufficient support has been accumulated to activate the trigger function.

*A diagram of a cyber-physical commons, built from the Commons Stack library. The Conviction Voting component of the system is displayed in purple, between the Augmented Bonding Curve (black) and the Giveth Proposal Engine (green). *This diagram is explored further in this video.

This design of the Conviction Voting module is being simulated and tested in cadCAD, one of the first times token engineering design tools are being applied to model system behavior in a complex governance process. There are many more details to explore in a forthcoming deep dive article — stay tuned!

Where to From Here?

This basic implementation of Conviction Voting is an MVP and is by no means a feature complete mechanism, nor are we suggesting it be appropriate for use in all scenarios. The **design space is wide open for alternative governance mechanisms **that mimic how decisions are made in natural systems, and we are excited to explore those design options through future improvements and additions to the Commons Stack component library, pending funding for our build phase. Further additions to the Conviction Voting mechanism could include delegations via liquid democracy and a reduction in the impact of wealthy participants via quadratic voting or an equivalent mechanism, though **these features will depend on (forthcoming) self-sovereign identity solutions **such as iden3.

Continuous voting mechanisms like Conviction Voting offer massive improvements over traditional forms of on-chain voting, and we’re excited to see where an exploration of this design space ends up. **You can help make this research a reality by **funding the build phase of the Commons Stack, so we can all benefit from a library of open source governance modules to be forked and used by projects as appropriate. We don’t believe there is a single answer to the question of governance — instead, we aim to facilitate an open ecosystem of components so that projects can choose what works best for them. We want to see experimentation proliferate in all directions, using robust cryptoeconomic primitives, and allow Darwinian market processes to decide what works best!

Taking the first steps towards real-time collaborative decision making!

The Network State-Summary

delabs@newsletter.paragraph.com (Real Block) — Mon, 27 Dec 2021 02:58:00 GMT

https://1729.com/summary

FROM @balajis

Writing a book is a commitment for reader and writer alike. So in the event you're deciding whether to make that commitment, here's a minimum description length-motivated summary of the key concepts behind the Network State. We'll do the one sentence, one page, and one thousand word versions. For the ten page version, read chapter one. And for the one hundred-plus-page version, read the whole thing.

One sentence

A network state is a social network with an agreed-upon leader, an integrated cryptocurrency, a definite purpose, a sense of national consciousness, and a plan to crowdfund territory.

One page

Technology has allowed us to start new companies, new communities, and new currencies. But can we use it to create new cities, or even new countries? A key concept is to go cloud first, land last — but not land never — by starting with an online community and then materializing it into the physical world. We get there in five steps:

Found the community. First, we need a founder. Anyone can found a network state, just like anyone can found a tech company or a cryptocurrency. The legitimacy of this founder comes from whether people opt to follow them. That is, there's no formal qualification for the role. Unlike the US president, a network state founder need not be part of the tiny fraction of the world born in America, above a certain age, or anything like that. Instead, the qualification for this job is wholly empirical: the founder must build an online community that's motivated enough to create a new state.
Form a network union. Given a sufficiently dedicated online community, the next step is to organize the group as a network union, the predecessor to a network state. Unlike a traditional social network, a network union has a purpose: it coordinates daily actions for the benefit of its members, and is capable of collective bargaining with states and corporations alike.
Build trust online and offline. We now begin holding in-person meetups in the physical world, of increasing scale and duration, while simultaneously building an internal economy using cryptocurrency.
Crowdfund the nodes of the network state. Eventually, once sufficient trust has been built, we start crowdfunding apartments, houses, and even towns (1, 2, 3) to bring digital citizens into the physical world within real co-living communities. These are the nodes of the network state, where we use web3 login and mixed reality to seamlessly link the online and offline.
Digitally connect physical communities. Finally, we network the nodes into a new kind of state: a network state, a digital archipelago with pieces of territory distributed around the world, ranging from single-person apartments to in-person communities of arbitrary size.

The overall concept is to populate the land from the cloud, and to do so all over the earth. The physical footprint of a network state thus looks more like a decentralized diaspora than a traditional centralized country, while in the digital realm the citizens of a network state are far more aligned than the polarized citizens of legacy states. As the population and economy of a network state grow comparable to that of a legacy state, it will gradually be able to attain diplomatic recognition from existing sovereigns — and ultimately the UN — just as Bitcoin has now become a bona-fide national currency.

One thousand words

We begin with premises. Technology, cryptocurrency, China, India, and Asia more generally are on the rise. America and the West writ broadly are in relative decline from an economic, military, demographic, and political standpoint. There are many exceptions to these broad trends — there are positive developments at the state and city level in the US, as well as in pockets of Europe, and the rise of innovation in bits has not yet fully unlocked innovation in atoms — but broadly speaking our future appears to be a centralized East and a decentralized West.

What should that decentralized West ultimately look like?

Not the current age of anarcho-tyranny, best exemplified by the city of San Francisco, wherein the anarchy of unpunished public stabbings is combined with the tyranny of unlimited parking tickets. That model may well be exported to much of the West before it reaches its end-of-life, but fundamentally the state capacity of modern America is just too low to maintain said tyranny for long.

Nor should it be a coming age of crypto-anarchy. In the hypothetical scenario where the establishment mismanages affairs to the point that the dollar collapses and Bitcoin replaces the US dollar as the global reserve currency, the American federal government's writ will hold as much value as its devalued currency — which is to say, none. If this scenario happens, we'll need a vision for shared prosperity and civil order that's better than the (arguably misunderstood) concept of Bitcoin citadels. Because even if it's mostly a joke, there are many societal goods you can't easily buy — like a calm walk down the street in a high-trust community — so Mad Max isn't a desirable long-term outcome for anyone, even Bitcoin Maximalists.

Neither should our future be control by a still-intact Chinese superstate. The CCP model is the limit case of digital centralization, in which the economy and military of the world's largest country folds up into an all-powerful surveillance state. If America falls into a period of prolonged anarchy, the CCP model will prove attractive to many countries as a bastion of stability in a time of uncertainty. Without caricaturing China — it's an enormous country, with significant internal difference of opinion, and many accomplishments to be justifiably proud of — it's important to recognize that we can't expect an unchecked China to behave any better than the US did during its post-1991 period as a hyperpower. Moreover, nature abhors a vacuum, and a durably stateless West would eventually prove a playground for foreign powers, who understand that the non-aggression principle has always been trumped by the aggression principle.

So then: if neither anarcho-tyranny, nor crypto-anarchy, nor Chinese control...then what? Instead, we should start building towards crypto-civilization. A new world where anyone can be either country founder or crypto-citizen, and can switch between these paths at any time — much as you might choose to found a company or join one as an employee. Where it is possible to peacefully start new countries, to join them as citizens, to move between them, to fold them in and spin them out, and to balance decentralized competition with centralized cooperation. Where we can use blockchains to reinvigorate liberal values in an increasingly illiberal time, by advancing free speech, free markets, equality of opportunity, privacy, voting rights, shared prosperity, and provably equal treatment through programmatic rule-of-law. And where we can rely on these liberal values as a base to pursue a higher collective purpose beyond entropic individualism alone, whether that be reaching the stars or reversing aging.

The key enabling technology for this world is the concept of the network state: a country you can start from your computer, an archipelago of digitally-linked enclaves, a union of sovereign collectives, a community aligned around cryptographic consensus, a city-state in the cloud, a body based on math rather than science, a group organized by geodesic over geographic distance, a polity that prizes exit above voice, a state that recruits like a startup, a territory one can acquire but not conquer, a nation built from the internet rather than disrupted by it.

And that is the subject of this book.

Why We’re Auctioning an NFT of Our 2005 YouTube Memo

delabs@newsletter.paragraph.com (Real Block) — Sun, 05 Dec 2021 11:49:14 GMT

By Team Sequoia

Image by Matt Hamel

In early 2021 the value of the combined cryptocurrency market crossed $1 trillion for the first time, a figure that caught the attention of even the staunchest skeptics. In November, that figure crossed $3 trillion — more than the value of any company on earth. Thousands of developers are now building crypto projects, with much of that activity inflecting in the last three years. There are over 7,000 tokens today, a nearly 12X increase from early 2017.

There is a Cambrian explosion underway in crypto. While we’ve invested in crypto for years, the recent acceleration in the space has been astounding. Over a quarter of all new Sequoia partnerships in our U.S./Europe business in the last year have been in crypto-related companies, and as part of our new structure, we’ll be participating more directly in governance and staking tokens. The question is no longer if cryptocurrencies will win mainstream adoption but the full scope of how, over the next generation, blockchain technology will transform economies and our digital lives.

We’ve learned through experience how easy it is to underpredict these transformations. For example, when we first met Chad Hurley, Steve Chen and Jawed Karim as they were just starting YouTube, we imagined what future scaling scenarios might look like at widespread adoption. The best case scenario in our investment memo entertained the possibility of serving 30 million videos per day. That represented 300X growth, which seemed ambitious at the time. But this was two years before the first iPhone and the rise of mobile, which brought a force multiplier in global video consumption. Today, YouTube serves 5 billion videos per day.

At this transitional moment in crypto, we’ve been reflecting on that 2005 YouTube investment memo. We realize how pivotal YouTube was not only in defining the previous generation of the internet’s evolution, but in setting the stage for the creator economy and what comes next. To honor YouTube’s place in that story, and to celebrate the unpredictable upside of foundational technologies like crypto, we’re minting an NFT of the original YouTube investment memo and auctioning it on OpenSea.

The rise of blockchains echoes the rise of the internet itself: the direct, free flow of information between people laid the foundation for the direct, free flow of value on blockchains. This is as much a shift in culture and psychology as it is in technology, and it will enable new economic realities across the world. In the world of NFTs, anyone can create a digital asset — and anyone can invest in one — bringing unprecedented diversity to asset valuation and exchange.

We now see YouTube as a tipping point that paved the way for how we think about the creator economy today. YouTube made the notion of digital asset ownership personal and brought wide distribution of those assets to the mainstream. The YouTube investment memo is a time capsule from the precipice of web2. It seems only right that it be tokenized for posterity. What better time to auction it than at the precipice of web3?

In the next phase of digital evolution, the role of distribution gatekeepers will diminish. Creators will gain the upper hand as control over assets tips toward network participants and away from aggregators. But blockchains will impact far more than currencies and how digital goods are valued and traded. Decentralized protocols and new entities like DAOs may reshape everything from how products are built to how people communicate and create community.

We can’t predict the scope of change or how it will reshape culture. At these early stages, we don’t know what factors will catalyze crypto or in which direction. Those catalysts could be technological, regulatory or cultural. It’s unclear whether transformation will come from a new diversity of currencies in the world, or from the decentralized applications enabled by blockchains — or both.

But what does seem clear is that blockchain technology is beginning to constitute a new protocol for digital interaction at a foundational level. Innovation is accelerating at the application level above layer 1 blockchains, as well as below: one of the most exciting developments we’ve seen is the pursuit of a protocol to make different blockchains fluidly interoperable. This effort has been compared to a TCP/IP for crypto. What this could unlock, we can only imagine. Early web enthusiasts knew it would change everything without being able to foresee trading stocks on an iPhone. The same is true of crypto today.

Whatever the future of web3 holds, visionary founders will be the ones to mold it, just like Chad, Steve and Jawed did before them. Our mission is seeking out the exceptional founders behind the next era-defining innovations.

The best way to prepare your mind for the possibilities of emerging technologies is through insatiable curiosity to learn and understand. So starting next week, we’ll begin hosting a series of live conversations about crypto on Twitter Spaces. We’ll get a global perspective on its potential and challenges — from technology and scaling to regulation and business infrastructure — from the founders and innovators pushing crypto forward. We’ll speak with some of the brightest people in crypto, and we’re happy to learn in public. If you’re a crypto founder — or just curious — we hope you’ll tune in and talk to us.

Until then, happy bidding on the 2005 YouTube memo. Proceeds from the auction will go to 0xPARC’s public goods ecosystem development pool, which will distribute them to maximally benefit the crypto community. We minted the NFT as an ERC-721 token. The auction is taking place on OpenSea and will close on Tuesday, December 7. We’re not retaining a royalty stake — the winner will assume 100% ownership. We’re remaking history, and you can own a piece of it.

Disclaimer*The information contained herein is being provided to you for informational purposes only and should not be relied upon as legal, business, investment or tax advice. Please consult your own advisors as to these matters.This is not an offer to invest in any fund (“Fund”) managed by Sequoia Capital Operations, LLC (together with any affiliates, “Sequoia”). Any offers will be made only by means of a confidential private placement memorandum (“PPM”) which will include important risk factors and considerations that should be carefully evaluated before making an investment in the applicable Fund. Any decision to invest in a Fund must be based solely upon the information set forth in the applicable PPM and the exhibits thereto, each of which should be read carefully by prospective investors prior to investment.The information herein is given in summary form and does not purport to be complete. Please note that any investments referenced herein are illustrative and do not reflect the performance of any Fund as a whole. Past performance is not indicative of future results and there can be no assurance that any Fund will achieve comparable results. All forward-looking statements are based upon assumptions that may not prove to be correct. There is no obligation for Sequoia to update or alter any forward-looking statements, whether as a result of new information, future events, or otherwise.*

The Beginning of the Era of DAO-to-DAO Transactions

delabs@newsletter.paragraph.com (Real Block) — Mon, 29 Nov 2021 14:55:41 GMT

The LAO is closing its first DAO-to-DAO transaction all mediated through Ethereum-based smart contracts.

The LAO

The LAO has received contributions of more than $5 million in ETH. This capital is already being deployed to support a number of projects (14 already), with the investments denominated in ether and settled with Moloch DAO v2 Ethereum contracts. Despite an atmosphere of global uncertainty, Ethereum entrepreneurship has not missed a beat, and The LAO continues to support builders, who keep shipping innovative blockchain-based products around the world.

Importantly, LAO-members are not just providing its capital to traditional projects; it’s also backing other DAOs. As highlighted previously, the OpenLaw team has been developing Ethereum contracts, strategies, and secure interfaces for LAO members to execute liquidity actions in addition to equity investments more trustlessly with code.

Last week The LAO launched an adapted Minion contract (0x549B33CB1A3d851F2039D19264f76DF3612cfbD7) to enable LAO members to deploy capital directly from a DAO-based vote into another DAO.

PieDAO Membership Proposal

The membership vote, if passed, will enable members of The LAO to join PieDAO, a fee-collecting organization coordinating weights of “tokenized asset allocations” (PIEs) that is open to anyone on the Ethereum network through the purchase of its voting shares, $DOUGH.

The LAO’s PieDAO Proposal will enable existing $DOUGH holders to assess whether they should include The LAO as a member and more broadly, present an inter-framework, inter-DAO deal handled entirely by code and member consensus.

👾 + 🥧 = 💒

Decentralized finance (DeFi) applications and communities are being launched and vetted at breakneck speed. Opportunities in the DeFi and blockchain ecosystems likely will not just be limited to traditional forms of investments, but also will increasingly require the agility and flexibility to join DAOs and other emerging blockchain-based organizations.

The LAO, with its digital-native-first approach, is well equipped to keep up with these developments and will continue to push in this direction, as the DAO-to-DAO ecosystem continues to mature and develop. Unlike legacy venture capital and crypto funds, we’re building at the pace of DeFi and DAO ecosystems.

Learn More

If you would like more information about becoming a LAO member or project, please reach out to us at hello@thelao.io. For further information, check out our docs, which cover questions about The LAO’s structure and operation, or hit us up via email or telegram.

The Beginning of the Era of DAO-to-DAO Transactions

delabs@newsletter.paragraph.com (Real Block) — Mon, 29 Nov 2021 14:55:19 GMT

The LAO is closing its first DAO-to-DAO transaction all mediated through Ethereum-based smart contracts.

Last week The LAO launched an adapted Minion contract (0x549B33CB1A3d851F2039D19264f76DF3612cfbD7) to enable LAO members to deploy capital directly from a DAO-based vote into another DAO.

PieDAO Membership Proposal

👾 + 🥧 = 💒

Learn More

Breaking Ownership, the Web3.0 Journey of Creator Economy

delabs@newsletter.paragraph.com (Real Block) — Mon, 15 Nov 2021 01:41:18 GMT

The creators have been sealed for several years, and we let the monopoly hurt them.

Web 3.0 transformation

Web 1.0: Internet

Web 2.0: social media/mobile internet

Web 3.0: Blockchain/AI

We are in the third stage of the Internet. Many Web 3.0 skeptics believe that decentralization will not change anything. I disagree.

Coinbase CEO Brian Armstrong believes that Web 3.0 is nothing new. He said that we are re-decentralizing the Internet, that is, what was the Internet like in the beginning and why?

He said that we need to “test the power of large technology companies,” also because many countries are excluded from the creator’s economic prosperity. Ask creators like Chinedu, my friend in Africa. It is difficult for them to make money through PayPal and Stripe. However, people like me have always taken this for granted. The luck of your birthplace should not affect whether you can join the creator economy and make a living from it.

Creativity is not restricted by the country of origin. Web 2.0 makes us think it is.

“Conversion rate” explains the exploitation of creators

Social media platforms like Twitter, Instagram, and TikTok have a 100% conversion rate-they don’t share any revenue with creators at all! This is good for them, but bad for users. — Chris Dixon

Here I will go further to trouble Dixon. Before CEO Jack Dorsey saw the power of Web 3.0, Twitter had never shared revenue with its creator, and now he has set sail again. He publicly announced that he will decentralize Twitter and turn it into a Web 3.0 product. In addition, Twitter has just launched a “super follow” feature that allows creators to make money from content.

In addition, there is a new revue newsletter feature that allows creators to charge for paid newsletters. This is not all. The best features have been introduced recently. Twitter has now opened up cryptocurrency services. You can use Bitcoin to transfer money on Twitter. For example, if you ever tried to send money from the United States to El Salvador, this is the new rule of the game. Twitter proved that the migration to Web 3.0 will happen 100%, albeit slowly.

However, Facebook, Instagram, and TikTok have not yet understood this shift. They allow content creators to work as slaves. The creator builds a follower and gets a view controlled by an algorithm that can decide whether to like your hoodie color tomorrow. They use this content to attract consumers and show them advertisements. The $0 in advertising revenue will be shared with creators. Please read it again.

When content platforms first appeared, we were just happy to use them without spending a penny. Now we are used to it. Our standards have changed. Creators hope to share the platform’s benefits from our content fairly. This is reasonable. However, unless Zuckerberg is forced to sell ads and share the revenue instead of buying another house, change will not happen.

If creators no longer provide content for free, then platforms like TikTok will go bankrupt. Please imagine.

Platform ownership is broken

How is Web 3.0 different? ownership. Creators want to own the platforms they create and have voting rights. When platforms make money, they also make money.

A content review policy is formed through voting rights. It is completed through a process of blockchain consensus and the forced trust of thousands of computers around the world (even an orange president cannot influence blockchain elections).

In addition, there are functions of the platform itself. Have you ever opened your favorite app on a beautiful Saturday afternoon and found that everything has changed, and it looks like it was designed by a freshman UI/UX kid? Do you feel that you don’t see the design giving your face A punch from the top? It’s not the child’s fault. They are too far away from the work of the creator. They are outsiders.

Web 3.0 is different. The function is determined by the user through a democratic process. If a group of users doesn’t like it, they will create a fork. Forking refers to running two versions of the same platform with different characteristics.

When ownership is fixed and transparent, the motivation will change. Ownership leads to user democracy, not a dictatorial philosophy similar to web 2.0 “This is the latest update, you dirty animal.”

Smart contracts contributed to this revolution

At the beginning of the 21st century: make a website.

The 2010s: developing applications.

The 1920s: Deploy smart contracts.

Many people misunderstand the role of Ethereum in the new creator economy. Ethereum allows machines instead of humans to execute smart contracts.

Entrepreneur Mike Novogratz explained: “Blockchain will allow information that should not be free, not free.” Remember Napster? You can download music for free, and no one can stop you, even metal The fool of the band.

The Web 2.0 version of the Internet we are using is not built for content ownership. If you want, you can take any video from Youtube. This is hard to detect. Damn it, this article can easily be stolen by copy and paste.

Smart contracts change this. The smart contract tells everyone who is the owner of this content. The creativity of NFT is to turn your content into portable digital assets so that you can publish it anywhere on the Internet.

According to expert Eric Jorgenson (Eric Jorgenson), the current era of web 3.0 is only due to differences in these three areas:

Web1 = free publishing

Web2 = Free communication

Web3=Free transaction

More ways to make money

Now that Web 3.0 solves the content ownership problem and makes our digital assets portable, we as creators can find more ways to make money.

Mike Novogratz stated that we will “see the transition from businessman to creativity.” Creators will have a way to monetize their creativity. Not only artistic creativity but all kinds of creativity.

He even said that we will wear NFTs on T-shirts, and other people can only see them if we wear AR/VR glasses.

You can share money with multiple parties. You can transfer your content from one platform to another according to which platform is better. Creators from all over the world will be able to collaborate and come up with crazy ways to make money from our work.

When Zach gets rich, he no longer has to make $0 on Facebook. According to the performance of the content, money can flow into your pocket in seconds.

Creators will accelerate the development of Web 3.0 because we just want to be paid so that we can engage in creation full-time. Once content capturers release us, more ways to make money will drown our creative brains. I can not wait anymore.

Web 3.0 changed every major industry

ETH: Decentralized Silicon Valley

DeFi: Decentralized Wall Street

NFTs: Decentralized Hollywood

This shift is not unique to the creator economy. All industries will slowly change to reflect a human obsession with democracy. Web 3.0 first aimed at finance and became an industry with more than 2 trillion US dollars. This shift has shifted to the creator economy. For example, platforms such as Bitclout invented coins, allowing creators to become their users so that they can invest in stocks.

The next wave of decentralization will be Youtube, Spotify, and Facebook. Now is the best time to become part of the creator’s economy. Observe the transformation that takes place in front of your eyes and port any content type you like to Web 3.0. This is how you as a creator can take advantage of this great opportunity.

Join Coinmonks Telegram Channel and Youtube Channel learn about crypto trading and investing

Also, Read

Composability is Innovation - Future

delabs@newsletter.paragraph.com (Real Block) — Tue, 09 Nov 2021 14:28:13 GMT

https://future.a16z.com/how-composability-unlocks-crypto-and-everything-else/

While many in tech and beyond have heard of bitcoin, cryptocurrency, and the concept of a blockchain, less well-known are smart contracts, the major innovation of Ethereum. They’re programs that anyone can write and deploy to a public blockchain, enabling all kinds of innovation. Buzzy acronyms like NFTs, DeFi, DAOs — representing new ways to own anything, better financial systems for all, and new ways for people to coordinate and collaborate, respectively — are all powered by smart contracts.

Smart contracts power new kinds of transactions with clear advantages over those enabled by legacy systems. Traditionally it takes weeks and reams of paperwork for a bank to verify an individual’s assets and issue a loan, for example. With a smart contract, a piece of code could automatically issue a loan based on the collateral provided by the individual.

Smart contracts go beyond simply allowing for instant and verifiable transactions for various applications though — they can also be programmed to interact with each other. In other words, they make crypto programs composable, like building blocks. This capability of composability is one of the most talked-about among tech enthusiasts, and not talked about enough more broadly, yet it’s one of the most powerful aspects of crypto. Because composability allows anyone in a network to take existing programs and adapt or build on top of them, it unlocks completely new use cases that don’t exist in our world.

In other words: composability is innovation.

Why composability is possible and what it makes possible

The ability for anyone in a vast network of disconnected, distributed participants to leverage the work of others to create new applications didn’t just arise spontaneously — it required the cooperation of many people. Ethereum smart contract developers enabled composability over time by converging on community standards that describe how certain types of contracts should behave. For example, the ERC-20 token standard, first proposed by developer Fabian Vogelsteller in November 2015 and formalized in September 2017, describes how Ethereum tokens should behave, including basic functionality like the transfer of tokens and approval for spending tokens. It allows third-party developers to easily support any token that complies with the ERC-20 standard.

This type of standardization is crucial to composability, just as standardizing internet and email and other protocols were crucial to the growth of the web. With these token standards in place, smart contracts can act as building blocks that are able to be assembled into larger systems. Just like a software library, smart contracts for different protocols and applications can easily plug into each other like Lego pieces. In fact, smart contracts within decentralized finance (DeFi) — which represents one of the earliest and most vibrant examples of composability — are often referred to as “money legos”.

How composability works in decentralized finance

Financial positions in DeFi protocols — which enable users to loan, borrow, trade, or otherwise transact without requiring centralized financial institutions in the middle — can be represented as ERC-20 tokens that can be redeemed for the underlying funds. For example, if you deposit USDC (tokenized U.S. dollar) to the lending protocol Compound, you receive cUSDC, which represents your position that’s earning interest within Compound. Similarly, when you deposit funds into the decentralized exchange protocol Uniswap to provide liquidity to a specific market, you receive ERC-20 tokens that represent your share of the funds pooled within the associated Uniswap market.

Crucially, these tokens are not “locked” into one protocol — they can now be used within other DeFi protocols. You can use your Uniswap Liquidity Provider tokens as collateral in the lending protocol Aave, for example. Smart contracts enable developers to build upon other protocols to easily interact across multiple applications; in the world of decentralized finance, this includes everything from lending to derivatives.

While some of these kinds of DeFi transactions have not been easily accessible for many — either due to the complexity around certain applications or technical savvy needed to interact with protocols — the usability is continuing to significantly improve. The chain of transactions involved in composing different DeFi building blocks may be constructed and visualized using projects like Furucombo and DeFi Saver, which abstract away the developer work needed to combine and interact with different smart contracts. One can simply drag and drop different actions into sequence or use combinations crafted by other people.

Furucombo makes it easy for users to create their own DeFi combos.

Composability leads inevitably toward more choice, and better user experiences, because there are no obstacles to someone taking an existing idea and making it easier to use, or adapting it to new use cases. As more and more of the underlying technology gets abstracted away, the focus will shift towards what people can do with their money, and not the inefficiency that marks much of the traditional finance world.

So what does composability really mean for builders and developers?

There are many possibilities, most of which will only be unlocked by people trying things out, but some examples of what it makes possible for builders include:

Developers can bootstrap their own projects and communities without having to build everything from scratch, because smart contract platforms like Ethereum are massive, open sandboxes to build systems that can reach a built-in global audience. This is a large driver of the rapid pace of innovation seen within the crypto space, allowing small teams to quickly bootstrap their own projects. For example, a new video game creator could easily add the ability for users to trade in-game items by integrating a decentralized exchange protocol rather than having to build a new marketplace from scratch.

Non-crypto businesses can increase efficiency and have more functionality by plugging into open ecosystems like Ethereum — much like the API economy enabled companies of all kinds, including mom-and-pop shops and small businesses, to access data and competencies they wouldn’t otherwise have been able to. An example in the tech space, however, is Reddit’s experimentation with Community Points, which are tokens that reward users for posting high-quality content and can be redeemed for unique items within the community. Reddit plans to launch Community Points as ERC-20 tokens, which would let them be used in existing wallets and applications on Ethereum. This now opens up many more functionalities for Community Points that Reddit doesn’t have to build itself. Even if it’s not a crypto company, it can get the benefits of crypto applications for its users, such as Redditors being able to use decentralized exchanges on Ethereum to trade their points for other tokens. This would allow them to have liquidity for their points from the start. Also, once plugged into the Ethereum ecosystem, anyone can incorporate Community Points into their own project to build on it and create further use cases.

Developers can learn and apply concepts from a broad variety of industries, including tech, finance, gaming, and art, leading to a deeper understanding of each, new ways of thinking, and new applications for people. For example, by adding DeFi components to gaming, we might be able to better understand incentives and marketplaces; and by adding gaming components to DeFi, we might be able to make finance more accessible and interesting to a broader audience than finance insiders. Communities that don’t normally get to interact with each other — because they spend their time on different platforms or can’t interoperate — can also communicate and share ideas this way, leading to even more innovation. Smart contracts enable this sharing of information to be more open, efficient, and trusted exchanges even among strangers.

There are many interesting examples of composability use cases in crypto today besides the DeFi example I shared already; some of these include:

Earning yield through “no-loss” lotteries

PoolTogether is a project that utilizes decentralized finance protocols to create “no-loss” lotteries. Users can purchase tickets, and all funds collected from ticket sales go into a prize pool that earns yield from decentralized finance protocols Compound and yEarn Vaults. Everyone gets their funds back, but one person wins all of the accumulated interest that was earned on the pooled money. No one loses the money that they initially put in, hence it’s a “no-loss” lottery. Anyone in the world with an Ethereum address is able to participate in the no-loss lottery, and anyone can create a no-loss lottery for any token, which makes participating in these types of systems more accessible and safer.

NFTs as collateral

Non-fungible tokens (NFTs) have received much attention recently. Unlike the interchangeable, “fungible” tokens in the ERC-20 token standard, an NFT is a unique digital asset whose ownership is tracked on a blockchain. But even though the tokens themselves are not interchangeable, they *do *still exist in a composable ecosystem. This means that when they are issued on a smart contract platform, anyone can own or trade an NFT for any other asset that exists on the same platform.

When “composed” (plugged into, combined) with decentralized finance building blocks, NFT activity can go well past trading and can include actions like being able to use the NFT as collateral in taking out a loan (e.g. NFTfi) or being able to rent out or earn interest on the NFT (e.g. RenFT, Charged Particles).

Say you own a piece of valuable real estate in a virtual world like Decentraland or Cryptovoxels. You could actually borrow USDC against that asset to finance a down payment for a house in real life. Or, say you own a desirable skin within a video game — you could rent that item out to other players to use temporarily, much like you might rent a room in an Airbnb.

NFTFi allows users to offer loans for NFTs representing everything from wallet names to virtual land.

Publishing

Another example of plugging two applications together thanks to the property of composability is the collaboration between the projects Mirror, a decentralized publishing platform, and Zora, a protocol for creating and exchanging NFTs. These projects have connected to allow Mirror writers to convert any of their posts into an NFT, and embed an auction for an NFT into their post. This in turn allows creators to crowdfund pieces of work like novels and blog posts or even research papers or other such artifacts, where purchasing the NFT helps fund the creator.

Sometimes the NFT provides the *contributors *the ability to earn a part of the proceeds once the NFT is re-sold. Imagine if early Kickstarter backers of Oculus, for instance, could have benefited too when Oculus was sold to Facebook, for their early belief and support. Recently $ESSAY by John Palmer was the first community-owned essay crowdfunded on Ethereum. The essay, published via Mirror, was minted as an NFT on Zora and backers are embedded in the essay forever. People contributed to the crowdfunding to support the writer as well as collect a piece of history — the first community-owned essay. But in other cases, early contributors (alongside the creator) could also share a piece of that secondary value.

Source

Flash loans

Flash loans are one of the most unique capabilities enabled by crypto — there’s nothing close to the equivalent of flash loans in the traditional system. Flash loans allow someone to borrow funds and repay the loan in the same transaction; if it’s not repaid in the same transaction, then the transaction will fail.

This allows for loans to be uncollateralized, which means that these flash loans are accessible to anyone in the world regardless of how much capital they have. Flash loans are very deep into the weeds for crypto, but happen regularly in the DeFi space to take advantage of arbitrage opportunities.

***

As crypto matures, we should expect these composable smart contract building blocks to start getting used outside of the crypto community. Eventually, developers will be able to add just one line of code to add a full decentralized marketplace to a video game, or another line of code to allow merchants in their ecommerce store to earn interest on their balance. For institutions, composability puts crypto at the forefront of revolutions in finance and other industries — changing industries fundamentally, much like the internet did. And for consumers, it will open up a whole new world of possibilities.

I’ve only scratched the surface of what might be possible in the future here. The next step is more experimentation. I’ve talked about the technology, but it’s human ingenuity that comes next.

Thanks to Will Warren for reviewing this post.

Disclosures: Linda Xie is a Managing Director of Scalar Capital Management, LLC, an investment manager focused on cryptoassets that holds ETH and Ethereum tokens. This post is not investment advice.

Linda Xie is the co-founder of Scalar Capital, a crypto investment firm. She was previously a product manager at Coinbase and a portfolio risk analyst at AIG.

Posted June 15, 2021

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Chris Dixon and Naval Ravikant — The Wonders of Web3, How to Pick the Right Hill to Climb, Finding the Right Amount of Crypto Regulation, Friends with Benefits, and the Untapped Potential of NFTs (#542)

delabs@newsletter.paragraph.com (Real Block) — Sat, 06 Nov 2021 02:46:25 GMT

Illustration via 99designs

**“What the smartest people do on the weekends is what everyone else will do during the week in ten years.”**— Chris Dixon

“Denying and pushing back against NFTs and crypto is basically saying: ‘We’re not going to have a collectively owned future. We’re going to have a corporate-owned future, and we’re going to have a government-owned future.'”— Naval Ravikant

Chris Dixon (@cdixon) is a general partner at Andreessen Horowitz, where for the past six years he has been an active seed and venture-stage investor.

Previously, Chris co-founded and served as the CEO of two startups, SiteAdvisor and Hunch. SiteAdvisor was an internet security company that warned web users of security threats. The company was acquired by McAfee in 2006. Hunch was a recommendation technology company that was acquired by eBay in 2011.

Chris has been a prolific seed investor, co-founding Founder Collective, a seed venture fund, and making a number of personal angel investments in various technology companies. Chris started programming as a kid and was a professional programmer after college at the high-speed options trading firm Arbitrade. He has a BA and MA in philosophy from Columbia and an MBA from Harvard.

He has written about his theories and experiences as an entrepreneur and investor on Medium and before that at cdixon.org. His a16z Podcast appearances can be found here.

Naval Ravikant (@naval) is the co-founder and chairman of AngelList. He is an angel investor and has invested in more than 100 companies, including many mega-successes, such as Twitter, Uber, Notion, Opendoor, Postmates, and Wish. You can subscribe to Naval, his podcast on wealth and happiness, on Apple Podcasts, Spotify, Overcast, or wherever you get your podcasts. You can also find his blog at nav.al.

For more Naval-plus-Tim, check out my wildly popular interview with him from 2015—which was nominated for “Podcast of the Year”—at tim.blog/naval. We also had a second long-form conversation in 2020, and you can find that here. His most recent appearance was helping me interview Ethereum creator Vitalik Buterin.

Please enjoy!

Listen to the episode on Apple Podcasts, Spotify, Overcast, Podcast Addict, Pocket Casts, Stitcher, Castbox, Google Podcasts, Amazon Music, or on your favorite podcast platform.

****Brought to you by UCAN endurance products powered by SuperStarch®, Theragun percussive muscle therapy devices, and Tonal smart home gym. More on all three below.

The transcript of this episode can be found here. Transcripts of all episodes can be found here.

#542: Chris Dixon and Naval Ravikant — The Wonders of Web3, How to Pick the Right Hill to Climb, Finding the Right Amount of Crypto Regulation, Friends with Benefits, and the Untapped Potential of NFTs

**This episode is brought to you by UCAN. **I was introduced to UCAN and its unique carbohydrate SuperStarch® by my good friend—and listener favorite—Dr. Peter Attia, who said there is no carb in the world like it. I have since included it in my routine, using UCAN’s powders to power my workouts, and the bars make great snacks. Extensive scientific research and clinical trials have shown that SuperStarch provides a sustained release of energy to the body without spiking blood sugar. UCAN is the ideal way to source energy from a carbohydrate without the negatives associated with fast carbs, especially sugar. You avoid fatigue, hunger cravings, and loss of focus.

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Go to Therabody.com/Tim right now and get your Gen 4 Theragun today, starting at only $199.

What was your favorite quote or lesson from this episode? Please let me know in the comments.

SCROLL BELOW FOR LINKS AND SHOW NOTES…

Want to hear my most recent interview with Naval? Lend an ear to our conversation in which we discussed why there’s no such thing as science with a capital S, the problems that arise when jargon masquerades as knowledge, how to get rich without getting lucky, get-rich-quick schemes for losers, anxiety control, cryptocurrency (of course), and more.

#473: Naval Ravikant on Happiness, Reducing Anxiety, Crypto Stablecoins, and Crypto Strategy

SELECTED LINKS FROM THE EPISODE

Connect with Chris Dixon:

Website | Twitter | Medium | a16z

Connect with Naval Ravikant:

Website | Twitter | AngelList | Naval Podcast

SHOW NOTES

Chris explains his interest in philosophy and the advice given to him by philosopher and cognitive scientist Daniel Dennett. [07:44]
How long is Satoshi Nakamoto’s white paper? [11:05]
What the smartest people do on the weekend is what everyone else will do during the week in 10 years. How this has been true of the development of the personal computer, and how will this play out with blockchain technologies and cryptocurrency? [12:20]
The problems proof-of-work system Hashcash was created to solve, and how it was adopted by we know today as Bitcoin. [17:02]
What is the Byzantine Generals Problem, and how does it relate to decentralization? [19:36]
What are Web1, Web2, and Web3? [20:20]
Digital scarcity, open source, composability, and the real promise of Web3. [27:01]
What gives digital assets like altcoins and NFTs value? [41:53]
How Web3 rewards creative people in ways Web2 has only robbed them. [50:07]
How video games are adapting to the Web3 world. [55:45]
Naval expands on the idea of NFTs being more than the sum of their JPGs. [1:01:12]
The data science of Sorare. [1:04:28]
Don’t have a house to offer as collateral on that loan? Maybe the bank will accept your CryptoPunk. [1:06:16]
What Gall’s Law tells us about who will win in the battle between decentralized gaming and centralized gaming. [1:07:35]
How skeuomorphic design has been used in the past, and how it will fit into a Web3 world. [1:08:47]
A couple of recommendations to prepare you for Web3. [1:15:42]
Weaknesses of — and challenges presented by — Web3. [1:16:31]
What is hill climbing in computer science, and how can you be sure you’re not climbing the wrong one? [1:22:38]
You’re not late to the party (yet): decentralization is still in its early days. [1:26:41]
The sticky wicket of regulating decentralization with archaic laws designed to govern the world where our grandparents and great-grandparents grew up. [1:28:33]
How mainstream adoption of cryptocurrencies is held back by the same political divides that are holding back society. [1:32:40]
How do novices — especially policymakers — even begin to wrap their minds around what’s going on in the world of crypto and separate signal from noise? [1:34:24]
Thoughts on decentralizing the American Dream to preserve the US as a bastion of innovation. [1:35:48]
Policymakers who seem to have the right idea about how to coexist with crypto, and what Chris and Naval think sensible regulation should look like. [1:41:24]
Streamlining philanthropy, fundraising, and production by blockchain. [1:47:08]
Where does Chris rate on the hierarchy of vices with his gum-chewing habit? [1:53:56]
Most gifted books. [1:55:04]
“Wen Tim Ferriss NFT drop?” [1:59:10]
How DAOs can serve communities, organizations, and governments in the real world. [2:00:09]
A disclaimer: do not take anything you hear on this episode as financial advice! Support the projects that genuinely appeal to you rather than trying to predict the future and cash out with a fistful of crypto. [2:03:54]
The lens through which Chris views NFTs. [2:07:57]
Further thoughts on motivations for participating in NFT markets. [2:09:07]
How the NFT market has finally made generative art profitable for the artists who create it, and why now may be the greatest time in history for creative people. [2:12:31]
Are we in “the kitchen recipe period” of NFTs? [2:16:04]
Still don’t get NFTs? Consider, instead, the humble sneaker. [2:19:21]
Vetting customers and ticketing with NFTs. [2:20:59]
Friends with Benefits and other spiffy DAOs. [2:22:11]
Parting thoughts. [2:25:03]

MORE CHRIS DIXON AND NAVAL RAVIKANT QUOTES FROM THE EPISODE

“We were told the internet is bad for creative people. The internet is not bad for creative people. Web2 is bad for creative people.”— Chris Dixon

“Denying and pushing back against NFTs and crypto is basically saying, “We’re not going to have a collectively owned future. We’re going to have a corporate-owned future, and we’re going to have a government-owned future.'”— Naval Ravikant

“As with all sorts of tech things and money involved, there are bad people. It’s just inevitable. It happened in the ’90s; it happened in the 2000s. It happens now. And those people give Web3 a very bad name. We want to get rid of those people.”— Chris Dixon

“Where we started was we actually decentralized the hardest thing. The hardest thing to decentralize is money. And once you have money decentralized, then you can own private property.”— Naval Ravikant

“The killer app of the internet is networks. We’ve got a million networks built on this thing now.”— Chris Dixon

“Any regulator that stops the next generation of artists and musicians and gamers and game developers from owning their platforms and their work is going to go into the wastebasket of history as a villain. It’s that simple.”— Naval Ravikant

“Step one will be you take the existing artists and they get more money. Step two is you’re going to incentivize a whole new generation to go do these cool things.”— Chris Dixon

“This should be the greatest time in history for creative people.”— Chris Dixon

“I really believe very strongly that one of the most important things you can do is just go speak to a lot of people. That’s where I get all of my information is talking to entrepreneurs, talking to people that are smarter than me.”— Chris Dixon

“I think Web3 is not only better for the world, but it’s also going to beat Web2. It’s going to be more popular because the people get really excited when they actually get to participate.”— Chris Dixon

PEOPLE MENTIONED

*The Tim Ferriss Show *is one of the most popular podcasts in the world with more than 700 million downloads. It has been selected for "Best of Apple Podcasts" three times, it is often the #1 interview podcast across all of Apple Podcasts, and it's been ranked #1 out of 400,000+ podcasts on many occasions. To listen to any of the past episodes for free, check out this page.

The metaverse: reconstructing society from first principles

delabs@newsletter.paragraph.com (Real Block) — Wed, 03 Nov 2021 03:12:24 GMT

Polynya

Homo sapiens are a fascinating species. Our bodies do have some advantages: opposable thumbs, decent endurance, bipedalism — but are quite mediocre overall in the grand scheme of evolutionary physiology. Where all our skill points have been allocated is in two key areas: communication and imagination.

Natural selection is an autonomous process, and our existence is completely meaningless. Yet, through our imagination, we have conjured fictional structures like religion, nations, economies, money etc. to give it all some meaning. Though our communication abilities, we have collectively given legitimacy and continued to memetically evolve all of these structures. But really, these are purely artificial constructs backed by some material creations.

The meatspace is already a multiplayer video game — you earn arbitrary points to accomplish certain tasks, with different methods to create the rules of the subgames. However, there’s one severely crippling limitation to meatspace, bound by physics: Our imaginations have far, far wider potential than what can be built physically, or experienced by our fragile bodies. There are also many arbitrary boundaries set that cripple our creativity. Further, the more we want to build meatspace things, the more toxic waste and damage we’ll leave. It’s affecting other species first, but eventually, biosphere collapse will catch up with homo sapiens and lead to our extinction. Now, of course, one would argue that the solution to this is colonizing the galaxy…

But a much easier and more feasible alternative is at hand: building the metaverse. Unconstrained by the many limitations of meatspace, we can collaborate on creating fairer societies from first principles — an opportunity our ancestors 10,000 years ago did not have.

Ultimately, the goal is to derive “happiness” out of our meaningless existence by leveraging our imagination and communication superpowers: the metaverse can accomplish this goal in a better, more benevolent, creative, and sustainable manner.

So how can all of this be accomplished? It’s early days, I don’t know. It’s very likely that a lot of the follies of meatspace will be translated over to metaverse in the early days, but hopefully the tools to break this cycle will be much more accessible. What do you think?

link:

https://polynya.medium.com/the-metaverse-is-real-reconstructing-society-from-first-principles-2f28ca15ba1

Real Block

The different types of ZK-EVMs

Overview (in chart form)

Type 1 (fully Ethereum-equivalent)

Advantage: perfect compatibility

Disadvantage: prover time

Who's building it?

Type 2 (fully EVM-equivalent)

Advantage: perfect equivalence at the VM level

Disadvantage: improved but still slow prover time

Who's building it?

Type 2.5 (EVM-equivalent, except for gas costs)

Type 3 (almost EVM-equivalent)

Advantage: easier to build, and faster prover times

Disadvantage: more incompatibility

Who's building it?

Type 4 (high-level-language equivalent)

Advantage: very fast prover times

Disadvantage: more incompatibility

Who's building it?

The future of ZK-EVM types

Blockchain, supply chain collaboration and the era of digital ec…

Blockchain, supply chain collaboration and the era of digital ec…

Web3成为主流的3个阻碍——Mirror CTO

#stETH脱锚与 #以太坊PoS中心化

1. 关于stETH与ETH的单向兑换：脱锚本该是常态

2. 但是，stETH/ETH的兑换为什么能长时间维持在1:1？

3. 然而，以太坊正在研究对PoS中心化的打击，会影响stETH的价格

4. stETH对ETH价格的影响：引发DeFi清算

5. 另外，stETH的流动性跟以太坊还是不能比的。

【NFT】-热狗MC HotDog

Decentralized Society: Finding Web3’s Soul1

A Beginner's Guide to Optimism

🎥 NEW EPISODE: ALL ABOUT THE OPTIMISM AIRDROP

Tactic Tuesday

Optimistic about crypto’s future? Then Optimism’s for you

How Optimism Works

A brief history of Optimism

How to get started with Optimism

Creating an Optimism wallet

Getting money onto Optimism

Optimism starter pack

TOOLS 🔨

READ 📚

WATCH 📺

METAVERSAL 🎨

Top Optimism apps

1. Synthetix

**2. Uniswap **

3. Perpetual Protocol

Bonus projects

Conclusion

Action steps

Do 'Trust Models' Deserve Their Title?

Blockchain applications are never fully trustless, but some applications are much closer to being trustless than others. If we want to make practical moves toward trust minimization, we want to have the ability to compare different degrees of trust.

Enter the Blockchain Writing Contest

Blockchain applications are never fully trustless, but some applications are much closer to being trustless than others. If we want to make practical moves toward trust minimization, we want to have the ability to compare different degrees of trust.

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