In 2020, Patrick Lewis introduced the term Retrieval Augmented Generation (RAG) in a groundbreaking paper, positioning it as a key method for improving the accuracy and reliability of generative AI models. The method has gained widespread acceptance, and more recently, he has apologized for the unappealing acronym.

As AI Agents continue to evolve and integrate multiple generative models, understanding concepts like RAG is crucial for AI enthusiasts and our community. This knowledge will serve as the foundation for creating dynamic AI Agents and Agent Collectives on the Theoriq protocol.

What is RAG?

RAG, or Retrieval Augmented Generation, is a technique that enhances AI’s ability to provide accurate, up-to-date responses. Imagine if every time you asked AI a question, it could quickly access the latest information from the Internet or a large database. That’s what RAG does. It helps Large Language Models (LLMs) to use up-to-date facts instead of solely relying on their pre-training data.

What is Pre-Training Data?

Before we dive deeper into RAG, it’s important to understand pre-training data and how LLMs work. LLMs are trained on vast amounts of text data to perform basic language tasks and follow instructions, building an understanding of language and general knowledge up to a certain point in time. This pre-training allows LLMs to generate human-like text.

However, pre-trained, out of the box LLMs have limitations:

• Static Information: Their information is frozen, only knowing data at the time of the LLMs training.

• Biased and Inaccurate: The model may reproduce biases or errors present in their training, which doesn’t reflect real world use cases or historical facts.

• No Real-Time Information: They can’t access current events or newly published data.

This is why current AI chatbots, like ChatGPT, are not search engines. While they can generate creative responses, under the hood they essentially predict the next word and may struggle with real-time facts and real-world scenarios.

How RAG Enhances AI Agents

Imagine asking an AI Agent, "What should I wear today?" Without RAG, it might give a generic answer like, “how about something comfortable, like jeans and a t-shirt?”. But with RAG, the same AI interaction can be programmed to have the persona of a ‘Stylist’ that can check the latest weather report, consider the occasion you’re dressing for, and analyze the latest styling trends – it would then suggest something that is tailored to your needs.

Once we add programming to our interactions with AI, like adding a Stylist persona, we call these tools ‘Agents’. At Theoriq, we define AI Agents as follows:

“AI agents are autonomous software systems that leverage modern generative AI models to plan, access data, use tools, make decisions, and interact with the real world to perform specific functions.” Theoriq Team. (2024). Theoriq: The AI Agent Base Layer.

The typical workflow for RAG involves chunking documents into smaller pieces, computing embeddings for each chunk, and storing them in a vector database. When a question is asked,  the system retrieves the most relevant chunks using a similarity metric, which helps the LLM generate a more accurate and contextually relevant response (that's where Retrieval Augmented Generation comes from - you retrieve relevant info and generate a response with the augmented context). This process might also include intermediate steps like re-ranking or filtering the retrieved information.

New Words Alert 🚨

• Chunking: Breaking down large documents into smaller, manageable pieces of text.

• Embeddings: Numerical representation of text that captures semantic meaning.

• Vector Database: A specialized database optimized for storing and retrieving embeddings.

A RAG Workflow Involves Several Key Steps:

• Large documents are split into smaller, manageable text chunks.

• Each chunk is converted into an embedding–a numerical representation that captures its meaning, allowing for quick comparisons between texts.

• These embeddings are stored in a special database that's optimized for finding similar information.

• When a question is asked, the system compares it to stored embeddings and retrieves the most relevant chunks.

• The AI Agent uses the retrieved information along with the question to generate an informed response.

A key aspect of building robust RAG applications is setting up the right data sources. These sources can range from Internet searches, documents from private databases, or publicly available domain-specific data. It's essential to review the retrieved content to ensure relevance–after all, "garbage in, garbage out"!

Why Use RAG?

• Better Answers, Fewer Mistakes: RAG helps AI Agents provide more accurate, grounded, and up-to-date responses, reducing hallucinations by ensuring the information provided is relevant to the question.

• Leveraging Private or Domain Specific Data: For example, a Web3 News Agent without access to fresh data could provide inaccurate answers. RAG pulls the latest information to avoid this.

• Cost and Time Efficiency: Feeding all possible context as an LLM input is either impossible or costly (for example, filling up Gemini 1.5 Pro context window of 1 million tokens will cost you at least $7 per request!). RAG retrieves only the most relevant information, improving both accuracy and performance, as well as reducing costs and latency.

• Enhanced User Experience: Users get richer, more precise answers that directly address their queries and intent.

Like Humans, AI Agents Need Context

RAG is about offering the most relevant context to help AI Agents answer questions accurately. RAG is also a way to record Agent interactions and experiences into context for future conversations. By saving and organizing these experiences into a "personal diary," which the Agent continually updates, RAG provides the most relevant experiences for the current situation, enabling long-term memory. This way, the Agent can learn from past mistakes and avoid repeating them.

At Theoriq, we’re advancing AI Agents by investigating the use of RAG into our decentralized Agent Collectives, where multiple agents collaborate on complex tasks. RAG could enable these agents to access shared experiences, making collective decision-making more efficient and intelligent. By pooling knowledge and context across multiple agents, Theoriq's ecosystem not only improves individual agent performance but also promotes a dynamic collaboration between agents. This approach accelerates the development of powerful, decentralized AI solutions that leverage the collective power of multiple agents, driving progress in both AI and Web3 applications.

RAG (Retrieval Augmented Generation) significantly enhances AI agents by providing up-to-date, accurate, and contextually relevant information. By breaking down documents into smaller chunks, creating embeddings, and utilizing vector databases, RAG enables AI to generate well-informed and precise responses. This technique not only reduces errors, but also lowers costs, and improves the user experience by leveraging specific and current data sources. RAG is the open-book test that AI always aces.

The team at Theoriq is constantly exploring the latest advancements in AI and Web3, striving to integrate them into the protocol. Through this approach, we are building an innovative, open, decentralized ecosystem where the benefits are shared equally by all.

About Theoriq

Theoriq is the first decentralized protocol for governing and building multi-agent systems by integrating AI with blockchain technology. The platform is centered around an agnostic modular base layer that powers an ecosystem of dynamic AI Agent collectives that are interoperable, composable and decentralized.

Theoriq has raised over $10.4M from leading investors such as Hack VC, Foresight Ventures, Inception Capital, HTX Ventures and more, and have active partnerships with leading web3 and web2 projects including Google Cloud and NVIDIA.

With Theoriq, you're not just part of a network; you're part of a movement that's empowering communities, developers, researchers, and AI enthusiasts to reshape the future of intelligent autonomous systems.

Website | X | Discord | LinkedIn

Navigating Web3 can be complex, often requiring multiple wallets and dApps for simple tasks. AI can simplify this by automating operations and enhancing the user experience. However, web2 AI agents face limitations—they are not smart contract-centric, preventing them from executing on blockchain operations securely.

Phala’s cutting-edge Trusted Execution Environment (TEE) compute capabilities addresses this gap, offering a secure environment for building confidential and verifiable AI agents integrated with on-chain smart contracts. Phala Network is transforming decentralized AI agents by revolutionizing AI Agents’ control and governance, ensuring operation within a decentralized hybrid cloud leveraging TEE and blockchain. This architecture eliminates central authority control, leading to more resilient, transparent AI aligned with user interests. It integrates tokenomics, governance, and incentivization within the ecosystem using cryptocurrencies.

Theoriq’s decentralized protocol has been developed to support the combination of specialized high-performance AI Agents into optimized Agent Collectives that are dynamic, interoperable, and secure. This approach complements the problem Phala is solving in Web3, and by partnering with industry leaders, we are ensuring that the decentralized development of AI advances both teams' missions of making AI and Web3 smarter, more equitable, and more efficient for its users.

Private, Efficient and Secure AI Agents Come to Life in Web3

Theoriq will require heightened data privacy capabilities as it rolls into its testnet, mainent, and node events towards the end of this year. By leveraging Phala’s TEE network, we can enhance the protocol's security and trust, implementing industry-leading protection and reliability for our AI and ML operations.

A TEE (Trusted Execution Environment) is a secure enclave within a device's main processor, designed to isolate and protect data from external processes, even those with elevated privileges. This isolation creates a trust-minimized environment, significantly boosting security against potential threats. This feature could eventually be integrated into Theoriq’s no-code builders, expanding an extra layer of security to many use cases in the industry.

Additionally, the partnership will involve collaboration between each company's research and development teams to explore joint projects focused on enabling AI Agents to function seamlessly in Web3 environments.

The collaboration between Theoriq and Phala is built on a strong foundation of complementary technologies and shared visions. By partnering with leaders in the AI and Web3 segment, each team will enhance their ecosystems and ensure their tech stacks have access to secure, private, and efficient AI agent deployments.

About Phala

Phala is a pioneer in confidential computing and secure data processing. They specialize in leveraging trusted execution environments (TEEs) and secure enclaves to enable secure and verifiable computations. Their expertise in confidential computing makes them a valuable partner in advancing the field of verifiable AI computing.

About Theoriq

Theoriq is the first decentralized protocol for governing and building multi-agent systems by integrating AI with blockchain technology. The platform is centered around an agnostic modular base layer that powers an ecosystem of dynamic AI Agent collectives that are interoperable, composable and decentralized.

Theoriq has raised over $10.4M from leading investors such as Hack VC, Foresight Ventures, Inception Capital, HTX Ventures and more, and have active partnerships with leading web3 and web2 projects including Google Cloud and NVIDIA.

With Theoriq, you're not just part of a network; you're part of a movement that's empowering communities, developers, researchers, and AI enthusiasts to reshape the future of intelligent autonomous systems.

Website | X | Discord | LinkedIn

Let’s have a quick look at what they spoke about.

Exploring the Theoriq Protocol Interfaces: Infinity Studio and Infinity Hub

The Theoriq technology stack comprises of three key sections, the first educational AMAs focused on explaining the Litepaper and the middle layer – the Agent Base Layer. This session started off by highlighting the two interfaces in the tech stack known as Infinity Studio and Infinity Hub.

These tools are designed to enhance user interaction with AI agents and collectives within the Theoriq framework. The Infinity Studio serves as a comprehensive platform where users can interact with AI agents, manage tasks, and analyze data. The Infinity Hub, functions as a centralized location for managing and coordinating various AI agents, facilitating seamless collaboration and data sharing.

The team provided insights into how these tools function and the benefits they offer to users. By leveraging the capabilities of the Infinity Studio and Hub, users can engage with AI agents for a wide range of tasks, from investment analysis to data-driven decision-making. This integration of AI into everyday activities highlights Theoriq's commitment to making advanced AI technology accessible and practical for a broader audience.

Pourya gave us a sneak preview into what the platform for both of these will look like, you can see a preview below or go to the X thread here.

Theoriq

@TheoriqAI

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9:57 AM • Aug 29, 2024

No-code Builders and the Democratization of Dynamic AI Agents

A key theme of this AMA session was the growing importance of AI agents in the digital landscape. The team emphasized their vision of a future where AI agents become ubiquitous, enabling individuals to interact with and utilize AI technology without the need for extensive coding knowledge. This vision is centered around the development of no-code builders, tools that allow users to create and deploy AI agents tailored to specific tasks without writing complex code.

The potential impact of no-code builders is significant, as they democratize access to AI tools and empower individuals to harness the power of AI for personalized applications. Imagine a world where anyone, regardless of technical expertise, can build an AI agent to manage their investments, optimize their business operations, or even provide personalized customer support. This democratization could lead to a major shift in how software and services are developed, moving away from one-size-fits-all solutions to highly customizable and dynamic systems.

Data Management, Preparation and Reliability Key for Efficient AI Systems

Data management, preparation and reliability is a critical aspect of any AI-driven system, and Theoriq is no exception. In the AMA, the team introduced the Extract, Transform, Load (ETL) process, which plays a vital role in managing large volumes of data. For these scenarios, setting up a dedicated database is key to ensure high-frequency queries are handled effectively. This means the system can process and analyze data in real-time, providing users with timely and accurate insights.

For smaller tasks, such as fetching current trends or market cap information for a cryptocurrency, simpler solutions like API calls can suffice. These API calls can efficiently retrieve data without the need for complex data management infrastructures, streamlining the process and reducing overhead. Theoriq's approach to data management highlights the importance of scalability and flexibility, allowing the system to adapt to varying data demands.

To leverage the full potential of AI, data must also be prepared and structured properly before it is used. Starting with clean, structured data is essential to ensure that the AI systems can analyze and interpret information accurately. However, real-world data is often messy and unstructured, requiring extensive cleaning, transformation, and pre-aggregation to make it analytics-ready.

Data preparation in production environments, especially those involving high-frequency data access, are important. Structured data allows AI systems to function more efficiently and provide reliable results. This focus on data quality and preparation is a cornerstone of Theoriq's approach to building reliable and effective AI solutions. But there are also some challenges when interacting with external data sources.

As AI agents increasingly interact with diverse data sources, such as live feeds from social media platforms like Twitter or Discord, issues arise related to the reliability of data sources, the stability of connections, and the potential for AI agents misinterpreting or hallucinating information. Ensuring the accuracy and reliability of the data used by AI agents is key, as errors or inaccuracies can lead to significant consequences.

To address these challenges, Theoriq emphasizes the need for continuous monitoring and error correction mechanisms. By implementing strong systems that detect and correct errors, Theoriq aims to maintain the integrity and reliability of its AI agents, ensuring that users can trust the insights and recommendations given.

Accelerating Production Ready AI with the Theoriq Standard

AI agents are rapidly approaching production readiness, even though they are still in the early stages of development. Quick prototypes and proof-of-concept models can be deployed relatively easily, but robust testing and validation are still necessary to address the limitations and challenges they face. Theoriq is focused on refining its AI agents to ensure they meet the high standards required for production environments.

Looking to the future, Theoriq envisions the deployment of specialized, smaller AI models on individual devices, tailored for specific tasks. This approach not only enhances the accessibility and functionality of AI agents but also reduces the reliance on centralized systems, paving the way for more decentralized and resilient AI applications.

The integration of AI into everyday technology is also set to accelerate, with major tech companies exploring new ways to incorporate AI into their products. Theoriq predicts that advancements in edge computing and the development of smaller, more efficient AI models will drive practical applications across various sectors. For example, integrating AI capabilities into smartphones and personal devices could revolutionize how we interact with technology, making AI a subtle part of our daily lives.

As AI technology becomes more mainstream, we can expect to see its impact in professional sectors, from healthcare to finance to customer service. The ability to create personalized, task-specific AI agents will transform industries, offering new levels of efficiency, accuracy, and personalization. Theoriq's commitment to pushing the boundaries of AI technology ensures that it will play a leading role in shaping this exciting future.

Theoriq envisions a future where specialized, smaller AI models are widely used, making AI an integral part of daily life. By addressing challenges and pushing technological boundaries, Theoriq is set to lead in shaping the future of AI.

Thank you to the team, and all of you for tuning in over the last month to Theoriq’s first educational AMA series. Your attendance, engagement, and questions have made it a success.

Get ready for the next wave of innovation, collaborative AI Agents are coming.

About Theoriq

Theoriq is the first decentralized protocol for governing and building multi-agent systems by integrating AI with blockchain technology. The platform is centered around an agnostic modular base layer that powers an ecosystem of dynamic AI Agent collectives that are interoperable, composable and decentralized.

Theoriq has raised over $10.4M from leading investors such as Hack VC, Foresight Ventures, Inception Capital, HTX Ventures and more, and have active partnerships with leading web3 and web2 projects including Google Cloud and NVIDIA.

With Theoriq, you're not just part of a network; you're part of a movement that's empowering communities, developers, researchers, and AI enthusiasts to reshape the future of intelligent autonomous systems.

Website | X | Discord | LinkedIn

To address this, AI development should start to mirror human intelligence by focusing on specialization. LLM development should be realigned to more specialized roles where they function as AI Agents, a form of software that leverages the capabilities of AI to perform specific functions, in many domains.

Recently, we published an article titled “Wen Agents?” which explored the potential growth of AI agents as an emerging technological field. It provided key insights into AI agents, including how they will be developed and the growing need for these agents to collaborate in multi-agent systems,which Theoriq have labeled as AI Collectives. The article also discussed how leveraging Web3 to develop these systems introduces principles like decentralization, community governance, and open innovation, creating more equitable AI development.

For a refresher, click here to read the full article.

To organize, assess, and grow Agent Collectives in Web3 and beyond, we will inevitably face the above limitations and further challenges that hinder their comprehensive development. Some of these primary challenges include:

• Composability and interoperability: Current AI models struggle to communicate, share data, and collaborate, creating fractured and heterogeneous systems.

• Evaluation and optimization: There are limited ways to measure, assess and choose the best performing AI Agents for specific tasks.

• Safety and security: Malicious agents and unintended consequences could erode trust in AI Agents.

• Decentralization and inclusivity: Convincing the majority that the concentration of AI development to centralized entities is bad for AI development and accessibility.

Each topic presents unique challenges, and to address these, Theoriq has developed a decentralized protocol that is modular, composable, and community permissioned, enabling the creation, discovery and interaction of AI Agents. This approach tackles each challenge in a unified way. In this blog, we will dive into each of these challenges and explain how the Theoriq protocol is practically addressing them.

Composability and Interoperability – Standardizing AI Agent Primitives

Although the LLM field is relatively young, a wide range of tools and frameworks for AI agent creators already exists, which has resulted in a diverse and heterogeneous AI landscape. This diversity encourages innovation but also presents significant challenges when aiming to   integrate these agents into a cohesive system. Differences in data formats, communication protocols, and operational logic create barriers for effective interoperability, highlighting the need for a common layer that supports collaboration and composability among AI agents.

Another major challenge is the lack of standardized protocols and interfaces. Without them, developers will continue creating custom solutions for each integration, increasing complexity and reducing efficiency. Having standardized protocols would simplify integration, allowing agents to communicate, share data, transact and coordinate actions much easier. Without these standards, the development of multi-agent systems will remain fragmented and labor-intensive, hindering seamless collaboration.

Theoriq addresses these issues by offering standardized agentic primitives, modular design, and interoperable frameworks, enabling agents to integrate and collaborate effectively. Cross-agent communication and collaboration is facilitated by the integration of innovative concepts like “Behaviors”, formal interfaces specifying Agent capabilities, and “Permissionless Extensibility”, both which ensure Agents can work and evolve together more efficiently.

Evaluation and Optimization – Robust Mechanisms and Optimization

Even when a diverse system is well-integrated, the complexity of interactions can make it challenging to accurately evaluate and optimize the performance of individual agents and collectives. Evaluating agents in dynamic, real-world environments, where tasks and conditions are constantly shifting, adds another layer of complexity.

How should users measure which agents are reliable and whether they complete the tasks you require efficiently? What methods and metrics should be developed that accurately assess this request?

Agents would firstly have to be  assessed on narrowly defined metrics such as task completion, response time, resource utilization, and accuracy, and more qualitative metrics such as objectiveness, fairness, or even simple preference. The next step to accurate evaluation is in creating robust mechanisms that allow users to evaluate and select the best agents from an ever-expanding pool of choices. The Theoriq protocol has developed and integrated a comprehensive toolkit that uses “Evaluators” to categorize AI Agents based on a combination of preference-based evaluation, staking mechanisms and human feedback.

The next hurdle, once you have found the best performing AI Agents for your specific tasks, how do you combine them into an optimized collective?

This is where Theoriq’s protocol implements a selection of optimization processes that assess, organize and improve the composition of agent collectives. Instead of just selecting the best-performing agents individually, users will be able to measure how well agents work together as a team by estimating the performance of agent combinations, significantly speeding up the process of finding high-performing Collective combinations.

Safety and Security – Aligning Agent Behavior with Intended Purpose

Even with a well-optimized system, complex agent interactions can lead to unexpected risks. It's essential to prevent and reduce the impact of malicious agents to keep the system safe.

Theoriq focuses on safety and security by using community-driven standards, staking, and slashing mechanisms to prevent malicious behavior. There are also banning measures for breaking these rules. Evaluators play a role in governance by providing data-driven, immutable, and verifiable checks to ensure that an Agent's behavior aligns with its intended purpose. These steps are crucial for maintaining transparency, security, and accountability within the ecosystem, creating a secure and trustworthy environment for AI Agent interactions and collaborations.

Decentralization – Equitably Distributing Development and Ownership

We believe that collaborative AI Agents will profoundly impact future economies, and to ensure this impact is widespread and beneficial, their development must incorporate the features of decentralization enabled by Web3. Currently, the development of AI systems are occuring behind gated corporate walls and developed in black box environments. This is concentrating the accessibility to monopolized entities and their developers, limiting competition and suppressing innovation.

The challenge then lies in decentralizing the development, control, and usage of AI systems. For these systems to reach their full potential, they must integrate the benefits of decentralization—such as distributed ownership, governance, transparency, and accessibility—into their design and implementation.

Theoriq are already instilling these benefits in its protocol, with Web3-enabled security for robust AI agent protection and immutable records for auditability and effective reputation systems. Its decentralized marketplace promotes inclusivity, offering fair participation and monetization for developers. Community governance promotes transparency, allowing stakeholders to influence the protocol's development, and in the future, a potential financial layer could align incentives by supporting staking, rewards, and governance, encouraging collaboration and innovation in the ecosystem.

This approach results in more practical, equitable, robust, and secure AI systems that cater to diverse use cases and provide real utility to their users. The Theoriq protocol is instilling this with their decentralized ecosystem where AI creators and users can build and deploy interoperable agents that collectively solve complex challenges.

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The future of AI lies in specialized agents that can collaborate seamlessly, optimize their performance, and operate securely within a decentralized framework. Theoriq is paving the way for this future by addressing the key challenges of interoperability, optimization, security, and decentralization. By leveraging Web3 principles and its innovative protocol, Theoriq is creating a robust and equitable ecosystem where AI agents can evolve, delivering real utility and value. This decentralized approach will not only drive the next wave of AI innovation but also ensure that its benefits are accessible to all.

All of the above concepts are dissected and presented in detail in the Theoriq Litepaper which you can find here.

About Theoriq

Theoriq is the first decentralized protocol for governing and building multi-agent systems by integrating AI with blockchain technology. The platform is centered around an agnostic modular base layer that powers an ecosystem of dynamic AI Agent collectives that are interoperable, composable and decentralized.

Theoriq has raised over $10.4M from leading investors such as Hack VC, Foresight Ventures, Inception Capital, HTX Ventures and more, and have active partnerships with leading web3 and web2 projects including Google Cloud and NVIDIA.

With Theoriq, you're not just part of a network; you're part of a movement that's empowering communities, developers, researchers, and AI enthusiasts to reshape the future of intelligent autonomous systems.

Website | X | Discord | LinkedIn

After introductions, the AMA dove straight into how Theoriq sets itself apart with its multi-faceted approach to evaluating AI Agents, how they are optimized using BOTS, and how they ensure fairness and transparency in the selection. Below you will find a summary of what was discussed. Enjoy!

The Challenge of Choice in an AI-Powered World

As AI continues to grow and become more ingrained into our everyday lives, we will start to see a variety of AI Agents become available for everyday use. Each agent will be designed to perform specific tasks, like booking you a flight or finding you the best performing index fund. Soon, there will be dozens of these choices, each claiming to offer the best service.

The challenge arises when the user is not just worried about functionality but also about trusting the reliability of different Agents. The key to solving this lies in creating robust mechanisms that allow users to evaluate and select the best agents from an ever-expanding pool of choices.

A Multifaceted Approach to Evaluating AI Agents

The Theoriq protocol has developed and integrated a comprehensive toolkit and strategy to address this challenge. The team's approach begins with categorizing Agents based on three primary criteria.

Preference-based Evaluation: This refers to the popularity of an AI Agent, if the agent is popular and frequently used, it is likely a strong performer. This popularity serves as an implicit quality signal, suggesting that the agent is and will be reliable and effective.

Staking Mechanisms: To enhance the evaluation process, Theoriq has introduced a staking mechanism, where users and community members can “stake” on agents they believe will perform well. This encourages active participation and rewards those who correctly identify high-quality agents. Staking adds an economic layer to the evaluation process, allowing users to earn rewards when their staked agents are successfully utilized.

Human Feedback: providing a human evaluation element plays a critical role. Users can provide direct feedback on their interactions with agents through simple thumbs-up ratings or detailed reviews. This feedback is crucial as it offers real-world evidence of an agent’s performance, helping to build a comprehensive profile of each agent. The data from these reviews is further analyzed using AI models, which help to reveal an agent’s strengths and weaknesses.

Optimizing Agent Collectives with Theoriq’s BOTS Algorithm

While choosing individual agents is important, many tasks require multiple agents working efficiently together. This is where Theoriq’s BOTS Algorithm comes into action. The algorithm—an acronym for Bayesian Optimization by Tournament of Substitutions—optimizes the composition of agent collectives. Instead of just selecting the best-performing agents individually, the BOTS algorithm considers how well agents work together as a team.

For example, planning a vacation might require an agent to book flights, another to manage your calendar, and another to find local restaurants. The BOTS Algorithm ensures that the chosen agents don’t just excel individually but also complement each other to achieve your overall goal. It builds a predictive model based on past Agent evaluations and user stakes. This approach allows BOTS to estimate the performance of new combinations without exhaustive testing, significantly speeding up the process of finding high-performing Collective combinations and doing so efficiently.

Ensuring Fairness and Meritocracy in AI

A significant concern with any system that relies on popularity or staking is the potential bias towards well-established agents. Theoriq solves this by ensuring that even new agents have the opportunity to prove their worth. Developers can submit their agents to standardized evaluations that compare them directly with more established agents. If a new agent performs well, it is automatically given priority in relevant tasks, creating an environment that awards meritocracy.

The Power and Potential of Agentic Systems

These innovations are part of a broader shift towards agentic systems—networks of AI agents working collaboratively to perform complex tasks. These systems represent a significant leap forward in AI development, driving personalized optimization that has the ability to revolutionize industries ranging from finance to healthcare.

Looking ahead, platforms like Theoriq’s Infinity Studio, where users can design and deploy their own collectives of AI agents, will empower individuals and businesses to create tailored solutions for specific uses. As we stand on the brink of this new era, the possibilities for AI are truly limitless, driven by the convergence of advanced evaluation techniques, optimization algorithms, and agentic systems. The future of AI lies in applying collaboration, transparency, and accountability, ensuring that the best agents and collectives rise to the top in a fair and efficient manner.

Make sure to tune into our next Weekly AMA Educational series on Discord and X.

If you want to dive deeper into all of the above, head over to our litepaper and read how we are building the future of AI Agent Collectives.

Bondex is a Web3 talent ecosystem that is serving as a talent network and marketplace that prioritizes professionals. Their platform combines a decentralized approach with community ownership, making it the first economically aligned talent marketplace for recruiters, talent, and companies.

The aftershocks of the pandemic have caused a major professional diversion to an "on-demand" workforce model. Managerial skill sets are more centered around building teams that can work remotely and in unpredictable circumstances. With the widened skills gaps and fractured talent issues, companies are looking for more ingenious ways to utilize their workforce and be more creative in sourcing the skills that are in higher demand.

Companies are now untethered in thinking of creative and out of the box ways to adapt, embrace new technologies, work with a global workforce, and overcome bottleneck procedural issues. Decentralized peer-2-peer (P2P) talent networks can facilitate collaboration between partners and customers to streamline the usage of talent networks.

Web3 and Artificial Intelligence (AI) are set to take talent acquisition to the next level for this on-demand workforce model. Bondex is building a fintech-enabled ecosystem, utilizing a proof-of-stake (PoS) blockchain protocol. The Bondex team will be leveraging Theoriq to develop an AI Agent Collective that will be trained on Bondex’s data, be capable of automating job matching and act as a virtual career coach.

How Could AI Agent Collectives Link Talent with Jobs in Web3?

AI Agents have the ability to leverage one or many AI models, allowing them to handle complex tasks, which paves the way for collectives of Agents who can specialize in completing multi-step tasks. By helping Bondex develop their own AI Agents, their platform will be able to more efficiently complete the following tasks:

• Provide feedback, answer questions, and act as a source of truth for the community.

• Process and browse resumes, CVs, portfolios and match them with live job postings, with a heightened focus on researching specific roles.

• Offering a personalized AI Agent career consultant who can help candidates prepare for job interviews and provide feedback in real time.

More recently, Bondex have successfully raised $10 million through pre-seed and seed rounds, including $4 million from investors like Animoca and Morningstar Ventures, and $6.5 million via Coinlist Launchpad. They have recently partnered with Gate.io, ByBit and Matchchain to continue placing the next generation of talent.

Theoriq’s AI Agents have the ability to impact many industries and segments in Web3 and beyond. By partnering with visionary companies like Bondex, and assisting them in building their own AI Agents, Theoriq are continuing their mission of unlocking the potential of collective AI by empowering its clients to actively shape the future of decentralized AI.

About Bondex

Bondex is building the premier Web3 professional network, offering decentralized talent and providing over 1 million monthly active users with opportunities to network, advance their careers, and monetize their connections. Through the Bondex Job Portal’s crowdsourced hiring and tokenized reputation system, Bondex is revolutionizing the talent marketplace, helping companies find top talent five times faster and more cost-effectively than traditional job boards..

Download the App | Jobs portal | Website | Newsletter | X ( Twitter) | YouTube | Telegram Group | Discord | LinkedIn | Instagram | Facebook

About Theoriq

Theoriq is the first decentralized protocol for governing and building multi-agent systems by integrating AI with blockchain technology. The platform is centered around an agnostic modular base layer that powers an ecosystem of dynamic AI Agent collectives that are interoperable, composable and decentralized.

Theoriq has raised over $10.4M from leading investors such as Hack VC, Foresight Ventures, Inception Capital, HTX Ventures and more, and have active partnerships with leading web3 and web2 projects including Google Cloud and NVIDIA.

With Theoriq, you're not just part of a network; you're part of a movement that's empowering communities, developers, researchers, and AI enthusiasts to reshape the future of intelligent autonomous systems.

Website | X | Discord | LinkedIn

This week's series started with a casual chat about the teams experience at the Futurist Conference in Toronto last week, and then dove deeper into the Theoriq protocols three core pillars, the mechanisms behind agent selection, the role of evaluators and optimizers, and the exciting potential of building specialized AI agents, particularly in the domains of education and financial planning. Below is a summary of what was discussed.

Enjoy!

The Importance of Multi Agent Systems Acting Ethically

The Theoriq protocol, utilizing its AI Agent Base Layer has been developed to act as the foundational layer for enabling the efficient operation of multi-agent systems, also known as Agent Collectives – networks of AI Agents that collaborate to perform complex tasks. These systems are particularly valuable for specialized tasks that require the combined expertise of multiple agents, each with a unique set of skills.

An interesting topic to think about in the early stages of AI Agent development is the importance of responsible AI governance. As multi-agent systems become more sophisticated and autonomous, it's important to ensure that these agents operate within ethical boundaries and are accountable for their actions. This is where the principles of AI governance come into play, providing a framework for managing AI agents in a way that is transparent, fair, and aligned with societal values.

How do Interoperability, Composability and Decentralization Create Better AI Systems?

The Theoriq protocol is designed to create the fairer development of AI systems, steering the technology toward a more positive future. The AI Agent Collectives are built on blockchain which ensure more transparency, security and accountability. The protocol is flexible, modular and has a dynamic marketplace that is designed to evolve with AI progress and community needs, built upon three core pillars.

Interoperability Agents: this ensures that different agents can communicate and collaborate effectively across a diverse range of frameworks and models. This is done by giving developers the tools they need to easily build and customize agents, allowing them to work together without needing special permissions or restrictions.

Composable Collectives: this refers to the ability to combine different AI agents, each specialized in a particular task, to perform more complex operations. This is made possible by creating mechanisms to find, assess, and combine different agents into stronger collectives, with a system that tracks how well they do, helping them improve over time.

Decentralized Innovation: this is an integral part in ensuring accountability and transparency in AI Agents. This happens by creating a community-driven marketplace where developers, users, and agents interact, and are incentivized by token economics to continuously improve and expand the capabilities of the network.

How would these core pillars interact in a real world use case?

Imagine having an AI Agent Collective designed for financial market analysis. Multiple AI agents would be required to handle specific tasks throughout the process. Interoperability would be crucial, allowing these agents to share information and determine which ones are best suited for analyzing specific tasks like news feeds, social media trends, or data analytics. A modular and composable Collective would enable developers to create AI systems by seamlessly "snapping together" various agents, similar to building with Lego blocks. And running this on a decentralized structure allows for a community-driven and incentivized AI system that can continuously improve and evolve to meet users' needs.

A Financial Market Analysis Collective. For more details, explore figure 2 from the Theoriq litepaper

The Role of Evaluators and Optimizers in Agent Selection

In order for AI systems to work together effectively, Theoriq have introduced the following key components in their protocol architecture to enable the creation, interaction, and continuous evolution of AI Agents and Collectives.

Evaluators: these are specialized Agents dedicated to producing quality signals that contribute to Agents reputation and further influence their visibility in the protocol. These signals are key to helping users discover the best performing Agents for their specific needs.

Once evaluators have fulfilled their assessment, they submit a Proof of Contribution, this proof is issued to agents that have directly contributed to the successful completion of a task. It acts as a record of the agent’s performance, providing a trackable history of its contributions across various tasks. This proof is essential for maintaining accountability within the AI system, as it allows for the monitoring and evaluation of individual agent performance over time.

Optimizers: specialized Agents designed to enhance the performance of Collectives by identifying optimal Agent formations.

Once Optimizers have chosen the best performing collectives they submit a Proof of Collaboration, this proof is awarded to agents that have successfully worked with other agents to achieve the task’s objectives. Collaboration is a critical component of AI systems, especially for complex tasks that require the integration of multiple specialized agents. The proof of collaboration ensures that agents are not only performing well individually but are also capable of working effectively as part of a team.

These components are responsible for assessing the quality of agent outputs and selecting the best candidates for specific tasks. This process is key for creating an optimal collective of agents that can collaborate to complete sophisticated tasks. Currently there is a routing system powered by an untuned large language model (LLM), which helps in selecting the best agents based on past performance.

Human evaluators are also key to this process and complement AI evaluators by providing contextual understanding, ensuring a robust and effective agent selection process that combines the strengths of both AI and human insights.

AI Agent Use Cases: Education and Financial Planning

One of the most exciting uses of AI is the potential to create specialized agents that cater to specific domains. In last week's AMA, the team highlighted the growing interest in building agents tailored to education and financial planning.

What could these Agents look like?

Educational Agents: these agents are designed to assist with learning and knowledge dissemination. They can be used to create personalized learning experiences, provide real-time feedback, and even offer tutoring in specialized subjects. The development of educational agents represents a significant step forward in making high-quality education accessible to a broader audience.

Financial Planning Agents: these agents are focused on helping users manage their finances more effectively. They can analyze spending patterns, provide investment advice, and create customized financial plans. Financial planning agents have the potential to democratize access to financial expertise, empowering individuals to make more informed decisions about their money.

The Theoriq protocol provides a forward-thinking approach that ensures AI systems are built using transparency, accountability, and ethical governance. Through interoperability, composability, and decentralization, Theoriq strengthens AI systems' functionality and adaptability while aligning them with societal values.

Evaluators and optimizers play key roles in maintaining the integrity of these systems, using their Proof of Contribution and Proof of Collaboration mechanisms. Theoriq's decentralized, community-driven platform supports dynamic AI systems and specialized use cases. As AI advances, Theoriq's innovative approach will be essential in steering the tech towards a positive future.

Make sure to tune into our next Weekly AMA Educational series on Discord and X.

If you want to dive deeper into all of the above, head over to our litepaper and read how we are building the future of AI Agent Collectives.

About Theoriq

Theoriq is the first decentralized protocol for governing and building multi-agent systems by integrating AI with blockchain technology. The platform is centered around an agnostic modular base layer that powers an ecosystem of dynamic AI Agent collectives that are interoperable, composable and decentralized.

Theoriq has raised over $10.4M from leading investors such as Hack VC, Foresight Ventures, Inception Capital, HTX Ventures and more, and have active partnerships with leading web3 and web2 projects including Google Cloud and NVIDIA.

With Theoriq, you're not just part of a network; you're part of a movement that's empowering communities, developers, researchers, and AI enthusiasts to reshape the future of intelligent autonomous systems.

Website | X | Discord | LinkedIn

Building the Foundations of Decentralized AI with Google for Startups Cloud Program

Theoriq is at an exciting development point. The platform is ramping up to a testnet phase, their use cases are starting to take shape and AI Agents are creeping into everyday tech lexicon. As they advance on this trajectory, new opportunities are emerging that will help scale their innovative AI Agent ecosystem.

The participation in this program has aligned with other milestones like joining NVIDIAs inception program in June, and more recently partnering with leading decentralized storage network Filecoin to develop intuitive AI Agent Collectives using their own data.

Benefits of the Google AI Startup Program

By participating in the Google AI Startup Program, Theoriq have gained exclusive benefits, including:

A war chest of Google Cloud credits: the program offers up to $350K in cloud credits, which can be used  over two years for Google-wide perks, this ensures that Theoriq have access to cutting edge compute capacity which taps into the best of Google’s infrastructure, AI products, and foundation models.

Access to dedicated training and resources: Theoriq will benefit from advanced hands-on learning labs focused on AI and the latest Google Cloud technology, including technical training and expert guidance through online webinars and workshops, actively boosting the team's knowledge.

Comprehensive start-up and Web3 specific support: Theoriq will have exclusive access to Google Cloud’s global community of startups, investors, and partners, enabling accelerated growth and scaling opportunities. They will also gain access to AI and Web3-specific resources, including event access, experts, Web3 tooling services, and potential grants from industry leaders.

Collaborating with Industry Pioneers for the Next Era of AI and Web3

The next evolution of AI and Web3 development will see a seamless convergence of the capabilities and benefits of both technologies. To effectively capture this shift, innovative and visionary startups like Theoriq embrace the support of those who have paved the way before them.

With Google as a strategic growth partner, Theoriq can leverage cutting-edge technology and expert support while driving innovation and accelerating the development of their AI Agent Base Layer. Theoriq is proud to partner with tech leaders who share their vision and belief in the transformative impact and limitless innovation driven by decentralized AI.

About Google’s Startups Cloud Program

Through the Google for Startups Cloud Program, startups gain access to a range of benefits tailored for AI innovation. This program provides cutting-edge technology and resources that simplify the development process, offering access to Google’s advanced infrastructure, AI products, and foundational models. By leveraging this open AI ecosystem, startups can accelerate their growth and harness the best tools for their technology solutions.

About Theoriq

Theoriq is the first decentralized protocol for governing and building multi-agent systems by integrating AI with blockchain technology. The platform is centered around an agnostic modular base layer that powers an ecosystem of dynamic AI Agent collectives that are interoperable, composable and decentralized.

Theoriq has raised over $10.4M from leading investors such as Hack VC, Foresight Ventures, Inception Capital, HTX Ventures, and more, and has active partnerships with leading web3 and web2 projects, including Google Cloud and NVIDIA.

With Theoriq, you're not just part of a network; you're part of a movement that's empowering communities, developers, researchers, and AI enthusiasts to reshape the future of intelligent autonomous systems.

Website | X | Discord | LinkedIn

PlayAI is leading the AI gaming segment with their platform that employs a modular chain, designed to feed developers with high-quality data and infrastructure to deploy AI agents and models. Their platform incentivizes their users to share their gameplay data which can be further used for training AI models.

Gaming has evolved into immersive worlds in which users feel connected to their experiences. The market is currently saturated with companies vying for users' attention and engagement, with this challenge PlayAI is set to transform gameplay into more than just an experience, but rather a hyper-personalized journey. They are achieving this by utilizing sophisticated self-learning algorithms to make games more dynamic, fun, and challenging in real-time.

PlayAI’s tech stack focuses on three areas, their Play Market, a data aggregation and validation layer, their Play Dojo, an agent and creation testing layer, and their Play Hub, an Agent integration and Game layer. Theoriq’s decentralized protocol for governing multi-agent systems, aligns perfectly with PlayAI’s dynamic platform and vision.

Theoriq Protocol makes PlayAI Gaming Agents and Models more Scalable, Efficient and Accessible

The partnership aims to combine Theoriq’s advanced AI Layer with PlayAI’s specific gaming agents. These gaming agents are developed using a stream-to-earn functionality in which users can stream their gameplay and earn rewards.

More specifically, the partnership will focus on:

• Cross-Communication and Composability for Gaming Models: to enable seamless interactions between different gaming models and platforms, allowing for enhanced interoperability and the creation of more complex, interconnected gaming experiences.

• Data and Agent Monetization through the Infinity Hub: a centralized marketplace on Theoriq where data and virtual agents can be bought, sold, and traded. Empowering creators and developers to monetize their digital data and agents more effectively, unlocking new revenue streams and creating a more dynamic digital economy.

• Economic Rails using the Agentic Protocol: to provide the necessary tools and frameworks to support secure, efficient, and scalable transactions within the digital ecosystem. This will streamline economic activities, making it easier for participants to engage in commerce, trade, and other financial interactions within our platform.

As Theoriq continues to grow, and AI agents start to integrate into many industries, it is important to partner with innovative platforms that are creating sophisticated, dynamic and accessible environments for more equitable AI development. PlayAI is pioneering the AI gaming segment with their modular platform, and Theoriq are excited to integrate their decentralized AI Agent protocol to continue pushing the boundaries in AI development.

Checkout our partnership announcement from Play AI here:

Play AI 🎲

@playAInetwork

Welcome @TheoriqAI to the Play AI ecosystem

Theoriq brings limitless innovation through composability and extensibility to our gaming agents and models

Check out what you can win to celebrate this partnership ↓

25

10:34 AM • Aug 7, 2024

About PlayAI

PlayAI is the first modular chain for AI in gaming, designed to equip developers with quality gaming data, deploy AI agents and models, and reward users for their data contributions.

By harnessing the decentralized nature of web3, PlayAI aggregates data and fosters collaboration to create Gaming AI models. It is building the Intelligence Layer for hyper-personalized, immersive gaming experiences.

Recently, PlayAI raised $4.3M in VC funding from investors like Polygon Ventures, Jump Crypto, Alphawave, Zentry and MH Ventures.

Website | Twitter | Quest | Medium | Discord

About Theoriq

Theoriq is a decentralized protocol for governing multi-agent systems built by integrating AI with blockchain technology. The platform supports a flexible and modular base layer that powers an ecosystem of dynamic AI Agent collectives that are interoperable, composable and decentralized.

By harnessing the decentralized nature of web3, Theoriq is unlocking the potential of collective AI by empowering communities, developers, researchers, and AI enthusiasts to actively shape the future of decentralized AI.

Theoriq has raised over $10.4M and is backed by Hack VC, Foresight Ventures, Inception Capital, HTX Ventures and more, and have joined start-up programs with Google Cloud and NVIDIA.

Website | X | Discord | LinkedIn

There was so much valuable information we had to share it with you all. Below you will find some important terms for our community to understand over the next few years, with a focus on AI Agent collectives, multi-agent systems and a use case of how AI Agents can already impact web3.

Let's get into it.

What is an AI Agent?

The most important term to understand first, is what we mean when we say an AI Agent?

but much different to your everyday chatbot assistant – this one can dynamically read documents, it can process vast amounts of information online, it can write and execute code, it can even make calculated decisions all by itself!

This is an AI Agent.

An Agent is a form of software that leverages the capabilities of AI to perform a specific function. These Agents use advanced AI models – such as Large Language Models (LLMs) – to perform specific tasks in which users can interact with them using natural language. Agents are able to access real-time data, interact with other software programs, and automate actions, like creating and sending emails or discovering and trading specific stocks.

More formally, at Theoriq, we define agents as follows:

“AI agents are autonomous software systems that leverage modern generative AI models to plan, access data, use tools, make decisions, and interact with the real world to perform specific functions.” Theoriq Team. (2024).  Theoriq: The AI Agent Base Layer.

What are the Foundational AI Models?

Before diving into how agents work and collaborate, it's important to understand what powers them. Foundational AI models, such as LLMs, are advanced AI systems that are trained on vast amounts of data. They learn to understand and generate human-like responses by looking at many examples of data, which range from digital blogs, social media posts, Wikipedia pages, and many other sources. This type of analysis is called ‘training’.

From these examples, AI models, like LLMs, have developed the ability of prediction, where they can predict the next word in a sentence, or paragraph based on patterns learned from their ‘training’ data. This form of training, combined with Instruction Tuning and Reinforced Learning From Human Feedback (RLFH), have evolved LLMs from basic inhuman outputs, to the ability to write essays, answer questions, and even hold conversations. Users can now interact with LLMs through chat interfaces by entering questions or instructions to LLMs, which are called ‘prompts’. We have seen this happen with the growth of interfaces like ChatGPT.

So do these models know all human knowledge? No, their knowledge is limited to what they have learnt during their training. Which means they may not always be up to date with the latest information, and is why agents need access to tools like the internet to solve more complex tasks accurately and efficiently.

What are Agent Collectives?

Now, imagine if instead of relying on one assistant, you had a whole team of specialists. This is where Agent Collectives come into play. In Theoriq, Agent Collectives are groups of AI Agents that collaborate to tackle more complex tasks.

Each agent in the Collective has a specific role. For example, one Agent might be great at analyzing data, while another is skilled at interpreting social media trends. Together, they can handle more complex tasks that would be too challenging for a single Agent.

Let's have a look at a specific example of how AI Agent Collectives could work in reality.

Example: A Web3 Market Analysis Collective

Let's say you want to analyze the latest trends in different Decentralized Financial (DeFi) markets. This is a laborious task that requires many hours of in depth research. But instead of doing this yourself, you can utilize  a group of AI Agents to create a Web3 Market Analysis Collective. This team of specialized AI Agents would include:

• A Router that delegates tasks to different agents depending on the task.

• A Social Media Specialist that analyzes social media data to learn market insights.

• A News Analyst that gathers and summarizes relevant news about the market.

• A Data Analyst that examines the heavy data analysis involved in trading data, Market Caps (MC), Total Value Locked (TVL), and liquidity trends.

Each part of the task is handled by the Agent best suited for it, making the whole Collective more efficient and supercharging your market analysis process. This Collective would boost your productivity, and free you up from examining an overwhelming amount of data. You could pick and synthesize the most useful information relative to your specific needs.

Why Should We Use AI Agent Collectives?

Using Agent Collectives has several advantages for users including:

• Efficiency and Specialization: By dividing tasks among specialized Agents, you can gather results faster and with more accuracy, instead of using primitive models that are trained only to perform one task.

• Collaboration and Creativity: Similar to human teams, AI Agents who work together can offer a more diverse range of perspectives and approaches, this enhances creativity and their ability to solve complex problems.

• Scalability and Flexibility: Collectives are inherently more scalable and adaptable than a single Agent. They can reconfigure themselves in response to new tasks, integrating new specialized agents as needed. This modularity allows for continuous improvement without having to overhaul an entire system.

• Interoperability and Composability: Theoriq's protocol ensures that Agents can seamlessly communicate and collaborate, regardless of their underlying implementations. This interoperability (Agents who can work together) allows for the dynamic discovery and composition of Agent Collectives, enabling more flexibility and more powerful AI agentic systems.

Theoriq is revolutionizing how AI Agents work together by creating a framework where they can form Collectives to tackle complex tasks more efficiently. By leveraging the strengths of individual specialized agents and empowering more seamless collaboration, Theoriq is paving the way for more powerful, adaptable, and responsible AI systems.

The governance of Theoriq's AI collectives is anchored in a decentralized, community-driven model that promotes transparency and accountability. By leveraging mechanisms like Proof of Contribution and Proof of Collaboration, the system ensures that the most effective agents are rewarded and aligned with community values. Stay tuned, as we'll dive deeper into this in the next blog of the educational series.

Whether you're new to AI or looking to deepen your understanding, exploring the world of AI Agents and their Collectives offers a fascinating glimpse into the future of technology. Dive into our X Spaces and Discord sessions to dive into the world of AI Agents and more.

Stay curious, keep learning, and together, let's unlock the full potential of AI!

If you want to have a deeper dive into all of the above, head over to our litepaper and read how we are building the future of AI Agent Collectives.

About Theoriq

Theoriq is a decentralized protocol for governing multi-agent systems built by integrating AI with blockchain technology. The platform supports a flexible and modular base layer that powers an ecosystem of dynamic AI Agent collectives that are interoperable, composable and decentralized.

By harnessing the decentralized nature of web3, Theoriq is unlocking the potential of collective AI by empowering communities, developers, researchers, and AI enthusiasts to actively shape the future of decentralized AI.

Theoriq has raised over $10.4M and is backed by Hack VC, Foresight Ventures, Inception Capital, HTX Ventures and more, and have joined start-up programs with Google Cloud and NVIDIA.

Website | X | Discord | LinkedIn

What is an AI Agent

An AI agent is an autonomous software system powered by one or more AI models with real-time access to data and tools. Tools can include generating and running software code in a contained environment (a sandbox), query databases, search engines to find data, and remote (API) access to systems, including executing smart contracts. An example of a basic agent is one that, through prompting, leverages a Large Language Model (LLM) to read and summarize a document. For a more in-depth introduction to AI agents, Bill Gates wrote an excellent article.

What is needed for agents to succeed

The rapid progress of generative AI models first paved the way for the success of chatbots such as ChatGPT. This led to leading software products such as Microsoft Office, Google Workspace, Zoom, Slack and Salesforce offering “co-pilots” - integrated chatbots that assist users. This was followed in short order by developers building more automated agents that are able to accomplish more complicated tasks on a user’s behalf resulting in a wave of investment interest. One high-profile example is Devin - an agent that specializes in software development. It has also resulted in the release of several competing open-source agents (such as OpenDevin and SWE-agent) and a benchmark for software development. Independent evaluations show that agent performance has improved rapidly. There has been a rapid growth in open source agents (e.g., the list at Awesome AI Agents). Bill Gates recently observed:

Agents are not only going to change how everyone interacts with computers. They’re also going to upend the software industry, bringing about the biggest revolution in computing since we went from typing commands to tapping on icons.

The state of the art for developing agents has been advancing rapidly. For example, Google Brain co-founder Andrew Ng has written a series of articles about techniques for building AI agents. Likewise, there has been a flood of academic research on AI agent architectures for reasoning, planning, and tool calling - as summarized by this research survey:

Meanwhile, AI models are improving rapidly, enhancing AI agents' ability to perform complex tasks, make more accurate decisions, and reduce hallucinations.  In addition, leading providers are racing to add key the planning and reasoning needed for agents to handle more complex assignments: the founder of DeepMind, Demis Hassabis discussed this recently as did OpenAI co-founder John Schulman. Likewise, Google DeepMind recently released a benchmark for AI agent planning showing that it is a priority research area.

Just last week, Anthropic released Claude 3.5 Sonnet, which is the current best AI model. Notably, it has dramatically improved at planning and executing coding tasks - Anthropic reports that it is able to automatically fix 64% of bugs in their test suite - a dramatic improvement in just three months (see also this demo):

This release continues a trend of rapid improvements in leading AI models that is being fueled by tens of billions of dollars of capital investment. This is unlocking new capabilities, particularly in planning and reasoning that will enable powerful AI agents:

Why are agent collectives the future?

The most basic interaction with an LLM is known as a 'zero-shot prompt'. The user instructs a language model to perform a task with no examples or iterations. This approach leverages the model's extensive pre-training on diverse datasets to generate general responses based on its general understanding of language. The next levels include popular techniques like few-shot prompting, Fine-Tuning, and RAG. Few-shot prompting is where the model is given a few examples of the task to guide its output, such as the appropriate customer service responses to typical questions. Fine-tuning is another advanced technique, involving training a model on a particular data set related to the intended task. This process enhances the model's performance on specialized tasks and significantly broadens its applicability across various specialized fields.

Retrieval Augmented Generation (RAG) is yet another sophisticated approach. RAG exposes the model to external databases or knowledge stores to generate more accurate and current responses. It combines LLMs with external data retrieval systems to enhance the accuracy and relevance of responses. These advanced techniques have typically been used with one agent at a time, specializing in one task at a time, with useful results. Such agents are considered expert agents in that one task.

As expert agents get more capable and tackle increasingly complex tasks, there is increasing leverage in assembling collectives of agents that are specialists in multi-step tasks, much as high performance teams of people integrate the skills of specialists. Experts are able to configure and assess specialized agents to make them reliable and useful, building on the contributions of others. This structure allows for community innovation and feedback, accelerating progress greatly over efforts to build monolithic agents that may attempt any task but usually fail at it.

The importance of agent specialization and collaboration will only increase as agents take on increasingly complex tasks with more autonomy. We’re already seeing agents collect information and make recommendations for users to act on explicitly. As a next step, agents will integrate intents to simplify user requests to act. As agent autonomy increases, agents will be responsible for budgets and long-lived workflows.

With a trend towards more specialized agents that work together dynamically, there will be a need for a marketplace to facilitate easy discovery and adoption of agents. We believe this will become increasingly automated so agents can dynamically discover and interact with other agents to create a more interconnected and efficient ecosystem

We are seeing early iterations of these marketplaces: OpenAI’s GPT store was launched in January 2024, to help users find useful and popular custom versions of ChatGPT and in Jun 2024e, Anthropic announced, Projects, for users to share work products that were co-created with Claude to improve innovation in areas like product development and research, where bringing together organizational knowledge from across the company can produce higher-quality outputs. These new features by prominent AI providers highlight the move towards shared agents, and collaboration as superior workflows. However, these systems are quite limited in scope: OpenAI GPTs can’t call each other and are only used if a user specifically asks for them. Likewise Claude Projects provide a private company workspace, but not a marketplace of interoperating agents.

Given the dizzying pace of innovation, we believe that users will want agents to recruit the best agents for a task dynamically, and that is a burning need for a protocol to identify, assess and assemble teams of agents to meet their need.

AI Collectives in Action: a Web3 Use Case

As a concrete example of the capabilities we anticipate emerging soon, consider Web3 Reporter a sophisticated AI Collective designed for Web3 ecosystem analysis. It comprises specialized AI Agents, each with unique capabilities.

When a user asks a question like "Have there been any unusual fluctuations in major DeFi project token prices recently?", the system works as follows:

1. A 'Router' Agent directs the query to the appropriate specialist collective, in this case, the 'Data Analyst' Collective.

2. The Data Analyst Collective then coordinates its team of specialists, including Python and database experts, to address the complex query.

3. The system can adapt and improve over time by integrating new, improved Agents (e.g., 'Python Specialist v2').

4. An 'Optimizer' evaluates new Agents using benchmarks to determine if their inclusion enhances overall Collective performance.

5. The User can then ask to seamlessly execute trades based on the research findings.

This dynamic, self-improving structure allows for the creation of highly capable Collectives that users can access without needing in-depth AI knowledge. The result is a powerful, evolving ecosystem of Agents that can tackle complex tasks with increasing efficiency and accuracy.

Why Web3 is best positioned

Note that Web2 faces obstacles in creating a vibrant AI agent ecosystem because key stakeholders are investing in AI following established SaaS or deep tech investment playbooks. The Theoriq team conducted market research to understand who would be early adopters of AI agents, and agent collectives for an AI-enabled analytics use case. We found that by investing in an AI agent company as if it was a SaaS opportunity projects were forced to monetize quickly, thereby limiting incremental improvements. This led to “GPT wrappers” that were quickly disrupted by the next generation of AI models. By contrast, Web3 communities were able to support and develop innovative projects that win support with a bold vision and that continue to deliver on a roadmap. Enterprise Web2 companies had no risk appetite for hallucinations and bias from external vendors and yet many were attempting to build AI capabilities in-house with existing software, engineering, and even marketing teams, all frantically reading up on transformer architecture and how to build RAG pipelines. In Web3, community adoption was possible for projects in development. Theoriq’s approach to applied responsible AI through smart contracts was well received and there was a clear appreciation for deep machine learning expertise and experience. We believe that the Web3 model will be much more successful in creating agents that revolutionize the future of work and enable consumer productivity.

AI agents and Web3 technologies are highly complementary, offering numerous benefits in modularity and composability, allowing agents to be easily integrated and combined for complex tasks. Web3's decentralized governance ensures that evolving standards for AI agents are community-driven, promoting transparency and inclusivity. Community ownership and censorship resistance empower users and developers, fostering innovation without the risk of centralized control. The open economy of Web3, enabled by micro payments and tokenized rewards, simplifies the funding of agent initiatives and incentivizes participation. Tight integration with the evolving decentralized GPU computing (aka DePIN) ecosystem enables increased choice in infrastructure and deployment. Smart contract automation allows trustless agents to execute tasks seamlessly, creating a reliable and efficient digital environment.

Given the continuing dominance of well-capitalized Web2 giants, we anticipate that Web3 protocols and agent developers will need to interoperate with and leverage proprietary models. Even the leading open weight models are principally being developed by commercial Web2 actors with their own motivations.  We believe that Web3 can mitigate many of the risks associated with this centralization including by reducing the cost and complexity of switching to use different AI models.

Web3-enabled security mechanisms provide robust protection for AI agents, while immutable records ensure auditability and build reputation systems. We believe that digital reputation for AI agents is the killer app for blockchains. However, it is important to recognize that safe and responsible deployment of agents and collectives of agents is a challenging open problem that will requires attention from AI researchers, agent developers and protocol developers. It is vital to build a system that produces a “race to the top,” incentivizing safety with community feedback.

More broadly, blockchains enable the following key requirements for AI agents:

• Payments for use of agents

• Agents to manage digital assets and act on behalf of users

• Staking to prevent malicious behavior by agents

• Incentives for quality feedback

• Distributed networks to collect data in realtime (e.g., by crawling sites)

• Immutable performance history

• Sustaining funding for open protocols and foundational research

Conclusion

We find ourselves at the dawn of the agentic era. The convergence of advanced AI models, Web3 technologies, and the growing demand for responsible intelligent automation is creating a perfect storm for the widespread adoption of AI agents. The Web3 ecosystem, with its inherent principles of decentralization, community governance, and open innovation, is uniquely positioned to lead this revolution.

The future is AI agent collectives, like the Web3 Reporter, becoming integral to our digital lives, seamlessly handling complex tasks across various domains. These collectives will not only enhance individual productivity but also reshape entire industries, from finance and healthcare to education and creative pursuits.

However, as we merge two industries that are both on the margins of existing regulatory frameworks and have both been associated with high-profile cases with bad actors deliberately contravening existing laws, it is crucial that we remain vigilant about the ethical implications and potential risks associated with increasingly autonomous AI systems and unregulated digital currency markets. The evolving institutions of Web2 and the Web3 community commitment to transparency, decentralized governance, and user empowerment will be instrumental in ensuring that this agentic future is built on a foundation of trust, safety, and inclusivity.

The road ahead is not without challenges. Bridging the gap between centralized AI development and decentralized Web3 principles will require innovative solutions and collaborative efforts. Yet, it is precisely these challenges that make the journey exciting and full of potential.

As we embrace this agentic future, let us move forward with both enthusiasm and caution, leveraging the unique strengths of Web3 to create a world where AI agents empower individuals, foster innovation, and contribute to a safe and inclusive digital ecosystem. The future is not just agentic; it's a future where agents and humans collaborate to unlock unprecedented possibilities.

About Theoriq

Theoriq is committed to building a responsible, inclusive, and consensus-driven AI landscape in Web3. At the forefront of integrating AI with blockchain technology, Theoriq empowers the community to leverage cutting-edge AI Agent collectives to improve decision-making, automation, and user experiences across Web3.

Website | X | Discord | LinkedIn

Filecoin AI Agent Collective

At Consensus 2024, Porter Stowell, FF’s Head of Community, demoed a Filecoin AI Agent developed in collaboration with Theoriq. Trained on the Filecoin docs and GitHub repositories, the Filecoin AI Agent allows users to get detailed answers through natural language queries on how to build on Filecoin, troubleshoot common issues, getting started as a storage provider, and more. If you’re interested in testing it out yourself, you can apply for access to the Filecoin AI Agent here.

The Filecoin AI Agent is just the start of the Agentic Collective. Looking ahead, FF and Theoriq will continue working together to develop Agents for a wide range of data hosted on Filecoin to provide seamless natural language interaction with public datasets. FF and Theoriq are currently exploring a CIA AI Agent that will enable researchers and policymakers to efficiently search and verify one million declassified documents. This Agent will leverage 25 years of declassified CIA datasets from MuckRock that are stored on Filecoin. MuckRock has been working with Filecoin Foundation for the Decentralized Web (FFDW) since 2022 to integrate IPFS and Filecoin to preserve critical public interest documents.

What is an Agent?

AI Agents are autonomous software systems that leverage one or many AI models that have access to data and tools, such as running a sandbox, querying databases or even executing a smart contract. This has enabled developers to build Agents that can handle complex tasks, while also paving the way for collectives of Agents that can specialize in completing multi-step tasks.

The Rise of AI Agents

Since the introduction of ChatGPT in November 2022, the AI industry has exploded – with $29.1 billion invested in 2023. While the introduction of the chatbots drove the mainstream adoption of AI technologies, the industry continues to rapidly evolve. Now, we’re seeing the rise of AI Agents that are more customized and built for specific functions - amplifying the impacts of large language models like ChatGPT.

“These Agents are not merely enhancing user experiences; they are pivotal in various sectors, automating complex tasks, personalizing interactions, and analyzing data with unprecedented accuracy. This evolution signifies a shift towards more autonomous, efficient, and intelligent systems, catalyzing innovation and transforming numerous industries. The development and deployment of these Agents are crafting a future where digital and physical realms are seamlessly integrated.”  Theoriq Unveiled: Catalyzing a Decentralized Future of for AI 

AI Agents can develop specialized platforms that harness artificial intelligence to make vast amounts of data more consumable, making it more accessible and highlighting the significance of transparent, verifiable sources. Imagine effortlessly navigating all of the NASA data on Filecoin to enhance scientific research more efficiently. Instead of processing an overwhelming amount of data in real time, AI Agents can help focus the power of AI technologies – thereby amplifying their impact for specific purposes.

The data economy will be built on a foundation of onchain verification, where users will have instant trust in the quality of the data they are accessing. From monetizing access to private datasets through tokenization to powering the next scientific, climate, and health breakthroughs, leveraging AI Agents and decentralized storage will open the door to new advancements for humanity. AI Agents are a crucial element in transforming this envisioned future into today's reality.

The Importance of Decentralized AI

On today’s version of the web, the majority of data is gathered, stored, and provided by just a few ultra-powerful companies, siloing information, centralizing control, and leaving it vulnerable to single points of failure. We’re following the same path with AI, where the AI developers are locking down data and code, which impacts the visibility into how AI models work like what data they’re using and how they’re trained.

Platforms, like Theoriq, are taking another approach and driving the future of decentralization, open, and transparent AI. This is an important step away from the centralized service providers dominating the current AI landscape and a step towards more open and equitable systems that foster innovation without sacrificing individuals.

FF and Theoriq will be hosting X Spaces soon to discuss the future of AI Agents and how decentralized systems can support the development of AI technologies! Stay tuned and follow us on X to stay up to date.

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About Filecoin Foundation **

Filecoin is the world’s largest decentralized storage network. Filecoin Foundation's mission is to preserve humanity's most important information, as well as to facilitate the open source governance of the Filecoin network, fund research and development projects for decentralized technologies, and support the growth of the Filecoin ecosystem and community.

Website | X | GitHub | LinkedIn

About Theoriq

Theoriq is committed to building a responsible, inclusive, and consensus-driven AI landscape in Web3. At the forefront of integrating AI with blockchain technology, Theoriq empowers the community to leverage cutting-edge AI Agent collectives to improve decision-making, automation, and user experiences across Web3.

Website | X | Discord | LinkedIn

Seamless Integration for Enhanced AI Capabilities

This strategic partnership will integrate Theoriq's advanced AI and blockchain technologies with Truflation's comprehensive real-time financial data streams. By leveraging Truflation’s decentralized data infrastructure, Theoriq aims to provide developers and users with unprecedented access to accurate and timely financial data. This integration is expected to:

Empower Developers' Community: By integrating Truflation’s comprehensive real-time financial data into Theoriq’s AI-driven platforms, developers can create AI agents with richer functionalities around traditional financial (TradFi) asset classes. This will enable a new level of sophistication and utility in decentralized finance applications.

Unlock New Use Cases for RWA Financial Data: The collaboration will facilitate innovative use cases for RWA financial data. This includes enabling AI Agents specializing in prediction markets, synthetic assets, and dynamic pricing that leverage accurate and transparent financial data.

Democratize access to complex financial data: At the intersection of Theoriq’s conversational AI capabilities and Truflation data, we're crafting user experiences that turn complex data into simple, natural dialogues with Agents, enabling users to make informed decisions in diverse financial landscapes and explore new investment opportunities.

Commitment to Future Innovations

Both Theoriq and Truflation are dedicated to fostering long-term innovations that will drive further integration of AI and blockchain. This collaboration is poised to set new standards in the field, enabling AI builders to transform data interactions and enhance the utility of blockchain applications.

"We are excited to join forces with Truflation to enable innovative use-cases for RWA data empowered with AI Agent collectives," says Ron Bodkin, CEO of Theoriq. "Imagine a swarm of AI Agents each specializing in their own TradFi asset class and competing among each other for the best portfolio performance that meets user investment profile”

"Adding real-time, independent RWA data to AI Agent workflows is a game-changer that will bring the new wave of adoption and liquidity to the Web3 ecosystem,” says Stefan Rust, CEO of Truflation. “Our partnership with Theoriq is a significant step forward in democratizing financial data."

Watch for more updates as Theoriq and Truflation continue to innovate and redefine the potential of AI and blockchain integration.

About Truflation

Empowered by Coinbase and Chainlink, Truflation stands as the foremost DRP (Definite Reference Point) for economic veracity, driving the tokenization of Real World Assets through its independent, transparent, and real-time financial data. With a comprehensive index tracking over 13 million items, Truflation offers censorship-resistant data infrastructure, fueling systemic advancements in the DeFi economy. This empowers decentralized applications (dApps) such as DEXs to unlock boundless markets. From predicting orange juice and uranium prices to facilitating BTC-denominated oil, gas, and corn markets, Truflation unlocks a diverse range of financial instruments, heralding a new era in the Web3 landscape.

Website | X | Discord | Telegram | Github | YouTube

About Theoriq

Theoriq is committed to building a responsible, inclusive, and consensus-driven AI landscape in Web3. At the forefront of integrating AI with blockchain technology, Theoriq empowers the community to leverage cutting-edge AI Agent collectives to improve decision-making, automation, and user experiences across Web3.

Website | X | Discord | LinkedIn 

Empowering Our Vision

Joining the NVIDIA Inception program grants us access to an array of benefits designed to accelerate our growth and innovation. These include:

Free NVIDIA Deep Learning Institute (DLI) Training Credits: Enabling our team to stay at the forefront of AI and machine learning advancements.

SDK Access: Offering our software development kits on NVIDIA's platform allowing machine learning engineers and researchers to build decentralize AI Agent on our platform.

Preferred Pricing on Select Hardware and Software: Benefiting from exclusive discounts on enterprise-grade GPUs, ensuring we have the best tools for our AI applications.

Free Cloud Credits: Utilizing NVIDIA's cloud solutions through their partners to power our AI models with unparalleled computational resources.

Advancing Decentralized AI with NVIDIA

This collaboration marks a significant milestone for Theoriq. NVIDIA's support goes far beyond access to the world's best cloud computing resources; it is a powerful endorsement from the world’s leading AI hardware company. We are honored to have such a prestigious partner on board, believing in our values and the promise of decentralized AI. With NVIDIA's cutting-edge GPUs and their expansive network, we are poised to propel this mission forward, creating a more secure and efficient environment for AI-driven applications.

"We are proud to join NVIDIA's Inception program," said Ron Bodkin, CEO of Theoriq. "This partnership is a testament to our commitment to expanding the limits of AI. With NVIDIA's support, we are well-equipped to bring our vision of decentralized, modular and composable AI Agents to life."

About NVIDIA

NVIDIA is a global leader in AI computing. Its Inception program is designed to nurture startups revolutionizing industries with advancements in AI and data science. With over 8,500 members across 90 countries, NVIDIA Inception provides critical support to cutting-edge startups through go-to-market support, expertise, and technology.

About Theoriq

Theoriq is committed to building a responsible, inclusive, and consensus-driven AI landscape in Web3. At the forefront of integrating AI with blockchain technology, Theoriq empowers the community to leverage cutting-edge AI Agent collectives to improve decision-making, automation, and user experiences across Web3.

Follow Theoriq:

Website | Twitter | Discord

Enabling AI/Web3 BUIDLers

This strategic partnership will integrate Theoriq's AI Agents with Parasail's scalable DePIN infrastructure. By combining Theoriq's AI expertise with Parasail's ability to amplify value of DePIN services, the partnership aims to enable blockchain developers with:

Compute readiness: Parasail pulls infrastructure from various sources, creating a vast pool of computational resources and general utility hardware. This integration ensures that Theoriq's AI developers can seamlessly access and utilize these powerful resources directly within their development environment.

Scalable infrastructure: Parasail’s network allows Theoriq’s dev community to swiftly scale computational resources to meet the needs of large-scale AI models. This flexibility supports rapid deployment and scaling of AI Agent functionalities, enabling efficient handling of increasing workloads.

Competitive resources: since computational resources come from different providers with Parasail, AI-developers will be able to find the most competitive offer for their specific use case. By tapping into distributed resources, the partnership makes advanced machine learning tasks more accessible and affordable for not only developers but also researchers, startups, and end users.

Reduced Latency: With Parasail's resources distributed globally, builders in Theoriq’s community can process tasks closer to data sources. This proximity significantly reduces latency, crucial for AI use-cases requiring real-time processing.

AI-enhanced Delegation. Since delegation is a crucial part of Parasail architecture, this collaboration with Theoriq may also allow the team to expand their capabilities and offer innovative ways of delegation using AI agents.

More possibilities for our communities

This partnership with Parasail opens up exciting new avenues for both communities, enhancing what can be achieved at the intersection of AI and Web3.

Theoriq and Parasail are dedicated to fostering long-term innovations that will drive further integration of AI and blockchain. This collaboration brings together the demand and supply sides of AI/Web3, enabling innovative use cases.

"We are excited to partner with Parasail, who will provide developers on Theoriq the option to use Parasail’s infrastructure to power AI agents that run on our protocol," said Ron Bodkin, CEO of Theoriq. "Decentralized and interconnected compute that enables our community of AI developers is an important element of our vision of fully decentralized and community-governed AI"

"Our partnership with Theoriq is about instilling confidence among users to access advanced AI via inclusive and seamless web3 infrastructure," said  Sylvan Zhang, co-founder of Parasail. "Together, we’re paving the way for the next wave of innovation and mass adoption in the Web3 ecosystem."

Stay tuned as Theoriq and Parasail continue to innovate and redefine the potential of AI and blockchain integration.

About Parasail

Parasail provides on-chain economic guarantee for DePIN services to boost user confidence and drive DePIN adoption. By connecting established assets and DePIN service proofs, Parasail enables new DePIN projects to build strong service guarantees more efficiently, therefore lowering the cost to acquire and activate real paying users of their DePIN services.

About Theoriq

Theoriq is committed to building a responsible, inclusive, and consensus-driven AI landscape in Web3. At the forefront of integrating AI with blockchain technology, Theoriq empowers the community to leverage cutting-edge AI Agent collectives to improve decision-making, automation, and user experiences across Web3.

Follow Theoriq:

Website | Twitter | Discord

Empowering Innovation and Collaboration in AI.

Theoriq is fundamentally built for the community on the ethos of web3, and we are profoundly grateful for the steadfast support from our vibrant and innovative community as we lead the fusion of AI and Web3 technologies. A pivotal goal for 2024 has been to innovate ways to acknowledge and reward our community members for their vital participation and ongoing contributions. As we usher in this new era, we're thrilled to introduce the Theoriq Proof of Engagement! Developed on the Zealy platform, this marks a major step forward in how Theoriq celebrates and motivates community engagement.

Follow the link to participate:

Join Theoriq

The future of AI-powered DeFi will be built by Theoriq's advanced agent swarm technology. Join Theoriq as they unlock the next phase of autonomous agentic finance. Complete tasks, earn points, and help shape the future of AIFi!

https://zealy.io

Theoriq is driven by a vision to democratize access to AI through Web3, recognizing the critical role our vibrant community plays in this endeavor. As part of our ongoing commitment to this community, we're excited to launch PoE!

Join the revolution today by engaging with other community members, completing quests, and participating in discussions around responsible, inclusive, and reflective AI!

About Theoriq’s PoE Program

At the heart of the Theoriq PoE Program is a desire to do more than just reward participation; it's about fostering an innovative, collaborative, and engaged community that drives the future of AI. Members earn XP through various engagements and contributions, reflecting their active roles in shaping our technology and ecosystem.

These XP are meant as markers of contribution within our ecosystem and are not designed to have real-world monetary value. It's crucial to remember that Theoriq does not currently offer tokens, and we urge vigilance against claims of Theoriq tokens to avoid scams. Please contact a team member or moderator to verify any doubts.

Our team monitors similar community engagement programs and potential issues they encounter. This program is designed to be fully compliant with local regulations, and we’ll continue to ensure that it serves the best interests of our community as the situation evolves.

How to Engage

Engage with us by contributing through various avenues:

• Follow us on our social media channels and participate in conversations

• Contribute to our open-source projects

• Translate Theoriq documentation into other languages

• Create educational content or tutorials about using Theoriq

• Create memes and infographics educating your audience about Theoriq

Rewarding Engagement

While the Community XP lacks real-world value, it is a key metric of involvement and contribution within the Theoriq community. Periodically, we will announce rewards linked to the PoE program, such as access to beta features, exclusive access to events,  special recognition within the community, and more.

A number of anti-Sybil rules were established to prevent bots from taking advantage of community members. Any wallet address identified as being involved in bot activity will be disqualified from the program. Stay vigilant if you spot community members trying to take advantage of the program; reach out to us, and we will be rewarding feedback.

Ready for Launch

We invite everyone to be part of this exciting new chapter in Theoriq's journey. Whether you're a newcomer or a long-standing member, your involvement is crucial to shaping the future of AI with Theoriq.

FAQs

Can XP be transferred between members?

No, XP are unique to your contributions and cannot be transferred.

Are there any caps on earning XP?

There are no caps; engage as much as you can!

How are the top contributors recognized?

A real-time leaderboard will be visible on Zealy.

How are potential abuses of the PoE program handled?

We have robust measures in place to maintain the integrity of the PoE program against gaming or exploitation.

Will there be opportunities for community input on quests and rewards?

Absolutely, we value community feedback and invite suggestions on our Discord channel.

When can members start earning XP?

The updated XP system is already active—start engaging today!

Are there different levels or tiers within the PoE program?

Yes, different levels unlock as you accumulate more XP, each offering its own set of rewards.

Have more questions?

We’re always here to help. Reach out to us on Twitter or Discord for any additional queries!

Early Interest Becoming a Lifelong Journey

Ron’s fascination with AI started in high school - he read about powerful computers running Lisp and wanted a chance to contribute as he learned to program. He was able to jump in and work with popular AI techniques at McGill University, where he excelled, earning his B.S. in Math and Computer Science with honors. This academic passion led him to MIT, where he furthered his studies with a Master’s Degree in Computer Science in the Clinical Decision Making Group. It was here, inspired by the dynamic intersection of theory and practical application, that Ron’s vision for technology’s potential began to crystallize. He pitched a groundbreaking idea at the MIT $100k Entrepreneurship Contest, a pivotal moment that steered him away from academia and towards the entrepreneurial path.

This path led to the co-founding of C-bridge, a company that pioneered B2B Internet solutions, marking Ron's first major foray into implementing his vision. His leadership helped propel C-bridge to impressive heights: from a bold startup to a public company with a valuation over $1 billion and 750 employees. As the CTO, Ron was instrumental in scaling the company, securing major clients like Chevron, Seagate, and Toyota, and driving it to a $100 million run rate. This experience was not just a business venture but a formative chapter in Ron's career, showcasing his ability to lead and innovate on a grand scale.

Through C-bridge, Ron honed his skills in guiding a tech company from its inception through to its IPO, navigating complex challenges and seizing strategic opportunities. This venture served as the foundation of his career, shaping his perspective on technology's role in business and setting the stage for his future endeavors.

AI Pioneer

Ron Bodkin's trajectory in the world of AI advanced significantly when he became Vice President of Engineering at Quantcast, a leader in applying AI in the digital advertising sphere. Here, Ron was pivotal in utilizing vast amounts of data to build machine learning models to create look-alike models for advertising, pushing forward the capabilities of predictive analytics and real-time ad optimizations. His leadership at Quantcast underscored the transformative impact of AI on business models and operational efficiency within large organizations.

Inspired by his successes and recognizing the broader applications of AI in enterprise settings, Ron founded Think Big Analytics. This venture focused on helping large corporations harness the potential of their data through strategic AI solutions. Think Big Analytics quickly became a beacon in the industry, guiding major enterprises in transforming their operations through data-driven decisions and AI integration. The company’s significant contributions to the AI and big data sectors culminated in an acquisition by Teradata, further validating the effectiveness and importance of Ron’s approach to applying AI in large-scale enterprise environments.

Breaking Free: Challenging Centralized AI

Ron's journey through Teradata marked his entry into the echelons of the most innovative companies leveraging AI. At Teradata, he was instrumental in assimilating Think Big Analytics' pioneering AI approaches into Teradata's broader data solutions, pushing the boundaries of what established big data companies could accomplish with advanced AI technologies. This experience not only deepened his expertise but also reinforced his position at the forefront of AI development.

However, it was during his tenure in the CTO Office at Google Cloud that Ron confronted the pivotal challenges of AI centralization. Surrounded by cutting-edge resources and some of the brightest minds in the field, he observed a recurring pattern where the power and potential of AI were predominantly controlled by a few. This insight was unsettling and sparked a profound reevaluation of his views on AI's future. Ron was passionate about advocating for a path for AI that was inclusive and broadly beneficial but instead saw a narrow focus on commercialization of the technology.

This epiphany brought Ron full circle to where he began—in AI research, but with a renewed purpose. He realized that the path to truly revolutionary AI wasn't just through advancing the technology under the aegis of a few but by enabling a broad community to participate in and shape its evolution. This realization rekindled his original passion for pushing the technology, setting the stage for a new chapter where he would advocate for a more open, accessible AI—ushering in a new era where AI could be a collective advancement rather than a centralized power.

Beneficial AI advocate

At the Vector Institute, Ron contributed to cutting-edge AI research, focusing on the development of deep learning technologies that could further the boundaries of AI's capabilities. This role allowed him to collaborate with leading AI researchers, including notable figures in the AI community. At Vector, his work centered on applying AI to real-world problems, striving to make AI both more effective and ethical, which aligned with his growing commitment to responsible AI development.

This also led him to the Schwartz Reisman Institute, where he deepened his involvement in the intersection of AI and society. Here, Ron focused on how technological advancements in AI could be governed and utilized to ensure positive societal impacts. The institute's commitment to studying and shaping the societal implications of AI resonated with Ron's vision of democratized technology, providing a platform to advocate for policies and frameworks that ensure AI developments benefit all segments of society, not just a few.

Redefining AI's Future with Theoriq

Armed with a renewed vision and profound insights from his research work at Vector and Schwartz Reisman Institutes, Ron brought together other co-founders - CTO Arnaud Flament, CPO David Mueller, and Head of Research Ethan Jackson, united with the idea of building the AI technology that serves humanity collectively, ensuring equitable access to innovation and fair recognition of contributions across the board. Together they embarked on another pioneering venture, one that is designed to transform the landscape of AI by decentralizing the power dynamics traditionally dominated by major tech corporations. The founders commitment to fostering a more inclusive and ethical AI ecosystem fueled the foundation of Theoriq, aiming to democratize access to AI technologies and empower a global community of innovators.

Theoriq is not just another AI company; it is a revolutionary platform designed to challenge the status quo of AI development. By leveraging a decentralized network, Theoriq enables independent developers, researchers, and smaller enterprises to contribute to and benefit from cutting-edge AI technologies without the need for large-scale corporate infrastructure. This approach ensures that advancements in AI are not only technically robust but also broadly accessible and driven by a community-oriented development model.

At the heart of Theoriq's innovative approach is its AI agent protocol, which facilitates a wide range of AI capabilities by allowing users to interact with and deploy AI agents across various applications and sectors. This protocol is designed to support scalable deployment and integration, ensuring that users can leverage AI tools effectively regardless of their technical background or business size. Theoriq’s AI agent protocol underscores the platform’s commitment to making AI as versatile and user-friendly as possible, promoting a future where AI is a common resource shared equitably across all sectors of society.

Closing remarks

Ron’s story isn’t just about technological achievements; it's about a steadfast commitment to ensuring that AI benefits everyone, not just a select few. With Theoriq, he aims to forge a future where AI is accessible and empowering, where every developer, researcher, and user has the tools to innovate and thrive. This isn't merely innovation; it's a movement to reshape the technology landscape, making it inclusive and equitable. Join us as we continue to innovate and democratize AI, paving the way for a future where technology serves all of humanity, not just a few monopolists. Together, we can build a world where AI is a tool for empowerment and a source of limitless potential.

Empowering Advanced AI Functionality through Strategic Collaboration

Our partnership aims to integrate 0G’s infinitely scalable storage capabilities with Theoriq's sophisticated AI agents that translate natural language into executable data queries. This synergy will:

• Enhance Data Processing: Theoriq's agents will leverage 0G’s data availability infrastructure to streamline complex data operations, transforming raw data into actionable insights with unmatched accuracy and efficiency.

• Expand Autonomous Capabilities: Utilizing 0G's AI models, Theoriq’s agents will extend their functionalities to include advanced autonomous tasks, such as predictive analytics and decision-making processes, further enhancing their versatility and effectiveness.

• Drive Intuitive Interactions: At the intersection of Theoriq’s conversational AI capabilities and 0G’s robust models, we're crafting user experiences that turn complex blockchain interactions into simple, natural dialogues.

This partnership enables the AI industry forward into a new era of decentralized intelligence. This collaboration not only elevates our technological capabilities but also empowers developers and users by setting new standards for integrating AI with blockchain, catalyzing community-driven innovation and user-centric solutions in the space.

Ron Bodkin, CEO of Theoriq, emphasizes the transformative potential of this alliance, stating, “Partnering with 0G enables Theoriq to harness their extensive data availability solutions and advanced AI models to bolster the capabilities of AI agents running on our protocol. This is a leap towards realizing our vision of a decentralized, community-driven AI ecosystem where advanced, autonomous agents thrive on-chain, driving innovation and accessibility.”

"At 0G, we're excited to partner with Theoriq to redefine the possibilities of AI on the blockchain. It's a fusion of our vision for a decentralized future where AI enhances every interaction," said Michael Heinrich, CEO of 0G Labs.  "By combining Theoriq's advanced AI agents with our robust data infrastructure, we are setting the stage for a new era of innovation in Web3, where AI-driven applications and agents will be the predominant form of interaction on-chain."

About 0G

0G is an infinitely scalable data availability (DA) layer and modular A.I. blockchain. With a team of top-tier PhDs and world-renowned cryptographers, 0G is crafting the future of data storage, offering scalable, interoperable solutions that anticipate the evolving needs of the digital world.

To learn more, visit 0g.ai.

About Theoriq

At Theoriq, our mission is to democratize AI technology through a decentralized protocol that fosters community-driven development. Our agentic AI ecosystem supports the creation and collaboration of AI agents, enabling them to perform complex tasks with a level of autonomy and accuracy previously unattainable in traditional models.

Stay tuned for more updates as Theoriq and 0G continue to innovate and expand the boundaries of what AI and blockchain can achieve together. Visit us at Theoriq.ai to explore how we're building the future of decentralized AI.

ChainML Labs, the creators of Theoriq, started in 2022 with the vision of embracing community-governed AI. Co-founder and CEO Ron Bodkin brought together other co-founders - CTO Arnaud Flament, CPO David Mueller, and Head of Research Ethan Jackson, united with the idea of building the AI technology that serves humanity collectively, ensuring equitable access to innovation and fair recognition of contributions across the board. So far ChainML Labs has raised over $10M in two rounds of funding from visionary investors such as Hack VC, Foresight Ventures, Inception, HTX Ventures, Figment, Hypersphere, Alumni Ventures, IOSG, LongHash, HashKey, SNZ, and others.

Since inception, the team was drawn to the potential of Web3 technology in achieving their vision of a broadly accessible AI platform, and collaborated with Space and Time to build their AI Data Engineer Houston. Being at the epicenter of the tectonic shifts in AI , we recognized that the future of AI is Agentic - that’s where the story of Theoriq begins.

The Rise of AI Agents

The recent advancements in Generative artificial intelligence (AI) are transforming humanity’s relationship with technology. As foundational Large Language Models (e.g. GPT4, Llama3 etc.) continue to improve, AI Agents are becoming more performant and autonomous. These agents are not merely enhancing user experiences; they are pivotal in various sectors, automating complex tasks, personalizing interactions, and analyzing data with unprecedented accuracy. This evolution signifies a shift towards more autonomous, efficient, and intelligent systems, catalyzing innovation and transforming numerous industries. The development and deployment of these agents are crafting a future where digital and physical realms are seamlessly integrated.

While impressive as individuals, *collectives of interacting AI agents *are believed by many experts to represent the next frontier of AI progress [DeepMind]. They believe this because for humans, much of our progress and success as a species is due to our ability to specialize and collaborate in social groups towards shared objectives with shared incentives. Another important factor in human success is individual agency. Individual human activities are not centrally controlled. The decentralization of social roles (e.g. the ability to choose how to participate in competitive labor markets) is a key factor for innovation and productivity. Determination and alignment of mutual interests are further coordinated by social frameworks like democracies and justice systems.

As we stand at the beginning of agentic AI, there is an opportunity to build it on the same principles that underpin human success: coordinated division of labor, decentralized economies, and inclusive governance.

To unlock the potential of increasingly complex and sophisticated multiagent systems, there is a need for a universal forum in which diverse types of AI agents can come together and collaborate, just as humans do in a decentralized economy. Given its complementary principles of decentralization, transparency, and user empowerment, Web3 provides the ideal technical platform for building such a forum. We are proud to introduce Theoriq: A universal Base Layer for Agentic AI.

Introducing Theoriq

At Theoriq, we envision a different future—one where AI benefits are democratized through decentralization, ensuring broader accessibility and fostering innovation. Recognizing the potential of AI agents as the cornerstone of this new paradigm, Theoriq has embarked on creating an AI agent Base Layer to enable this shift. The goal is to promote community-driven governance, foster choice, and ensure safety and security, thereby leveling the playing field for independent developers globally.

Theoriq's AI Agent Base Layer was born out of the necessity to counter the monopolistic control of AI Agent technologies and to integrate their capabilities within the emerging Web3 framework. The protocol introduces a Web3-enabled consumption layer and an open marketplace for AI Agents, effectively democratizing access to AI technologies. This approach not only enhances transparency but also aligns with the foundational principles of Web3, contrasting starkly with the centralized models of existing tech giants.

"Today marks a pivotal moment for ChainML and for the broader AI and Web3 communities," said Ron Bodkin, Co-founder and CEO of ChainML. Theoriq is not just a platform; it's a revolution in how AI agents are developed, deployed, and interacted with. Our protocol enhances how agents communicate and operate, ensuring they are not only interconnected but also more autonomous and capable than ever before."

With Theoriq, our goal is to create the world’s best AI innovation ecosystem - one where users have access to best-in-class AI agents and developers have the tools they need to meet current and future user demands. One of the keys to building a self-sustaining innovation ecosystem is to ensure that developers, especially, have a wide range of economic opportunities in the protocol. These include transparent revenue models, available seed funding, and support for contributing to public goods initiatives.

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Roadmap

• Theoriq Unveiled (May 14, 2024):This significant milestone marks the public introduction of Theoriq, showcasing its pioneering approach and vision to bring decentralization to AI development.

• Litepaper (Q2 2024):The publication of the Litepaper will provide a comprehensive overview of Theoriq’s technology and the underlying principles of the decentralized AI agents.

• Testnet (Q3 2024):The launch of the Testnet will serve as a robust testing ground for developers and early adopters to explore the capabilities of Theoriq.

• Mainnet (Early Q4 2024):Transitioning to Mainnet represents the full operational launch of Theoriq, where all functionalities will be live and accessible for community use.

Stay tuned for the launch of the Infinite Rewards Program, designed to celebrate and motivate our community members as they engage with Theoriq and contribute to the development and application of AI in Web3. By participating in discussions, completing quests, and contributing to projects, members will be able to earn XP that signifies their role and influence within Theoriq. While non-monetary, XP will reflect the value of each contribution towards advancing collaborative and decentralized AI technology. As part of our launch, members will enjoy various perks linked to their rewards, such as early access to features, special event invitations, and recognition within the community. This initiative is a testament to our commitment to democratizing AI innovation by empowering and rewarding our community for their engagement and creativity.

Web3 Future of AI

The potential fusion of AI and Web3 technologies signals a significant departure from the traditional, centralized paradigms that dominate the AI landscape today. Embodying the core principles of decentralization, transparency, and user sovereignty, Web3 architecture provides a fertile ground for the development of AI systems that are not only open and equitable but also more aligned with democratic values.

In this emerging framework, AI systems benefit from decentralized data architectures, ensuring that no single entity can monopolize the vast data resources that AI technologies are built upon. This fosters a fairer environment where biases are minimized and diverse data sets enhance the robustness of AI models.

Moreover, the evolution of AI algorithms within this decentralized ethos occurs in an open-source milieu. Here, a community of developers—rather than a single corporate entity—continuously contributes to and refines these algorithms, enhancing innovation and accessibility. This collaborative approach not only accelerates technological advancements but also ensures that these innovations are widely accessible, rather than being gated behind corporate walls.

Governance in this decentralized AI scenario is also radically transformed. Rather than being dictated by a handful of decision-makers, it is managed by a broad network of stakeholders, mirroring the democratic processes that govern public institutions. This ensures that the trajectory of AI development is aligned with the broader needs and ethics of the community it serves.

By leveraging blockchain technology, this new era of AI promises secure and transparent data transactions, facilitating an environment where AI models and applications can be developed, accessed, and improved upon by a global community of innovators. This shift not only democratizes the development process but also significantly broadens participation in the economic benefits derived from AI.

This holistic approach to decentralizing AI—with its emphasis on distributed data, collaborative algorithm development, and democratic governance—ensures that the future of AI will be more equitable, secure, and aligned with the ethos of Web3. In this way, Theoriq is not merely participating in the industry but actively shaping a future where technology serves the collective good, powering a more inclusive and innovative digital economy.

“I believe that ChainML's Theoriq isn't just a breakthrough — it has the potential to be the cornerstone for the next frontier in AI and blockchain convergence" said Ed Roman, Managing Partner at Hack VC.  “Theoriq's vision is to redefine the possibilities of democratizing AI Agent development in ways that align deeply with Web3's ethos of transparency and community governance.  The opportunity for Theoriq is to catalyze a robust agent ecosystem that integrates into multiple layers of our digital lives."

Theoriq's initiative comes at a critical time when the integration of AI in everyday applications is becoming a norm. By ensuring that the AI landscape does not consolidate power among a few, Theoriq facilitates a more equitable digital economy. This is crucial for fostering a future where technology empowers rather than controls, promoting an environment of innovation and inclusivity.

Stay connected and join our community @TheoriqAI!

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