DePINs are an integral part in the blockchain, they signal a potential transformation in the way critical infrastructure is developed, operated, and monetized. At its foundation, DePINs uses blockchains and decentralized networks to build and scale physical infrastructure without dependence on centralized networks. This model fosters a new era defined by openness, transparency, community led growth, shared ownership, and aligned incentives for all participants. The true impact of DePINs lies in its ability to challenge traditional infrastructure models, which are frequently burdened by high costs and inefficiencies. The main focus of this article is to highlight DePINs infrastructures in three sectors:

• Compute, Storage & Bandwidth

• Decentralized AI

• Energy

Compute, storage, and bandwidth are the three foundational pillars that power the internet, it’s important to understand how data is managed, stored, and delivered today and whether that may change in the near future. If storage networks require greater demand, compute networks need increased supply, and retrieval networks depend on density to compete, how can we integrate these services to build a scalable, decentralized alternative?

This is where DePINs infrastructure comes in to provide a decentralized scale to make storage and computing of data decentralized, Decentralization can offer the opportunity for better distribution, increased scope of rewards, and a protection mechanism against centralization.

Let's look at DePINs protocols responsible for decentralized computing and storage

Hyperbolic is an open-access AI cloud that enables users to offer compute, run inference tasks, and tap into lower cost GPUs. The team behind Hyperbolic believes AI should be a public resource not just open-source code, but also the compute power that drives it. They argue that while some organizations share their models, the essential fuel compute is still tightly controlled by centralized data centers.

Hyperbolic challenges this status quo by pointing to a vast untapped resource: over two billion computers worldwide sit idle for more than 19 hours a day. What if that dormant compute could be redirected toward a more productive, communal purpose?

That’s the vision. With Hyperbolic, anyone can (in theory) contribute their unused compute to the network. Providers list their idle GPUs, consumers rent them by the hour, and both sides benefit, compute providers earn rental income and points (which may eventually translate into tokens).

On the inference side, Hyperbolic provides access to the following model types:

Text-to-Text: Models capable of generating text from text prompts. This includes tasks such as translation, summarization, question answering, and creative writing.

Text-to-Speech: Models that convert text into spoken audio. These models can be used for applications like voice assistants, audiobooks, and accessibility tools.

Text-to-Image: Models that generate images from textual descriptions. These models are useful for creating visual content, illustrations, and design prototypes.

Text-to-Video: Models that create short videos based on text prompts. This technology can be used for creating marketing materials, educational content, and entertainment.

For context, AI inference refers to the process of using a trained model to generate accurate outputs from new inputs based on prior learning. While it typically demands less compute than training, it can still be resource-intensive.

At present, Hyperbolic supports several variants of the Hermes and Llama models, as well as Stable Diffusion for image generation and Melo TTS for audio synthesis.

Read more on their docs

Livepeer is a decentralized video infrastructure network built on the Ethereum blockchain. It provides a scalable, cost efficient, and open-source solution for video encoding, transcoding, and streaming essential components of video delivery over the internet.

Livepeer wants to provide the infrastructure for developers to create live or on demand video at over 50x cheaper costs. They achieve this through the use of orchestrators and delegators, the two key participants in the Livepeer network.

Orchestrators join the Livepeer network by running specialized software that grants access to their computing resources such as CPUs, GPUs, or bandwidth which are then used to transcode video submitted by users. To participate, orchestrators must hold LPT tokens; the more tokens they stake, the more work they can handle, increasing their potential rewards in the form of LPT.

Delegators, on the other hand, support the network by staking their own LPT tokens toward orchestrators they believe are performing reliably. In return, they earn a portion of the fees generated by that work, as well as future LPT token emissions. This stake based access model allows Livepeer to scale its economic incentives alongside rising demand for its services.

Livepeer’s business model stands out by integrating its native token into a rapidly expanding and highly relevant vertical. Short-form video content has become ubiquitous, driving engagement across nearly every industry from marketing and entertainment to news and education. Platforms like TikTok, Instagram, and Twitter increasingly rely on short form video to fuel their ecosystems. At the same time, global mobile data consumption largely driven by video is growing at over 25% annually. If this trend holds, Livepeer is well-positioned to absorb some of this demand, provided it continues to offer transcoding at significantly lower costs than traditional providers.

The network’s architecture is refreshingly straightforward rare for crypto infrastructure. Orchestrators simply run a node, set their transcoding price, and the Livepeer protocol automatically routes jobs to their GPUs, requiring no hands-on management. On the demand side, users receive affordable video processing, while orchestrators earn from otherwise idle GPU resources. Delegators, in turn, collect a share of fees if they’ve staked effectively with active orchestrators. It’s a streamlined and thoughtfully designed system that balances simplicity, efficiency, and incentive alignment.

Read more on their docs

DePINs provide the physical backbone offering distributed compute, storage, and bandwidth that allows AI models to be trained, fine-tuned, and run without relying on centralized cloud providers while traditional AI pipelines, training and inference depend on centralized cloud providers, which control resource pricing, access, and deployment flexibility

Let's explore protocols actively contributing to the decentralized AI (DeAI) space through their functional products.

Prime Intellect is building a decentralized, crypto backed protocol and platform that aggregates global compute resources GPUs from both centralized providers and distributed contributors. It enables collaborative training and development of open AI models, allowing participants to co-own and benefit from the models they help create. Prime Intellect’s core business, to put it in one sentence, is to build a decentralized AI platform that aims to “commoditize computing power and intelligence.” This is not a simple DePIN, it is more like an "Airbnb for computing power". Imagine that idle GPU resources around the world, whether personal mining machines or data centers, can be gathered through Prime Intellect's "Compute Exchange" to form a huge "unified resource pool".

Prime Intellect's vision is not just to provide cheap computing power. Its deeper goal is to enable the next generation of AI innovation, especially those AI models and applications that require large-scale, distributed computing capabilities. Its typical application scenarios are mainly concentrated in the following key areas:

First of all, distributed training of large-scale language models (LLMs) is one of the core application scenarios of Prime Intellect. They have successfully demonstrated that their platform can support the training of very large-scale LLMs. For example, they trained the INTELLECT-1 model with 10 billion parameters and performed distributed training on GPUs contributed by 30 independent computing power providers in three continents (including five countries), achieving a high computing utilization rate of 83-96%, proving that decentralized training can match or even exceed centralized efficiency. The recently released 32-billion-parameter INTELLECT-2 model is trained through globally distributed reinforcement learning (RL), further expanding the boundaries of its distributed training capabilities. This is crucial to breaking the monopoly of AI giants on computing power and promoting the development of open source LLM.

Secondly, in AI model training, high-quality data is the "fuel". Prime Intellect, through its GENESYS framework and leveraging the SYNTHETIC-1 dataset, enables large-scale synthetic data generation, particularly in areas such as mathematics, coding, and science that require high-precision verified reasoning. SYNTHETIC-1 is an open source dataset containing 1.4 million structured tasks and verifiers, which aims to make up for the shortcomings of traditional data collection on complex reasoning tasks. This provides critical data support for training more powerful and reliable AI models.

Read more on their docs

Ritual is a software centric decentralized AI protocol aiming to merge the strengths of blockchain and artificial intelligence. It positions itself as a sovereign execution layer purpose built for decentralized AI. The project emerged in response to fundamental flaws in the current AI ecosystem such as the dominance of a few large players, prohibitive compute costs, centralized APIs controlled by major labs, and the opaque nature of model architectures and outputs.

To address these challenges, Ritual introduced Infernet, its first network iteration. Infernet is designed to integrate AI into on-chain applications by offering a modular suite of execution layers that act as AI coprocessors for any blockchain. While its architecture is technically complex featuring data availability layers, routing mechanisms, node clusters, and decentralized storage, it provides a flexible foundation for trustless, verifiable, and composable AI execution across Web3 systems. In short, Ritual acts as a bridge between blockchains and AI, enabling smart contracts to make AI requests, leverage off-chain compute, verify outputs on-chain, and integrate AI functionality directly into decentralized applications. As more data and user activity continues to migrate on-chain, Ritual is well-positioned to become a key infrastructure layer supporting that transition.

Anyone building on-chain apps that need:

• Trustless cryptographic operations

• Private computations

• Decentralized key management

Ritual makes it possible to do all this without relying on centralized infra.

Read more on their docs

One of the biggest issues today with renewables is that many of the sources are intermittent and dependent on weather conditions (i.e. wind does not blow consistently, the sun does not shine 24/7). Integrating these energy sources into existing grids is also challenging, the grid has to manage fluctuating power levels which can strain infrastructure. Traditional power grids were designed for one-way energy flow from centralized power plants to consumers. Despite these challenges, we’re seeing the advancement of smart grid technology, large-scale battery storage systems and an opening up on the regulatory front to allow DePINs to participate more fully in energy markets. We continue to believe distributed energy is fertile ground for crypto and DePINs.

Let's take a look at some of the DePINs in the energy sector and what they are building.

Daylight is a protocol hoping to sell user distributed energy resource (DER) data to energy companies that want to make the electric grid more performant, with an end goal where anyone can build a virtual power plant (VPP) from within the Daylight protocol. VPPs are effectively a system of integrated, heterogenous energy sources that provide power to the grid. They’re uniquely suited for DePIN given its incentivization and coordination benefits.

The core user flow of Daylight is as follows:

Homeowners can store excess energy produced by a DER; this is standard, as there’s typically enough in excess to produce revenues and sustain a home’s energy consumption

In times of high demand, distribute this energy back to the grid

VPP operators can aggregate these homes into pools and sell it back to a marketplace

Daylight wants to make it easier to aggregate DERs across the country, both for energy companies and DER owners. For the homeowners, the value-add is obvious: more money in a simpler way. For energy companies, the value-add is aggregating supply of energy to loop back into the grid. Daylight is one example but there are others working on similar problems using a different approach.

StarPower is yet another decentralized energy network that hopes to connect energy devices like ACs, EVs, and home storage batteries to increase energy efficiency and reduce costs across the energy stack. They’re positioning themselves as “Uber for energy” as they aggregate these devices under one roof to more effectively manage operations. The team saw the same opportunity in facilitating the development and growth of VPPs, and their tiered roadmap seems to focus on hardware.

StarPower’s system lets users connect their devices to the network, which earn STAR rewards based on their electricity data and response of the connected devices. While they’re initially focused on water heaters and ACs, they hope to eventually integrate services for EVs and energy-storage batteries. The team has already built a product suite and a plug that’s currently available for purchase, the Starplug. It’s a simple wall plug that can be used with any type of StarPower-compatible device and features real-time monitoring, remote control, and energy optimization.

StarPower’s other products include the Starbattery and the Starcharger. The former is a home energy storage solution that handles excess energy in the grid, while providing backup power during outages and managing optimization during peak energy consumption hours.

In the next article, we will be taking a look at other traditional sectors DePINs are impacting such as Telecoms.