Whether in the main venue or the sub-venues, discussions about AI x web3 are incessant.

Written by: Anci, Core Contributor of Biteye

AI and web3 are recognized as the two driving forces propelling humanity into the next technological growth point in recent years. Following the disruptive AI experience brought by ChatGPT, on-chain AI has quietly completed a stunning transformation from meme to infrastructure, becoming the most promising new track for sustainable explosion in the minds of web3 enthusiasts.

At the recently concluded Hong Kong Consensus Conference 2025, the integration of AI and web3 was also a hot topic, with discussions about AI x web3 echoing throughout both the main venue and the sub-venues. The Biteye team delved into this area, learning about many promising AI projects and bringing frontline insights to everyone.

1. AI Infrastructure

1. AI Agent Launch Platforms and Frameworks

With the explosive popularity of $AI16Z and $VIRTUAL earlier this year, the construction of AI infrastructure such as AI Agent launch platforms and frameworks has been very active in the past six months. These projects provide developers and ordinary users with low-threshold platforms to own and use AI Agents, making it one of the key directions of this round of AI projects.

0G Labs is the first decentralized artificial intelligence operating system (deAIOS), which builds a Layer 1 dedicated to AI, connecting computing resources, data, and models to create a distributed AI development ecosystem. Developers can use the modular tools provided by 0G to build more efficient and transparent AI Agents while receiving fair reward distribution. Users can contribute computing resources to the decentralized network by running nodes and earn rewards.

DeAgentAI is an innovative platform focused on decentralized AI Agents, dedicated to promoting the development of Multi-Agent Systems. Through DeAgentAI, users can create, manage, and coordinate AI Agent networks for various scenarios such as business automation, data analysis, and personalized recommendations.

Autonomys Network is a decentralized infrastructure stack aimed at achieving secure and autonomous human-machine collaboration. Anyone can join the network as a node with just a solid-state drive (SSD). Users can create dedicated AI entities that can act autonomously, such as booking services, managing funds, coordinating meetings, and even participating in on-chain governance.

Gaia Network is a decentralized AI infrastructure platform that supports the distributed development and operation of AI Agents and applications. It integrates distributed storage, computing, and data verification through blockchain technology to address issues of privacy, scalability, and accessibility in AI. GaiaNet does not establish centralized servers but builds a distributed network of edge computing nodes controlled by individuals and enterprises to host fine-tuned AI models based on the proprietary domain knowledge and expertise of node operators.

Questflow is a decentralized network composed of multiple AI Agents, where users only need to describe their needs, and the AI agent network can autonomously complete tasks. Multiple AI agents can seamlessly execute tasks, leveraging the collective intelligence and capabilities of these AI Agents to achieve efficiency and speed unmatched by a single AI model or human.

2. Decentralized AI

Decentralized AI is the ultimate goal of on-chain AI. Currently, many projects are striving towards this goal in areas such as computing power, data, and models, hoping to break the monopoly of large companies on LLMs through decentralization and help the public gain ownership of data and models.

Vana is dedicated to building a decentralized user data sovereignty platform that turns personal data into financial assets. Vana is an EVM-compatible Layer 1 blockchain that allows users to contribute and verify data through its unique design, Data Liquidity Pools (DLP), generating tokenized assets for AI model training while ensuring data security and quality through Proof of Contribution and privacy protection technologies. It recently received investment from YZi Lab, with CZ serving as an advisor.

Hyperbolic is an open-access AI cloud platform that integrates global computing resources to provide users with affordable and scalable GPU resources and AI services. The platform supports AI inference services, on-demand GPU access, and monetization of idle hardware, helping businesses, researchers, and individuals reduce costs and efficiently utilize computing resources. Hyperbolic serves well-known on-chain AI projects such as Virtuals and AI16z, and revealed at this conference that it will launch its own AI Agent framework to further promote innovation and application in AI computing.

OpenLedger is a next-generation network focused on AI and blockchain, providing decentralized economic infrastructure that supports developers in obtaining high-quality data, fine-tuning specialized language models (SLM), and deploying them as paid services. SLM is its core advantage, designed specifically for blockchain, DeFi, and smart contracts; it also utilizes the Open LoRA framework to efficiently run thousands of fine-tuned models on a single GPU, reducing costs while maintaining high throughput. Combined with Datanets data network and Model Factory, OpenLedger offers a complete solution for data aggregation, model optimization, and secure deployment.

IO.NET is a decentralized computing platform that provides on-demand access to GPU and CPU clusters, aiming to eliminate users' need for expensive hardware or infrastructure. Through a decentralized physical infrastructure network (IOG Network, composed of independently operated distributed hardware nodes), users can instantly access distributed GPU clusters via IO Workers, suitable for high-performance computing, AI model training, and other scenarios without the need to purchase expensive hardware.

Aethir is an innovative platform focused on providing distributed cloud computing infrastructure, where Aethir Earth is a bare-metal GPU cloud designed for AI computing tasks, offering high-performance computing capabilities; Aethir Atmosphere is a cloud GPU network optimized for the gaming industry, supporting low-latency, high-quality gaming experiences. Users can also contribute their own GPUs to the Aethir platform and earn rewards.

MinionLab is a decentralized autonomous AI agent network, where these agents, known as "Minions," run on user devices to mine data from the internet in real-time. Device owners can earn MINION token rewards by supporting the network and running these autonomous data mining agents. By utilizing idle computing resources, MinionLab provides a more resilient, cost-effective, and scalable way of data mining while pushing the AI industry towards decentralized and user-driven development.

GAIB is an economic layer solution dedicated to the fields of AI and high-performance computing, aiming to create a new asset class and economic system by financializing and tokenizing GPU resources. Its core concept is to view GPUs as assets and computing power as currency. GAIB addresses the current challenges of computing resource allocation and financing through a decentralized computing network, fractional ownership, and blockchain technology (L1/L2), while meeting the enormous demand for high-performance computing resources in the AI era.

Kite AI is a decentralized Layer 1 blockchain platform designed for the AI economy, aiming to unlock fair access and rewards for AI assets (data, models, and agents) through its innovative Proof of AI (PoAI) consensus mechanism. Kite AI is committed to building an open and collaborative ecosystem where data providers, AI developers, and end-users can all benefit from the decentralized AI economy.

Automata aims to provide a middle layer of privacy protection and non-tracking computing functions for decentralized applications (DApps). It offers developers and users an efficient, trusted, and decentralized environment that maximizes data privacy and user autonomy.

Public AI envisions creating an open and transparent AI data platform that supports the collection and annotation of multimodal data, including text, audio, video, and map data. It also provides efficient and low-cost AI-assisted data annotation services. AI assistants will perform preliminary annotations on the data, which will then be thoroughly reviewed by AI verifiers to ensure data quality. Utilizing a fair and transparent Proof of AI consensus mechanism, everyone can participate in the AI training process by contributing data.

3. Verifiable AI

One of the significant challenges facing AI development is the lack of transparency in the training process and the inability to guarantee the accuracy of AI output results. Currently, many projects aim to achieve verifiability of the AI training process through technologies such as ZKP and TEE, ensuring the reliability of AI output results.

Phala Network is a decentralized cloud computing platform that provides trusted privacy computing and AI inference services for on-chain applications. Its product services include a confidential computing network based on Trusted Execution Environment (TEE), supporting smart contracts, AI model training and inference, as well as data privacy protection. Phala Network has inherent advantages in scenarios requiring high privacy, such as DeFi, DeSci, NFT markets, and on-chain AI Agent development, ensuring data security and computational verifiability through TEE technology.

Brevis is a decentralized computing engine positioned to provide verifiable off-chain AI and blockchain computing, combining zero-knowledge proofs (ZKP) to enhance privacy and efficiency, focusing on financial data privacy protection, and supporting the scalability of smart contracts and Web3 applications. Its products provide a secure computing environment, ensuring the privacy of on-chain AI inference and transactions while maintaining verifiability, suitable for DeFi, prediction markets, and privacy-driven AI inference.

Verisense Network is an innovative platform focused on decentralized data verification and trusted AI, helping developers verify data sources and ensure the authenticity and integrity of training data. It also supports auditing and verification of AI decision-making processes, providing transparent training data and inference processes for AI models, eliminating the "black box" problem and making AI decisions more trustworthy. It is suitable for serving AI models in DeFi, prediction markets, and compliance monitoring, ensuring the reliability of on-chain data.

2. AI Use Cases: Potential and Expectations

Compared to the rich AI infrastructure, there are still relatively few standout AI use case projects. In addition to the familiar Twitter bot AIXBT, the speakers at this event also mentioned @BukProtocol from the Virtuals ecosystem, which can facilitate travel booking services, NBA star commentator @HeyTracyAI, and the DeFAI Agent @askjimmy_ai under the ARC framework, providing more possibilities for the application of AI Agents.

Narra is a Gamefi AI Agent platform on Berachain that utilizes Narra's AI engine to generate real-time dynamic narrative content, interact with players, drive story development, and provide personalized experiences in gamified scenarios. Additionally, Narra supports the generation and interaction of AI-NFTs, which are not only digital assets but also possess intelligent characteristics, allowing for dynamic interaction with users.

AI Travel is an AI-driven travel assistant that helps users automatically customize different travel plans through chat; it can also assist users in calling hotels to book suitable rooms at the best prices; and it provides booking and price comparison services for hotels, flights, and other activities through a browser plugin.

HeyTracyAI is an AI Agent focused on sports commentary in the basketball field, involving NBA champion Tristan Thompson, capable of providing real-time analysis and predictive insights for games.

AskJimmy is an AI Agent platform focused on finance and trading, with the primary goal of creating a decentralized multi-strategy hedge fund operated autonomously by AI Agents.

3. Traditional Projects Transitioning to AI

As a trend, many traditional web3 projects are embracing AI at this event, announcing their respective AI transition plans.

Established chains like Sui, Near, Flow, and Aptos actively participated in AI-related meetings during this conference. They expressed that the emergence of AI Agents is significantly helpful in simplifying complex blockchain interaction processes, bringing more users into the web3 world and addressing the interaction challenges that have long plagued the industry. The tokenization of AI Agents and their collaboration also revealed more possibilities for AI on-chain. In response, these established chains expressed their development goals for AI, committing to fully support AI development from aspects such as underlying architecture and account innovation, while encouraging developers to innovate and develop AI applications on-chain through hackathons and other activities.

Eigenlayer, which previously focused on Restaking services, also stated in its co-hosted AI sub-meeting that it is working to build a Decentralized Trust layer, providing Verifiable Cloud services to offer on-chain proof for off-chain computations such as AI training, inference, and predictions, aiding the development of verifiable AI Agents.

4. Challenges and Future

As a hot topic at the Hong Kong Consensus Conference 2025, discussions and sharing about AI and Web3 were intense and exciting. While envisioning a bright future, many speakers also mentioned that the current development of on-chain AI still faces numerous challenges, including insufficient model reliability, ambiguity in prompt intentions, storage and hardware limitations, and privacy and security issues. These challenges not only present technical difficulties for the industry but also give rise to significant innovation opportunities. In the long run, there is great hope for the development of on-chain AI, with expectations that through further improvement of infrastructure, innovation in use cases, and community collaboration, the integration and prosperity of AI and Web3 can be jointly promoted.

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