GuShiio.com At the just-past Hong Kong Consensus Conference 2025, what AI projects emerged?
Author: Anci, core contributor to Biteye
AI and web3 are recognized in recent years as the two carriages for mankind to enter the next technological growth point. After ChatGPT brought a disruptive AI experience, on-chain AI also quietly completed a gorgeous turn from meme to infrastructure, becoming the most determined new track for sustainable explosion in the minds of the web3.
At the just-past Hong Kong Consensus Conference 2025, the integration of AI and web3 was also a hot topic. Whether it was the main venue or the branch venue, discussions about AI x web3 were endless. The Biteye team went deep into it, learned about many potential AI projects, and brought everyone to share on the front line.
1. AI infrastructure
1. AI Agent launch platform and framework
With the popularity of $AI16Z and $VIRTUAL at the beginning of the year, the construction of AI Agent launch platforms and framework-based AI infrastructure has become very popular in the past six months. These projects provide developers and ordinary users with a low-threshold platform to own and use AI Agents, and are one of the key directions of this round of AI projects.
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0G Labs
It is the first decentralized artificial intelligence operating system (deAIOS) that builds a distributed AI development ecosystem by building an AI-specific Layer 1 to connect computing resources, data and models. 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 and gain benefits to the decentralized network by running nodes.
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DeAgentAI
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It is a decentralized infrastructure stack designed to achieve safe and autonomous human-computer collaboration. Anyone only needs a solid-state drive (SSD) to join the network to become part of the node. Users can create dedicated AI agents that can act autonomously, such as booking services, managing funds, coordinating meetings, and even participating in on-chain governance.
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Gaia Network
It 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 solve AI privacy, scalability and accessibility issues. Rather than building centralized servers, GaiaNet builds a distributed network of edge computing nodes controlled by individuals and enterprises to host fine-tuned artificial intelligence models based on the unique domain knowledge and expertise of node operators.
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Questflow
: A decentralized network composed of multiple AI agents. Users only need to describe their needs, and the AI agent network can complete tasks independently. Multiple AI agents can perform tasks seamlessly and leverage the collective intelligence and capabilities of these AI agents to achieve efficiency and speed unmatched by a single AI model or humans.
2. Decentralized AI
Decentralized AI is the ultimate goal of on-chain AI. Currently, many projects are constantly working hard towards this goal in the direction of computing power, data, models, etc., hoping to break the monopoly position of large companies on LLM through decentralization and help The public gains ownership of data and models.
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Vana
We are committed to building a decentralized user data sovereignty platform to turn personal data into financial assets. Vana is an EVM-compatible Layer 1 blockchain that, through its unique design Data Liquidity Pools (DLP), allows users to contribute and verify data through the blockchain, generate tokenized assets for AI model training, while ensuring data security and quality through Proof of Contribution and privacy protection technologies. Yesterday, he received investment from YZi Lab and CZ served as a consultant.
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Hyperbolic
It is an open-access AI cloud platform that provides users with affordable and scalable GPU resources and AI services by integrating global computing resources. The platform supports AI inference services, on-demand GPU access, and monetization of idle hardware, helping companies, researchers and individuals reduce costs and efficiently utilize computing resources. Hyperbolic provides services to well-known on-chain AI projects such as Virtuals and AI 16z, and revealed at this conference that it will launch its own AI Agent framework to further promote the innovation and application of AI computing.
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OpenLedger
Is a next-generation network focused on AI and blockchain that provides a decentralized economic infrastructure that allows developers to access high-quality data, fine-tune Dedicated Language Models (SLMs), and deploy them as a paid service. SLM is its core strength and is specifically designed for areas such as blockchain, DeFi and smart contracts; it also leverages the Open LoRA framework to efficiently run thousands of fine-tuning models on a single GPU, reducing costs and maintaining high throughput. Combining Datanets Data Network and Model Factory, OpenLedger provides a complete solution for data aggregation, model optimization and secure deployment.
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IO.NET
Is a decentralized computing platform that provides on-demand access to GPUs and CPU clusters, designed 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 through IO Workers, which is suitable for scenarios such as high-performance computing and AI model training without having to buy expensive hardware.
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Aethir
It is an innovative platform focusing on providing distributed cloud computing infrastructure. Among them, Aethir Earth is a bare metal GPU cloud specially designed for AI computing tasks, providing high-performance computing capabilities;Aethir Atmosphere is a cloud GPU network that optimizes the gaming industry and supports low-latency, high-quality gaming experience. Users can also add their own GPUs to the Aethir platform, become contributors and earn revenue.
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MinionLab
Is a decentralized network of autonomous AI agents, called “Minions”, running on user devices and used to mine data in real time from the Internet. Device owners can obtain MINION by supporting the network and running these autonomous data mining agents.
Token rewards. By leveraging idle computing resources, MinionLab provides a more resilient, cost-effective and scalable approach to data mining, while simultaneously pushing the AI industry towards decentralized and user-driven development.
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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 philosophy is to treat GPUs as assets and computing power as money. GAIB solves current computing resource allocation and financing problems through decentralized computing networks, segmented ownership and blockchain technology (L1/L2), while meeting the huge demand for high-performance computing resources in the AI era.
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Kite AI
is a decentralized Layer 1 blockchain platform specifically designed for the artificial intelligence economy that aims to unlock fair access to AI assets (data, models, and agents) and rewards through its innovative Proof of AI (PoAI) consensus mechanism. Kite AI is committed to building an open, collaborative ecosystem that allows data providers, AI developers, and end users to benefit from a decentralized AI economy.
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Automata
Designed to provide mid-level privacy protection and trackless computing capabilities for decentralized applications (DApps). It provides developers and users with an efficient, trustworthy and decentralized environment that maximizes data privacy and user autonomy.
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Public AI
Our vision is to create an open and transparent AI data platform that supports the collection and annotation of multimodal data, including text, audio, video and map data. At the same time, it provides efficient and low-cost AI-assisted data annotation services. The AI assistant will initially mark the data, and then the AI validator will conduct a comprehensive review to ensure data quality. Adopt a fair and transparent Proof of AI consensus mechanism so that everyone can participate in the AI training process by contributing data.
3. Verifiable AI
One of the important challenges facing AI development is the opacity of the training process and the inability to guarantee the accuracy of AI output results. At present, many projects hope to achieve the verifiability of the AI training process through ZKP, TEE and other technologies to ensure the reliability of AI output results.
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Phala Network
It is a decentralized cloud computing platform that provides trusted private computing and AI reasoning services for on-chain applications. Its products and services include a secure computing network based on the Trust Execution Environment (TEE), which supports smart contracts, AI model training and reasoning, and data privacy protection. Phala Network has natural advantages in scenarios that require high privacy, such as DeFi, DeSci, NFT markets and on-chain AI Agent development. It can ensure data security and computing verifiability through TEE technology.
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Brevis
It is a decentralized computing engine positioned to provide verifiable off-chain AI and blockchain computing, combine zero-knowledge proof (ZKP) to improve privacy and efficiency, focus on financial data privacy protection, and support smart contracts and Web3 applications. Expansion. Its products provide a secure computing environment that ensures the privacy of AI reasoning and transactions on the chain while maintaining verifiability and are suitable for DeFi, predictive markets and privacy-driven AI reasoning.
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Verisense Network
It is an innovative platform focusing 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 and provides transparency for artificial intelligence models. Training data and reasoning processes eliminate “black box” problems and make AI decisions more credible. DeFi, predictive market and compliance monitoring suitable for serving AI models can ensure the reliability of data on the chain.
2. AI Use Cases: Potential and Expectations
Compared with the rich AI infrastructure, there are still relatively few outstanding AI actual use case projects. In addition to our familiarity with the Twitter robot AIXBT, speakers at this event also mentioned the Virtuals ecosystem. @BukProtocolTravel booking services, NBA star commentators,, and DeFAI Agent under the ARC framework @askjimmy_aietc., providing more possibilities for the application of AI Agents.
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Narra
Gamefi AI Agent platform on Berachain can use Narra’s AI engine to generate real-time dynamic narrative content, interact with players, promote story development, and provide personalized experiences in gamified scenarios. In addition, Narra also supports the generation and interaction of AI-NFTs. These NFTs are not only digital assets, but also have intelligent features to dynamically interact with users.
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AI Travel
It is an AI-driven travel assistant that can help users automatically customize different travel plans through chat; it can also help users call hotels and order suitable rooms at the best price; and provides hotel flights and other activities through browser plug-ins. Booking and price comparison services.
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HeyTracyAI
It is an AI Agent that focuses on sports commentary in the basketball field participated by NBA champion Tristan Thompson. It can provide real-time analysis and predictive insights for games.
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AskJimmy
Is an AI Agent platform focusing on the financial and trading fields. Its main goal is to create a decentralized multi-strategy hedge fund independently operated by AI Agents.
3. Transformation of traditional projects to AI
As the trend goes, many traditional web3 projects at this event have also embraced AI and announced their respective AI transition plans.
Husband chains such as Sui, Near, Flow and Aptos actively participated in AI-related meetings at this conference. During the discussion, they said that the emergence of AI Agents is of important help in simplifying the complex blockchain interaction process and can bring more users into the world of web3 to solve the interactive problems that have plagued the industry before. The tokenization and mutual cooperation of AI Agents also allow everyone to see more possibilities for AI to be linked. In this regard, husband chains have expressed the development goals of AI first, and will fully support the development of AI from aspects such as underlying architecture and account innovation. At the same time, developers are encouraged to innovate and develop AI applications on the chain through activities such as hackons.
Eigenlayer, which used to focus on Retaking services, also said in an AI sub-conference co-sponsored by it that it is working hard to build a decentralized trust layer and provide verifiable cloud services to provide on-chain proof for AI training and offline operations such as reasoning and prediction, and help the development of verifiable AI Agents.
4. Challenges and the Future
As a hot topic at this Hong Kong Consensus Conference 2025, the discussions and sharing about AI and Web3 are intense and exciting. While looking forward to a beautiful blueprint, many guests also mentioned that the current development of on-chain AI still faces many challenges, including insufficient model reliability, ambiguity of prompt word intentions, storage and hardware limitations, privacy security and other issues. These challenges not only bring technical problems to the industry, but also breed huge innovation opportunities. In the long run, everyone is full of hope for the development of AI on the chain, and looks forward to jointly promoting the integration and prosperity of AI and Web3 through further improvement of infrastructure, use case innovation and community collaboration.
