The Integration of AI and Web3: Observations from the Hong Kong Consensus Conference 2025

AI and web3 are seen as the two main driving forces propelling humanity into the next stage of technological growth. After ChatGPT brought a revolutionary AI experience, on-chain AI has quickly evolved from a concept into the most promising sustainable growth track in the web3 space.

At the recently concluded Hong Kong Consensus Conference 2025, the integration of AI and web3 became a hot topic, with related discussions taking place in both the main venue and the breakout sessions. Let's take a look at some promising AI projects presented at the conference.

1. AI Infrastructure

1. AI Agent Launch Platform and Framework

In the past six months, the launch platforms and framework-based AI infrastructure for AI Agents have been thriving. These projects provide a low-threshold platform for developers and ordinary users to use AI Agents, making it one of the key directions for current AI projects.

• 0G Labs: The first decentralized artificial intelligence operating system (deAIOS), by building an AI proprietary Layer 1, connects computing resources, data, and models to create a distributed AI development ecosystem.

• DeAgentAI: An innovative platform focused on decentralized AI Agents, dedicated to promoting the development of multi-agent technology ( Multi-Agent Systems ). Users can create, manage, and coordinate AI Agent networks.

• Autonomys Network: A decentralized infrastructure stack aimed at achieving secure and autonomous human-machine collaboration. Users can create AI agents that act independently.

• Gaia Network: A decentralized AI infrastructure platform that supports the distributed development and operation of AI agents and applications, addressing issues of privacy, scalability, and accessibility in AI.

• Questflow: 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.

2. Decentralized AI

Decentralized AI is the ultimate goal of on-chain AI. Currently, many projects are working on computing power, data, models, etc., hoping to break the monopoly of large companies on LLM through decentralization and help the public gain ownership of data and models.

• Vana: Committed to building a decentralized user data sovereignty platform, turning personal data into financial assets.

• Hyperbolic: An open-access AI cloud platform that integrates global computing resources, providing affordable and scalable GPU resources and AI services.

• OpenLedger: Focused on the next generation of networks in AI and blockchain, providing decentralized economic infrastructure.

• IO.NET: A decentralized computing platform that provides on-demand access to GPU and CPU cluster services.

• Aethir: An innovative platform providing distributed cloud computing infrastructure.

• MinionLab: Decentralized Autonomous AI Agent Network for real-time mining of internet data.

• GAIB: An economic layer solution for the AI and high-performance computing fields, financializing and tokenizing GPU resources.

• Kite AI: A decentralized Layer 1 blockchain platform designed for the AI economy.

• Automata: Provides a middle layer of privacy protection and non-tracking computing functions for decentralized applications.

• Public AI: Build an open and transparent AI data platform that supports multi-modal data collection and annotation.

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 the output results. Some projects hope to achieve verifiability of the AI training process through technologies such as ZKP and TEE, ensuring the reliability of AI output results.

• Phala Network: A decentralized cloud computing platform that provides trusted privacy computing and AI inference services for on-chain applications.

• Brevis: A decentralized computing engine that provides verifiable off-chain AI and blockchain computation.

• Verisense Network: An innovative platform focused on decentralized data verification and trustworthy AI.

2. AI Use Cases: Potential and Expectations

Compared to the rich AI infrastructure, there are currently few standout AI practical use case projects. In addition to the Twitter bot AIXBT, there are:

• Narra: The Gamefi AI Agent platform on Berachain generates real-time dynamic narrative content.

• AI Travel: AI-driven travel assistant that customizes travel plans through chat.

• HeyTracyAI: An AI agent for sports commentary in basketball featuring NBA champion Tristan Thompson.

• AskJimmy: An AI Agent platform focused on finance and trading.

3. Traditional Projects Transitioning to AI

Many traditional web3 projects have also announced AI transition plans:

• Public chains like Sui, Near, Flow, and Aptos actively participate in AI-related conferences, indicating that they will support AI development from aspects such as underlying architecture and account innovation.

• Eigenlayer is building a decentralized trust layer ( Decentralized Trust ), providing verifiable cloud services ( Verifiable Cloud ), and offering on-chain proof for off-chain AI computations.

4. Challenges and Future

The development of on-chain AI still faces many challenges, including insufficient model reliability, ambiguity in prompt intentions, storage and hardware limitations, and issues related to privacy and security. These challenges not only present technical difficulties but also foster significant innovation opportunities. In the long run, the industry is hopeful about the development of on-chain AI and looks forward to promoting the integration and prosperity of AI and Web3 through improved infrastructure, innovative use cases, and community collaboration.