Thank you for the valuable input and feedback from Zhenyang at Upshot, Fran at Giza, Ashely at Neuronets, Matt at Valence, and Dylan at Pond.

This research seeks to unpack critical areas in AI that are relevant to developers in the field and explore the potential burgeoning opportunities in the convergence of Web3 and AI technologies.

TL;DR

Current advancements in AI-centric decentralized applications (DApps) spotlight several instrumental tools and concepts:

• Decentralized OpenAI Access, GPU Network: AI's expansive and rapid growth, coupled with its vast application potential, makes it a significantly hotter sector than Bitcoin mining once was. This growth is underpinned by the need for diverse GPU models and their strategic geographical distribution.
• Inference and Agent Networks: While these networks share similar infrastructure, their focus points diverge. Inference networks cater primarily to experienced developers for model deployment, without necessarily requiring high-end GPUs for non-LLM models. Conversely, agent networks, which are more LLM-centric, require developers to concentrate on prompt engineering and the integration of various agents, invariably necessitating the use of advanced GPUs.
• AI Infrastructure Projects: These projects continue to evolve, offering new features and promising enhanced functionalities for future applications.
• Crypto-native Projects: Many of these are still in the testnet phase, facing stability issues, complex setups, and limited functionalities while taking time to establish their security and privacy credentials.
• Undiscovered Areas: Assuming AI DApps will significantly impact the market, several areas remain underexplored, including monitoring, RAG-related infrastructure, Web3 native models, decentralized agents with crypto-native API and data, and evaluation networks.
• Vertical Integration Trends: Infrastructure projects are increasingly aiming to provide comprehensive, one-stop solutions for AI DApp developers.
• Hybrid Future Predictions: The future likely holds a blend of frontend inference alongside on-chain computations, balancing cost considerations with verifiability.

Introduction to Web3 x AI

The fusion of Web3 and AI is generating immense interest in the crypto sphere as developers rigorously explore AI infrastructure tailored for the crypto domain. The aim is to imbue smart contracts with sophisticated intelligence functionalities, requiring meticulous attention to data handling, model precision, computational needs, deployment intricacies, and blockchain integration.

Early solutions fashioned by Web3 pioneers encompass:

• Enhanced GPU networks
• Dedicated crypto data and Community data labeling
• Community trained modeling
• Verifiable AI inference and training processes
• Comprehensive agent stores