The fusion of artificial intelligence (AI) and cryptocurrency technologies has sparked the development of a thriving AI ecosystem within Web3. While there is considerable interest in this space, there seems to be a lack of clarity about the different protocols and how they function together. This report aims to provide an overview of the Web3 AI supply chain, delving into each layer of the technology stack and exploring the competitive landscape.
The Infrastructure Layer
Generative AI is predominantly powered by large language models (LLMs), which require high-performance GPUs for training, fine-tuning, and inference. Within this layer, there are general-purpose GPUs, ML-specific GPUs, and GPU aggregators. General-purpose GPU marketplaces offer computing power suitable for model inference, while ML-specific GPU marketplaces cater to a broader range of AI tasks, including training and fine-tuning. GPU aggregators serve as product distributors by consolidating GPU supply from both general-purpose and ML-specific marketplaces.
The Middleware Layer
While the previous layer facilitates access to GPUs, middleware is necessary to connect this computational resource to on-chain smart contracts in a trust-minimized manner. Zero-knowledge proofs (ZKPs) play a crucial role in this layer, enabling verification of inference outputs while preserving data privacy. Decentralized marketplaces for ZKP verifiers allow interested parties to bid on the verification process. Additionally, developer tooling and application hubs that provide software development kits (SDKs) and services for building AI agents and applications are also part of this layer.
The Application Layer
The top layer of the Web3 AI tech stack consists of user-interfacing applications that leverage the permissionless AI processing power facilitated by the underlying layers. These applications cover a wide range of use-cases, including smart contract auditing, blockchain-specific chatbots, metaverse gaming, image generation, and trading and risk-management platforms. While this market is still emerging and relies on centralized infrastructure, advancements in the underlying infrastructure and the maturation of ZKPs are expected to unlock the potential for next-generation AI applications.
Investor Outlook
Given the evolving nature of AI functionality, infrastructure and middleware protocols present attractive investment opportunities. The demand for substantial GPU power, ZKP technology, and developer tooling and services is expected to increase as Web3 AI applications develop further. While the market is currently promising, it remains to be seen whether early entrants will sustain their positions or if new leaders will emerge in the coming years.
In conclusion, the Web3 AI ecosystem offers a vast potential for innovation and growth. Understanding the different layers of the technology stack and the competitive landscape is vital to navigate this dynamic market successfully.
The source of the article is from the blog mgz.com.tw