KevinQin.eth
KevinQin.eth|Feb 23, 2025 02:15
The Evolution and Future Development of DeFai in Three Stages The development of the DeFai market will be divided into three stages: first, efficiency is required, then decentralization, and finally privacy. The first phase of DeFi artificial intelligence will focus on efficiency, improving user experience through various tools to accomplish complex DeFi tasks without the need for solid protocol knowledge. Examples include: Artificial intelligence that can understand user prompts even if the format is incomplete, and quickly execute real-time market research for swaps in the shortest block time, helping users make favorable decisions based on their own goals If innovation is realized, it can help users save time and energy, while lowering the threshold for on chain transactions, and may create a "phantom" moment in the coming months. In the second stage, the agent will conduct autonomous transactions with minimal human intervention. Trading agents can execute strategies based on third-party perspectives or data from other agents, creating a new DeFi model. Professional or mature DeFi users can fine tune their models and build proxies to create optimal returns for themselves or clients, thereby reducing manual monitoring. In the third stage, users will begin to pay attention to wallet management issues and artificial intelligence verification, as they will demand transparency. TEE and ZKP solutions will ensure that artificial intelligence systems are tamper proof, free from third-party interference, and verifiable. Finally, once these stages are completed, the no code DeFi AI engineering toolkit or AI-as-a-Service protocol can create a proxy based economy that trades using models trained on cryptocurrencies. Although this vision is ambitious and inspiring, there are still several bottlenecks that need to be addressed: most of the current tools are just ChatGPT packaging, without clear benchmarks to identify high-quality projects. On chain data fragmentation pushes artificial intelligence models towards centralization rather than decentralization, and it is currently unclear how on chain agents will solve this problem
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