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AI Agents and Blockchain Integration: The Rise of a New Generation of Decentralized Autonomous Agent Financial Systems
The Integration of AI Agents and Blockchain: The Rise of a New Generation Financial Paradigm
In the future world, AI agents may form a digital symbiotic relationship with humans. These autonomous agents can clarify intentions in conversations based on users' natural language needs, automatically break down tasks, and achieve desired outcomes.
A certain Blockchain project has established an Actor-based asynchronous parallel network, which achieves massive scaling of computational power by reaching consensus only on the transaction order, rather than on the entire computation process of the contract. This design enables the network to support more complex computational tasks, including the operation of AI models.
The computing unit of the project can now access 16GB of memory following the recent update of the WASM virtual machine, which is sufficient to run large language models such as the unquantized version of the Falcon series like Llama 3. Additionally, the project allows users to access network data as if they were accessing a local hard drive and supports interaction between different types of virtual machines in a shared environment, providing more possibilities for future application development.
This system design makes it possible to implement smart contracts that integrate AI agents. By programming within this network, we can create AI agents that make intelligent decisions in the market, where agents may compete against each other or represent humans against humans. In the future, the process of designing and selecting machine learning models and executing automated trading may be more easily automated by AI.
In recent years, the development of decentralized finance (DeFi) has made it possible to execute various financial operations on-chain without relying on centralized entities. However, the core factors that determine market vitality are still the flow of capital and the individuals making financial decisions. As the development of network applications progresses, we may be able to enhance the intelligent decision-making aspect of the market by filtering information, processing data, and combining strategies within the network, integrating the wisdom of AI agents for real-time decision-making, and creating a rich decentralized autonomous agent financial system.
Currently, some projects have begun to realize this vision, including Autonomous Finance (AF), Dexi, and Outcome.
Autonomous Finance
AF focuses on researching and developing financial applications that integrate AI on a certain Blockchain, attempting to bring intelligent decision-making layers on-chain through the construction of AI models and data-driven financial decisions. Its main businesses include core infrastructure, smart agent finance (AgentFi), and content finance (ContentFi).
Core facilities include decentralized exchanges, lending, derivatives, and synthetic asset protocols.
AgentFi primarily executes trading strategies through composable semi-autonomous and fully autonomous agents. These agents utilize on-chain data streams for self-learning, executing investment strategies across various liquidity pools and financial bases within the ecosystem, without the need for off-chain signals or human intervention.
Typical autonomous agents include:
Among them, the DCA agent serves as the basic agent, providing various customizable parameters, such as triggering trades within a specific price range, adjusting trading time intervals, and asset price weighted trading.
Content finance is a framework for attributing and monetizing data stored on the permanent network into composable assets. AF is building applications that allow data contributors or content funds to contribute data to the permanent network, which will serve as on-chain signals for autonomous agents and machine learning.
AF has launched two main products: AO Link and Data OS. AO Link is a message browser for the network, providing features such as message computation, visualization, and real-time message streams. Data OS is a ContentFI protocol that uses autonomous AI agents to acquire content and regenerate content derivatives.
Dexi
Dexi is an important interactive interface for users to participate in Agent Fi using a proxy on the network. It is an application implemented by proxies that can autonomously identify, collect, and aggregate various financial data on the network. This data covers asset prices, token exchanges, liquidity fluctuations, and token asset characteristics. Dexi primarily serves end users and web applications, providing data subscription services.
Outcome
Outcome is a prediction market platform that provides users with the opportunity to bet on various events. Currently, the prediction topics in the market cover fields such as technology, memes, business, gaming, and DeFi. The project plans to allow users to build autonomous agents based on real data and large language models for automated betting in the prediction market in the future.
These innovations provide us with a new perspective to explore the possibilities of directly deploying AI models on the Blockchain and using various AI agents to execute automated trading. We look forward to seeing more application cases that combine AI agents to realize financial strategies, driving the development of a new generation of financial paradigms.