Deconstructing AI Frameworks: From Intelligent Agents to Decentralization Exploration

Introduction

The narrative of the combination of AI and cryptocurrency has undergone dramatic changes in just two months. Recently, the market has begun to focus on "framework" projects led by technological narratives, and this niche has already spawned several projects with market capitalizations exceeding one billion, even ten billion. These projects have derived a new asset issuance model: issuing tokens based on a codebase, and creating new tokens again based on the framework. With the framework as the foundation and Agents on top, a unique infrastructure model of the AI era has formed. This article will explore the significance of AI frameworks for the cryptocurrency industry.

1. Framework Introduction

AI frameworks are underlying development tools or platforms that integrate pre-built modules, libraries, and tools to simplify the process of building complex AI models. They can be understood as the operating systems of the AI era. Although "AI frameworks" is an emerging concept in the cryptocurrency field, its development has a history of 14 years. The framework projects that have emerged in the cryptocurrency space are designed to meet the demands of a large number of Agents. Below are introductions to several mainstream frameworks:

1.1 Eliza

Eliza is a multi-Agent simulation framework specifically designed for creating, deploying, and managing autonomous AI Agents. Developed in TypeScript, it has strong compatibility and is easy to integrate with APIs. It is primarily aimed at social media scenarios, supporting multi-platform integration and media content processing.

The currently supported use cases include: AI assistant applications, social media personas, knowledge workers, and interactive roles. Supported models include local inference of open-source models, OpenAI API cloud inference, and more.

1.2 G.A.M.E

G.A.M.E is a multimodal AI framework for automatic generation and management launched by Virtual, primarily designed for intelligent NPCs in games. Low-code and even no-code users can also use it.

The core design is a modular design that allows multiple subsystems to work together, including the Agent prompt interface, perception subsystem, strategic planning engine, and several other modules. It is suitable for gaming and metaverse scenarios.

1.3 Rig

Rig is an open-source tool written in Rust that simplifies the development of applications using large language models. It provides a unified interface and supports multiple LLM service providers and vector databases.

Core features include a unified interface, modular architecture, type safety, and efficient performance. Suitable for building Q&A systems, document search tools, chatbots, and more.

1.4 ZerePy

ZerePy is an open-source framework based on Python, used for deploying and managing AI Agents on the X platform. It provides a command line interface and supports large language models from OpenAI and Anthropic, directly integrating with the X platform API.

2. Similarities with the Development Path of the BTC Ecosystem

The development path of AI Agents is similar to that of the BTC ecosystem, which can be summarized as: GOAT/ACT - Social type Agents/Analytical AI Agents - Framework competition. In the future, infrastructure projects focusing on the decentralization and security of Agents may become the main theme.

The AI framework can be likened to the future public chain, while the Agent can be compared to future Dapps. Future debates may shift from the competition between EVM and heterogeneous chains to a framework competition, with the key issue being how to achieve Decentralization or chainification.

3. The Significance of On-Chain

The combination of blockchain and AI needs to consider its significance. Possible significances include:

1. Achieve lower usage costs, improve accessibility and choice.
2. Provide blockchain-based Agent security solutions
3. Create Unique Blockchain Financial Playstyles
4. Achieve transparent and traceable reasoning, enhancing interoperability.

4. Opportunities in the Creative Economy

AI framework projects may offer entrepreneurial opportunities similar to GPT Store in the future. Frameworks that simplify the agent building process may have advantages, forming a more interesting Web3 creative economy than GPT Store.

Web3 still has many demands to be filled, and community economics can be introduced to make Agents more complete. The creative economy of Agents will provide opportunities for ordinary people to participate, and future AI Memes may be more intelligent and interesting.