Analyzing AI Frameworks: From Intelligent Agents to Decentralization Exploration

Introduction

Recently, the narrative of the combination of AI and cryptocurrency has developed rapidly. The market focus has shifted to technology-driven "framework" projects, and this niche track has seen several dark horses with market capitalizations exceeding hundreds of millions and even billions emerge in just a few weeks. These projects have given rise to a new asset issuance model - issuing tokens through GitHub repositories, with Agents built on the framework also able to issue tokens again. 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 Overview

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 system of the AI era. Although "AI frameworks" is a new concept in the cryptocurrency field, its development has a history of nearly 14 years. The framework projects that have emerged in cryptocurrency are designed to meet the demands of a large number of Agents and are expanding into other fields, forming AI frameworks in different niche areas.

1.1 Eliza

Eliza is a multi-Agent simulation framework for creating, deploying, and managing autonomous AI Agents. Developed in TypeScript, it has good compatibility and is easy to integrate with APIs. It is mainly targeted at social media scenarios and supports multi-platform integration.

Use cases supported by Eliza include: AI assistant applications, social media characters, knowledge workers, and interactive roles. Supported models include local inference with open-source models, cloud inference with OpenAI's API, 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. This framework allows users with low-code or even no-code backgrounds to utilize it.

The core design of G.A.M.E is a modular design that works through the collaboration of multiple subsystems, including the Agent prompt interface, perception subsystem, strategic planning engine, and various other components.

1.3 Rig

Rig is an open-source tool written in Rust, designed to simplify the development of large language model applications. It provides a unified operating interface that enables developers to easily interact with multiple LLM service providers and vector databases.

The core features of Rig include a unified interface, modular architecture, type safety, and high performance. It is suitable for building question-answering systems, document search tools, and context-aware chatbots, among others.

1.4 ZerePy

ZerePy is an open-source framework based on Python that simplifies the process of deploying and managing AI Agents on the X platform. It provides a command-line interface, supports multiple LLMs, directly integrates with the X platform API, and features a modular connection system.

Compared to Eliza, ZerePy focuses more on simplifying the process of deploying AI Agents on specific social platforms, leaning towards practical applications.

2. Similarities with the Development Path of the BTC Ecosystem

The development path of AI Agents has similarities with the recent BTC ecosystem. The development of the BTC ecosystem can be summarized as: BRC20 - multi-protocol competition - BTC L2 - BTCFi. AI Agents can be summarized as: GOAT/ACT - Social type Agents/analytical AI Agents - framework competition.

However, AI Agent narratives do not reproduce the historical chain of smart contracts. Existing AI framework projects provide new infrastructure development ideas. Compared to Memecoin Launchpad and inscription protocols, the AI framework resembles a future public chain, while the Agent resembles a future Dapp.

3. The Significance of On-Chain

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

1. Reduce usage costs, improve accessibility and options, allowing ordinary users to participate in AI "rental rights".

2. Provide blockchain-based security solutions to protect the interaction between the Agent and real or virtual wallets.

3. Realize unique blockchain financial gameplay, such as a new investment model based on Agent.

4. Achieve transparent and traceable reasoning to enhance interoperability.

4. Potential of the Creative Economy

AI framework projects may provide entrepreneurial opportunities similar to GPT Store in the future. Frameworks that simplify the agent construction process could gain an advantage, creating a more interesting Web3 creative economy than GPT Store.

Compared to the GPT Store, the Agent creative economy in the Web3 space may be fairer and introduce a community economy that makes Agents more complete. This will be an opportunity for ordinary people to participate, and future AI Memes may be smarter and more interesting than existing Agents.