AI

This article delves into the development trends and investment logic within the AI Agent field, with a particular focus on analyzing framework-based projects in detail. It introduces the basic concepts and functionalities of AI frameworks, and demonstrates their performance and potential across different application scenarios through specific case studies such as Eliza, G.A.M.E, Rig, and ZerePy. Additionally, from technical, market, and investment perspectives, the article compares the similarities between AI Agents and the BTC ecosystem, exploring the significance of bringing AI Agents onto the blockchain and the potential innovations this may bring in the future.

AIXBT is an innovative AI-driven cryptocurrency intelligence platform developed by Virtuals Protocol on the Base chain. Integrating multiple data sources and utilizing advanced narrative detection and Alpha-focus analysis provides users with real-time market insights and optimized trading strategies. The platform supports intelligent trading analysis and interacts with blockchains to execute smart contracts and manage investment portfolios. Since its launch in November 2024, AIXBT has demonstrated remarkable growth potential, with its market cap surpassing $250 million within two weeks and gaining over 100,000 followers on the X platform. Users holding more than 600,000 $AIXBT can access more precise market analysis through the official platform.

In October, TEE frequently appeared on X posts, drawing attention from the Web3 community. This article outlines the concept of TEE, its applications in Web3, its limitations, and future development prospects.

This article delves into the practical applications and potential value of the integration between Web3 and AI, demonstrating how this combination can bring innovation and transformation in sectors like finance, art, and healthcare. It analyzes how Web3's token mechanisms and privacy protections provide AI with real and diversified data, and discusses how this combination grants new agency in data flow and pricing for individuals and groups.

This article organizes 22 non-AI crypto projects that lay out AI Agent frameworks, covering various sectors such as gaming, public chains, payments, DeFi, and DePIN. These projects primarily accelerate the construction and development of the AI Agent ecosystem through technical frameworks and the implementation of use cases.

AI Agent is a hot topic in the field of artificial intelligence in 2025, but many people still misunderstand its definition. AI Agent projects need to have three core capabilities of perception, thinking, and action, and solve problems in logical steps. This article visually demonstrates the working principle of AI Agent through the case of automatic investment in cryptocurrency, from reading news to executing buying and selling operations, revealing its actual value in real-world applications.

The article provides a detailed overview of market leaders Virtuals and Ai16z, exploring their project backgrounds, core strengths, and future potential. It also analyzes other promising competitors like ZereBro, ARC, and Griffain.

The article provides an in-depth exploration of the application prospects of AI Agents in fields such as healthcare, autonomous driving, and finance. It highlights the advantages of using smart contracts as behavioral guidelines, emphasizing features like decentralization, immutability, and traceability. At the same time, the author objectively analyzes the challenges faced by this technological combination, including security issues, scalability limitations, ethical responsibility, and privacy controversies, while warning about the potential to exacerbate social inequality.

DeFAI (DeFi + AI) takes DeFi and makes it accessible. By leveraging AI, it simplifies complex interfaces and removes the friction that stops everyday people from participating.

Discussions about AI Agent framework standards often evoke mixed feelings—viewed both as potential breakthroughs and significant risks. Frameworks in this sector have the potential to rapidly appreciate, possibly reaching revenues of $300 million swiftly. However, if they fail to deliver on their promises, the loss of consensus can lead to dramatic declines. This article explores why AI Agent framework standards have become a critical competitive field and offers insights on evaluating their investment potential.

This article explores the concept, development history, classifications, key innovations, and challenges faced by AI agents in cryptocurrency. Through case studies of each classification, it helps users quickly grasp the opportunities AI agents present in the crypto industry.

This article focuses on the integration of AI and blockchain, exploring the current state and trends in the AI agent domain. AI agents are evolving through five key areas: frameworks and launch platforms, DeFI (decentralized finance), entertainment and gaming, decentralized organizations, and economic agency.

With the recent security incidents of Spectral and previous security audits of memecoin launchpads such as Tokr.fun, Pumpup, and Pump404, we will provide an in-depth analysis of Virtuals protocol and Clanker's core mechanisms and a detailed interpretation of its functional design, including token minting, fee models, liquidity and other key features, while helping users understand their security points.

This article delves into the key strategies for achieving market capitalization growth in the crypto space, and emphasizes the importance of launching projects early. The article analyzes the advantages of early launches, such as validating ideas, establishing a leading position, and forming community effects, and points out that product building is not the only determining factor; team background and community building are equally important.

This article delves into the four major frameworks in the Crypto x AI domain: Eliza ($AI16Z), GAME ($VIRTUAL), Rig ($ARC), and ZerePy ($ZEREBRO). It analyzes their technical characteristics, market positioning, and industrial impact. The article provides a detailed comparison of these frameworks' usability, scalability, adaptability, and performance, exploring their potential and limitations in various application scenarios.