AI

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.

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.

In recent years, the rapid advancement of generative AI has introduced new demands on infrastructure and workflows, particularly in validation and evaluation. The reliability of AI applications is closely tied to user trust, and Mira is dedicated to addressing this core issue through a decentralized network, setting new industry standards for AI validation and evaluation.

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.

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.

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.

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.

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.

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.

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 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.

This article delves into the role of AI agents in the digital economy, analyzing the three major waves of agent evolution. It explains the development trends and potential value of the agentic economy, and introduces the "Decentralized AI" stacking framework proposed by Delphi Digital, providing investors with clear directions and references.

This article explores the concept of combining DeFi with AI, known as DeFAI, which aims to simplify DeFi operations, optimise trading strategies, and increase profits through artificial intelligence. It also introduces several DeFAI projects, including Griffain, Hey Anon, Mode, and more.

This article offers a comprehensive overview of AI Agents, examining their development stages and integration with cryptocurrency. It compares AI Agents with traditional large language models, highlighting their key advantages and unique features in decentralization, incentive mechanisms, and sustainability. The article traces the evolution from infrastructure to real-world applications, and presents an overview of leading AI Agent projects and framework standards. Readers will gain a clear understanding of the AI Agent landscape through this beginner-friendly guide.

A detailed overview of AIXBT's role as a KOL, financial performance, tech stack, tokenomics, and future development direction.