AI

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.

Assisterr is a decentralized AI platform that leverages Small Language Models (SLMs) and an innovative economic model to make AI technology more accessible, efficient, and sustainable. The platform addresses the limitations of Large Language Models (LLMs) and promotes community collaboration, allowing users to create, share, and monetize AI models. Its unique decentralized economic system rewards contributors, ensuring fair value distribution, fostering AI adoption, technological innovation, and driving advancements in the field.

At the end of 2024, Solana announced the official launch of the first AI Hackathon, with a total prize pool of more than $185,000 to attract developers to submit projects. So far, in about half a month, more than 400 projects have submitted their works. Which Alphas may emerge from them? This article integrates various types of information and organizes some of the more discussed projects that already have tokens, and summarizes them as follows.

In this article, we’ll explore three major use cases for AI within DeFi and illustrate how each one is poised to transform the way we access and benefit from decentralized financial services.

This article delves into the concept of d/acc, comparing various strategies to analyze its role in addressing risks associated with artificial intelligence. It also discusses the value of cryptocurrencies in this context and explores mechanisms for funding public goods. Finally, it envisions that despite challenges in future technological development, humanity still has the opportunity to leverage existing tools and ideas to build a better world.

This article compares and tests five major AI platforms (ChatGPT, Google Gemini, HuggingChat, Claude, and Mistral AI), evaluating their ease of use and the quality of results in creating AI agents.