AI模型

“煽风点火”让大模型“卷”起来的提升性能的套路

作者

近日，一名网友分享了一种通过巧妙利用不同AI模型之间的‘竞争’心理来提升AI输出效果的方法，具体步骤包括：选择任务→交给第一个AI（如ChatGPT）→将结果复制粘贴给第二个AI（如Claude），并要求其改进表现→再继续挑战第三个AI（如Grok）。这种方法已经得到了很多网友的验证和认可。

首篇MCP技术生态全面综述：核心组件、工作流程、生命周期

作者

Model Context Protocol (MCP) is a standardized interface aimed at achieving seamless interaction between AI models and external tools and resources, breaking down data silos and enhancing interoperability across different systems. MCP’s core components include the MCP host, client, and server, working together to enable secure and efficient communication with AI applications and external data sources. It covers lifecycle stages like creation, operation, and updates of MCP servers, along with an ecosystem including key adopters such as Anthropic, OpenAI, and community-driven platforms. This protocol also discusses security threats at each stage and proposed mitigation strategies.