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Minimax 推出 MaxClaw2 月 26 日，Minimax 团队发文介绍了 MiniMax Agent Expert 的功能升级，以及全新推出的 AI 助手 MaxClaw。MiniMax 在 Expert 2.0 中进一步优化了专家 Agent 的创建体验。用户不需要考虑 Skill、SubAgent、MCP 的配置，以及提示词的结构编排，只需用自然语言描述任务目标或能力需求，Agent 会根据目标完成 SOP 梳理、工具编排与能力配置。
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impact. The grantmaking model is continuously refined.
德國該拿什麼拯救它的汽車工業？2025年2月16日，详情可参考91视频
This is not the only surprise in this article.
Even though my dataset is very small, I think it's sufficient to conclude that LLMs can't consistently reason. Also their reasoning performance gets worse as the SAT instance grows, which may be due to the context window becoming too large as the model reasoning progresses, and it gets harder to remember original clauses at the top of the context. A friend of mine made an observation that how complex SAT instances are similar to working with many rules in large codebases. As we add more rules, it gets more and more likely for LLMs to forget some of them, which can be insidious. Of course that doesn't mean LLMs are useless. They can be definitely useful without being able to reason, but due to lack of reasoning, we can't just write down the rules and expect that LLMs will always follow them. For critical requirements there needs to be some other process in place to ensure that these are met.。业内人士推荐Line官方版本下载作为进阶阅读