做 AI 智能体开发的团队终于有了一个能自我进化的开源框架——SIA 让模型从“冻结工人”变成“持续学习者”，直接提升任务效果，建议研究自优化系统的开发者点开看看。
Hexo AI 发布了开源递归自我改进框架 SIA（Self Improving AI），该框架允许 AI 智能体在完成任务后，不仅改进外部工作流程（如提示词、工具），还能直接更新模型内部权重，实现真正的自我进化。与当前大多数“冻结工人”式智能体不同，SIA 通过反复训练自身任务反馈来积累领域知识，无需人工手动编码策略。实验结果显示，SIA 在 LawBench 上提升 56.6%，GPU 内核运行时减少 91.9%，单细胞 RNA 去噪提升 502%。这一突破为构建持续自优化的 AI 系统提供了新路径。
Big release - Open Source Recursive Self Improveme…
Big release - Open Source Recursive Self Improvement from @hexoai
Shows AI agent can improve both how it works and what it internally knows after seeing its own task results. i.e. by repeatedly training on its own task feedback, not by relying on a human to hand-code every strategy.
Most agents today are frozen workers: you can give them better prompts, better tools, better retry rules, and better code, but the actual model usually stays the same.
SIA (Self Improving AI framework) changes the outer workflow, called the harness, and also changes the model’s weights, which are the internal settings that store learned patterns. which means task feedback changes the model’s internal parameters, pushing it toward domain knowledge.
The paper reports a 56.6% gain on LawBench, 91.9% runtime reduction on GPU kernels, and 502% improvement on single-cell RNA denoising over baseline.
- marktechpost05-29 07:28原文