hexoai开源了SIA（自我改进AI）框架。该框架展示了AI智能体不仅能优化其外部工作流（harness），还能通过任务反馈直接更新自身的模型权重，从而在领域知识和能力上实现自主提升，而非仅依赖人类提供的提示或工具改进。论文报告显示，SIA在LawBench基准上性能提升56.6%，在GPU kernels运行上耗时减少91.9%，在单细胞RNA去噪任务中相比基线提升502%。
不再只是给AI换提示词，SIA框架连模型自己的权重都更新了，在三个任务里分别提升了56%、502%和91%加速，开源出来会让整个Agent开发范式重新思考。
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.
Superintelligence will be built on Self Improvement. Today @hexoai, we’re excited to release ‘SIA’ - an open-source Self-Improving AI, to achieve any goal through recursive self improvement. While trying to solve a problem, SIA doesn't just improve it's abilities by updating it's harness, it updates it's own weights as well.在 X 查看被引用的帖子
来源：Rohan Paul · x.com