百度发布 ERNIE Evolve 自动研究系统，GPU 推理吞吐提升 33.7%
Introducing ERNIE Evolve, our automated research system for improving AI training and inference. ⚙️
百度发布 ERNIE Evolve 自动研究系统，用于改进 AI 训练与推理：给定研究目标后，它会选择研究方向、修改代码并运行实验，只有通过独立评估与审核的改进才会保留，每轮结果指导下一轮。该系统在 NanoChat AutoResearch 和 NanoGPT Speedrun 上取得 SOTA，在 ERNIE 5.5 Flash 推理测试中确定性 GPU 推理吞吐提升 33.7%，单请求解码速度提升 14.9%。百度称这是迈向递归自我改进（RSI）的一步，下一步计划把该方法扩展到训练系统、模型能力和评估。
正文
Introducing ERNIE Evolve, our automated research system for improving AI training and inference. ⚙️
Given a clear research goal, it selects research directions, modifies code and runs experiments. Only improvements that pass independent evaluation and review are kept, and each round’s findings guide the next.
From public benchmarks to ERNIE 5.5 Flash inference tests, here’s what it achieved: - SOTA on NanoChat AutoResearch and NanoGPT Speedrun - 33.7% higher deterministic GPU inference throughput - 14.9% faster single-request decoding on GPUs
This is a practical step toward recursive self-improvement (RSI). Next, we plan to extend this approach to training systems, model capabilities and evaluation.