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. ⚙️ 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.
百度发布自动化研究系统 ERNIE Evolve,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被保留,每轮结果指导下一轮。
百度官方给出 ERNIE Evolve 自动改代码跑实验的机制和三项基准数字,适合做机制拆解加数据对比的实测解读。
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