Baidu ERNIE Discloses RSI Progress for the First Time; ERNIE Evolve Has Been Used in ERNIE 5.5 Flash R&D
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Baidu ERNIE discloses RSI progress for the first time, unveiling the automated research system ERNIE Evolve that participated in the R&D of ERNIE 5.5 Flash. The system can autonomously propose research directions, conduct experiments, verify results, and accumulate experience. On the three evaluation metrics across the two tasks NanoChat AutoResearch and NanoGPT Speedrun, ERNIE Evolve achieved the current publicly verified SOTA performance, and has already been used for inference optimization of ERNIE 5.5 Flash, including performance optimization for low-latency scenarios on Kunlunxin P800, deterministic inference throughput optimization, and extreme decoding speed optimization. Baidu open-sourced ERNIE 5.5 Flash Base on November 5, and a person close to Baidu revealed that the new ERNIE model may be released soon.
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Baidu publicly discloses for the first time the R&D loop of its automated research system ERNIE Evolve, and presents its publicly verified results on two tasks.
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11月9日，百度文心首次披露 RSI 最新进展，公布参与文心 5.5 Flash 研发的自动研究系统 ERNIE Evolve，其能够围绕目标与约束，自主提出研究方向、开展实验、验证结果并积累经验，既可以持续优化已有路径，也能根据实际效果探索新方向。在 NanoChat AutoResearch 和 NanoGPT Speedrun 两项任务的三个评测指标上，均取得了目前公开验证的 SOTA 表现。目前，ERNIE Evolve 已应用于即将发布的文心 5.5 Flash 推理优化，包括昆仑芯 P800 低时延场景的性能优化、确定性推理吞吐优化及极致解码速度优化。
文心技术博客指出，推理基础设施优化是 RSI 在真实研发中的第一个落点。未来，同样的研究闭环将逐步延伸至训练系统优化、模型能力研究和评测体系迭代，推动 AI 自主发现问题、提出假设、设计实验并验证结果。扩展过程将在明确的目标、权限和资源边界内进行，并接受持续的安全评估与人工监督。
11月5日，百度已正式开源最新基座模型文心 5.5 Flash Base，该模型在知识、推理、数学、代码、多语言和长上下文等多个基准测试中取得同尺寸模型 SOTA 表现。接近百度人士透露，文心新模型或将于近期发布。
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