研究者用Claude Code发现AI缩放算法，计算量减少70%
Researchers let Claude Code discover AI scaling algorithms that humans probably wouldn't have designed
AI自己设计算法，省钱又高效
来自马里兰大学、Google、Meta等机构的研究者使用AutoTTS框架，让Claude Code自主发现AI推理控制算法。
该算法相比标准自一致性方法，在保持相同准确率的同时，计算量减少约70%。整个搜索过程仅花费40美元，耗时160分钟。
Researchers let Claude Code discover AI scaling algorithms that humans probably wouldn't have designed
Researchers from UMD, Google, Meta, and other institutions use AutoTTS to let a coding agent independently discover control algorithms for AI reasoning. The algorithm it found cuts compute by about 70 percent compared to standard self-consistency while matching its accuracy. The whole search cost $40 and took 160 minutes. The article Researchers let Claude Code discover AI scaling algorithms that humans probably wouldn't have designed appeared first on The Decoder .
This report is categorized under AITOP's "Papers" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows. Key entities and technical topics under continuous tracking include 智能体, 推理模型, 大模型, AutoTTS.
Source attribution: curated from Decoder (@Jonathan Kemper).
