Noam Brown：谈大模型在科研问题上的能力门槛
中文全文 · AI 翻译
大语言模型已经跨越了一个重要的门槛：在某些研究问题上超越了顶尖人类专家。能力多年来一直在稳步提升，但在科学发现中，一个模型刚好低于顶尖人类表现水平与刚好高于它的表现之间存在巨大差异。这有助于解释为什么数学结果的激增感觉如此突然。
大语言模型的能力仍然参差不齐，它们在许多方面仍不如人类。但随着模型持续改进，我预计其他领域的突破将接踵而至，从而开启科学发现的新时代。
对照原文
LLMs have crossed an important threshold: surpassing top human experts on some research problems. Capabilities have been steadily improving for years, but in scientific discovery there is a big difference between a model just below top human performance and one just above it. That helps explain why the surge in math results feels so sudden. LLM capabilities remain jagged, and there are many ways they are still worse than humans. But as models continue to improve, I expect breakthroughs in other domains to follow, leading to a new era of scientific discovery.