# 大模型在非可验证领域同样进步

- 来源：Ethan Mollick (@emollick)
- 发布时间：2026-07-03 12:16
- AIHOT 分数：43
- AIHOT 链接：https://aihot.virxact.com/items/cmr4fysit01gesll5plyvrpek
- 原文链接：https://x.com/emollick/status/2072897123822010853

## AI 摘要

虽然显然，缺乏可验证领域会使模型训练变得困难……但同样真实的是，模型在非可验证领域也变得越来越好。前沿是参差不齐的，但比我仅从可验证性预期的情况要好得多。

## 正文

While it is obviously true that not having verifiable domains makes training models in those spaces difficult… it is also true that models are also getting much better at non-verifiable domains. The frontier is jagged， but less so than I'd have expected from verifiability alone