Aran 用 Codex 自动探索未解猜想 8 小时就看到了可发表进展，做自动推理或数学研究的开发者值得关注——这暗示了 AI 在数学前沿的潜力被严重低估，建议试试 Codex /goal 在自己的领域跑一跑。
Aran Komatsuzaki 使用 Codex 的 /goal 命令，自动探索一些 20-50 年历史的未解猜想，运行 8 小时后已看到可发表的进展。他认为人们高估了“开放数十年”作为重要性的指标，很多旧问题只是无聊但难，而非真正重要。他主张加速近期研究方向，因为社区有共识和品味，而旧问题参与者少、门槛高。他的更强观点是：当前模型已能 95% 自动化地推动前沿，但领域人士保守、AI 人士不了解深层问题，导致这一能力被低估。
i was playing with Codex /goal on some lesser-know…
i was playing with Codex /goal on some lesser-known open conjectures, mostly 20–50y old. after letting it run autonomously for 8h+, i was already seeing what looked like publishable progress, even if not full resolutions.
weakly held take: people overrate “open for decades” as a proxy for importance.
unsolved ≠ important. a lot of old problems are just boring-but-hard, or maybe hard in the bad way / structurally not that productive. imo the higher-value thing is often accelerating recent research directions where the community actually has live taste / consensus that the topic matters.
these aren’t necessarily “harder” in some intrinsic sense. there are just way fewer participants because the prerequisite stack is brutal, vs more approachable combinatorics / Erdős-style problems. so the marginal AI researcher there may be much higher-value than grinding on random half-century-old open problems.
my stronger take: current models can already push some frontiers forward rapidly 95%-automatically, not “solve smooth 4D Poincaré today,” but real progress.
it’s underpriced because the domain people are conservative or slow to retool around AI, and the AI people mostly don’t know which deep problems exist / matter.