AI数学证明成本高昂且难以验证
问题概述
本文报道的AI模型在8000个数学问题上仅解出~5%，每解出一个问题需约60小时compute成本，约$810。读者发现AI生成的证明内容混乱、难以阅读，迫使人类花费大量时间验证。同时，依赖Lean等形式化验证可能无法确保自然语言论证的有效性，造成信任缺口。
痛点标签
- 单次尝试仅解出~5%长期数学问题，每解出一个问题需约60小时compute成本，单次成本约$810
- AI生成的数学证明内容混乱、不清晰，阅读需额外AI辅助，增加了人类理解负担
- 人类需花费大量时间阅读和验证AI生成的代码/证明，工作乏味、 barely-credited 且缺乏乐趣
- Lean等形式化验证可能代码正确，但无法保证自然语言论证的有效性，用户难以信任结果
- 自动形式化在验证数学文本时存在局限，对原始自然语言论证的置信度降低
待验证问题
- 实际的token使用量和compute成本与文中估算相比如何？
- 目前的autoformalization流程（如Lean验证）在实际中是否能有效解决自然语言证明可信度的问题？
- 对于典型的软件工程团队，引入AI生成的数学/代码证明是否具有实际的效率提升，还是主要增加了验证负担？
证据
原话
apparently they tried the model on about 8,000 problems. So, right now it “merely” solves ~5% of the longstanding open mathematical problems that it’s asked about, the problems that whole communities have spent years on, after a single 3-hour attempt on them
原话
It feels like something written by someone who’s on psychedelics. So much unclear and doesn’t make sense.
原话
The "OpenAI model" sets up a crazy race among humans to digest and explain a messy AI proof (work that could easily be some combination of thankless, barely-credited, competitive, and unfun)
原话
But it also appears that no human has understood just about any of these proofs yet. Has anyone verified any of the proofs produced by OpenAI or is everyone just assuming that it just be true because the Lean code checks out?
免责声明：本卡片由 AI 从社区讨论中提炼，属于「痛点证据」，是需求分析与验证的起点，不等同于「已验证的市场需求」。AI 存在分析局限，关键决策前请打开上方原始讨论人工复核。