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AI 金句日刊 Vol.49:当 AI 开始自己解决问题

三条近期公开观点,从重新发明解法、委托复杂工作到提前应对 AI 失配风险。

三条来自 X 的近期公开观点,分别谈重新发明解法、把复杂任务交给 AI,以及为什么安全不能等到事故发生之后。

01|已有解法,不代表没有新路

François Chollet 在 2026 年 7 月 26 日的公开帖中提醒,人们很容易把已有解法误认为唯一且最优的解法。1
Most people are conditioned to expect that all known problems already have canonical solutions, that these solutions are the best that can be achieved, and that attempting to reinvent them would be a pointless, quixotic effort.
In reality, everything out there was made by people no smarter than you, often idiots stumbling in the dark. Not only can new solutions be found, but entirely new paradigms are absolutely possible, including ones that completely bypass the current tech tree.
这条观点放在 AI 语境里,指向的不是盲目推翻工程积累,而是对「陌生问题」保留重新定义问题和绕开既有路径的能力。
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02|ChatGPT 不再只是对话

Sam Altman 在 2026 年 7 月 26 日描述了一次 ChatGPT Work 的使用体验:他从手机发出一个跨越历史记录、旅行规划、建站、群体协作和预约的请求,并写道:2
chatgpt work is remarkable, and "work" undersells it.
from my phone i sent:
"use all my chat history to figure out ideas for a long weekend trip with 8 friends, plan the best three options, make a full-stack site where the 9 of us can coordinate on what we would want to do in each place and decide where to go, and then after we get to group agreement make reservations. draft an email in my gmail i can send out to my friends when the site is ready."
it...just worked.
这里的关键变化,不是「回答得更像人」,而是一次请求开始横跨记忆、规划、软件构建与现实执行;聊天框只是入口。
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03|失配不能拖到事后

Yoshua Bengio 在 2026 年 7 月 22 日回应一则相关报道时,警告 AI agent 为了完成失配目标而欺骗、作弊的行为,已经不能只被当作受控测试里的抽象风险。3
This incident is deeply concerning. AI agents are willing to cheat and deceive to achieve misaligned and unintended goals, behaviours which have been demonstrated in controlled tests for months. Now, this real-world case should serve as a wake-up call.
Continuing on the current trajectory of AI development will likely lead to an increase in concrete cases of autonomous cyberattacks as well as other high-risk incidents of misaligned and dangerous AI behaviour. We urgently need to take action to prevent these situations, rather than attempting to clean up the damage after the fact.
当系统开始自己规划和执行,能力增长与安全约束就不再是两条可以分开排期的路线:目标失配越早被发现,代价才越可能停留在测试阶段。
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