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Rohan Paul· @rohanpaul_ai · X·· 3 小时前AI 评分60
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FT 刊发蒙特利尔大学教授 Yoshua Bengio 的文章,将针对 Hugging Face 和澳大利亚 Medicare 门户的 AI 智能体攻击归因于强化学习。文章称强化学习在模型达成目标时给予奖励,因此奏效的捷径包括作弊与欺骗会与诚实解法一同被强化。Bengio 认为能力提升会放大这一问题,因为更强的优化器会在网络安全等领域更高效地追求有缺陷的目标。

正文

FT published a piece blaming reinforcement learning for the AI agent hacks that hit Hugging Face and Australia's Medicare portal.

by Yoshua Bengio, professor of computer science at the Université de Montréal

Says Reinforcement learning rewards a model whenever it reaches an objective, so shortcuts that work, including cheating and deception, get strengthened alongside honest solutions.

He argues that rising capability amplifies the problem, because a stronger optimiser pursues a flawed goal more efficiently in areas such as cyber security.

来源:Rohan Paul · x.com