哈萨比斯和大卫·西尔弗有一个执念，他们一开始就认为，通向AGI之路一定是强化学习，未来的AGI一定是一个单一的模型。所以他们这种执念，导致了他们的成功，最起码在游戏的领域。成功的原因我觉得很简单，因为游戏是一个规则相对明晰、边界相对清晰，奖励机制非常清晰，你可以用这种强化学习、试错、反馈机制，快速地优化。强化学习威力最大的这方面，可以发挥得淋漓尽致。
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Poor software quality already costs the U.S. economy $2.41 trillion per year, according to a 2022 study by the Consortium for Information & Software Quality. That number was calculated before AI began writing a quarter or more of new code at leading companies. Chris Lattner, the creator of LLVM and Clang, put it bluntly: AI amplifies both good and bad structure. Bad code at AI speed becomes “incomprehensible nightmares.” As AI generates an increasing share of the world’s critical infrastructure (financial systems, medical devices, defense, transportation), unverified code becomes a systemic risk, not just a quality problem.，推荐阅读下载安装 谷歌浏览器 开启极速安全的 上网之旅。获取更多信息
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