Geoff Hinton: On Radiology

推荐理由

Thanks for pointing to that clip. Hadn't seen that

引用sndean · 原文2017年5月

说明

这是2016年由Creative Destruction Lab发布的一部评论，主题归在AI safety, AGI & impact。它讲的是ai prediction failures这一支里的具体问题，而不是把整个领域扫一遍。适合按兴趣直接看、不打算先补课的人。内容上可以概括成：A one-minute clip from a 2016 Toronto conference in which Geoff Hinton comments on deep learning and radiology. He suggests radiologists should stop being trained because machines would soon read scans better.这些读者给出的理由，核心是：HN uses it as a famous example of an overconfident AI prediction that turned out wrong, since radiologists remain in demand.它贴着当时的技术，看的时候要记得那是那个年份的判断。从2017年到2026年，有0位不同的读者在0个不同月份把它推荐出来，其中明确叫别人去看的有0次。适合已经知道原事件、想听一种解读的人。把它当成观点，而不是教科书。如果已经会了基本定义，就把注意力放在它怎么把ai prediction failures变成能跟着复述的例子。

视频信息

频道

Creative Destruction Lab

时长

1 分 25 秒

发布年份

2016

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