Keep on to blur preview images; turn off to show them clearly
"If Anyone Builds It, Everyone Dies" seems weak. Yud & Soares wasted an opportunity to make a real, strong case for AI x-risk. They instead continue to make obvious, long-debunked mistakes, like naively counting "possible" AI goals https://t.co/90rd1Kjc4i Disappointing
Research scientist on the scalable alignment team at Google DeepMind. All views are my own.
"If Anyone Builds It, Everyone Dies" seems weak. Yud & Soares wasted an opportunity to make a real, strong case for AI x-risk. They instead continue to make obvious, long-debunked mistakes, like naively counting "possible" AI goals https://t.co/90rd1Kjc4i Disappointing
Research scientist on the scalable alignment team at Google DeepMind. All views are my own.
"If Anyone Builds It, Everyone Dies" seems weak. Yud & Soares wasted an opportunity to make a real, strong case for AI x-risk. They instead continue to make obvious, long-debunked mistakes, like naively counting "possible" AI goals https://t.co/90rd1Kjc4i Disappointing
Research scientist on the scalable alignment team at Google DeepMind. All views are my own.
"If Anyone Builds It, Everyone Dies" seems weak. Yud & Soares wasted an opportunity to make a real, strong case for AI x-risk. They instead continue to make obvious, long-debunked mistakes, like naively counting "possible" AI goals https://t.co/90rd1Kjc4i Disappointing
Research scientist on the scalable alignment team at Google DeepMind. All views are my own.
"If Anyone Builds It, Everyone Dies" seems weak. Yud & Soares wasted an opportunity to make a real, strong case for AI x-risk. They instead continue to make obvious, long-debunked mistakes, like naively counting "possible" AI goals https://t.co/90rd1Kjc4i Disappointing
(It'd be less frustrating if they didn't also have a cult contorting to insist that Y&S are some of the best reasoners who have ever lived and no one has truly found a hole in their arguments)
"If Anyone Builds It, Everyone Dies" seems weak. Yud & Soares wasted an opportunity to make a real, strong case for AI x-risk. They instead continue to make obvious, long-debunked mistakes, like naively counting "possible" AI goals https://t.co/90rd1Kjc4i Disappointing
Research scientist on the scalable alignment team at Google DeepMind. All views are my own.