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A decision theorist and researcher at the Machine Intelligence Research Institute, Yudkowsky published earlier drafts of his writings to the websites Overcoming Bias and Less Wrong. Rationality: From AI to Zombies compiles six volumes of Yudkowsky's essays into a single audiobook. Collectively, these sequences of linked essays serve as a rich ...
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Mar 17, 2016 · Eliezer Yudkowsky is a decision theorist and computer scientist at the Machine Intelligence Research Institute in Berkeley, California who is known for his work in technological forecasting. His publications include the Cambridge Handbook of Artificial Intelligence chapter “The Ethics of Artificial Intelligence,” co-authored with Nick Bostrom.
- Eliezer Yudkowsky
Mar 31, 2023 · Los Alamos National Laboratory photo. ... In an op-ed for TIME, AI theorist Eliezer Yudkowsky said that pausing research into AI isn’t enough. Yudkowsky said that the world must be willing to ...
Dec 13, 2018 · In How to Actually Change Your Mind, decision theorist Eliezer Yudkowsky asks how we can better identify and sort out our biases, integrate new evidence, and achieve lucidity in our daily lives. Because it really seems as though we should be able to do better—. —and a three-pound all-purpose superweapon is a terrible thing to waste.
- Eliezer Yudkowsky
May 8, 2023 · This was a difficult listen. Eliezer Yudkowsky has developed a dense jargon for describing issues around AI safety and alignment. He seems to find the jargon useful, but few people outside the rationalist/LessWrong community would understand it — I say this as a PhD student working in machine learning who was vaguely aware of Yudkowsky’s ideas prior to this episode.
Jun 14, 2020 · 409 Followers. intelligence.org lesswrong.com. Read writing from Eliezer Yudkowsky on Medium. Writing about things of no ultimate importance. If it was important it'd be on intelligence.org or lesswrong.com.
In Mamba, you basically learn a time varying A and B. The parameterization is a bit wonky here, because of historical reasons, but it goes something like: A_t is exp (-\delta (x_t) * exp (A)), B_t = \delta (x_t) B x_t, where \delta (x_t) = softplus ( W_\delta x_t). Also note that in Mamba, they also constrain A to be diagonal and W_\delta to be ...
