How 3 Turing Awardees Republished Key Methods and Ideas Whose Creators They Failed to Credit
Whose Creators They Failed to Credit
Source: people.idsia.ch
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Why the Original Transformer Figure Is Wrong, and Some Other Interesting Historical Tidbits About LLMs
A few months ago, I shared the article, Understanding Large Language Models: A Cross-Section of the Most Relevant Literature To Get Up to Speed, and the positive feedback was very motivating! So, I also added a few papers here and there to keep the list fresh and relevant.
Juergen Schmidhuber Substack Notesor Dynamic Recurrent Neural Networks Understanding Large Language Models Layer Normalization Transformer Architecture
Source: sebastianraschka.com
LeCun's 2022 paper on autonomous machine intelligence rehashes but does not cite essential work of 1990-2015
1990: gradient descent learns subgoals. 1991: multiple time scales and levels of abstraction. 1997: world models learn predictable abstract representations...
Source: people.idsia.ch