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You are here		www.lesswrong.com New Scaling Laws for Large Language Models - LessWrong
\|	\|	blog.moonglow.ai Three Kuhnian Revolutions in ML Training	2.5 parsecs away Travel
\|	\|	Parameters and data. These are the two ingredients of training ML models. The total amount of computation ("compute") you need to do to train a model is proportional to the number of parameters multiplied by the amount of data (measured in "tokens"). Four years ago, it was well-known that if	2.5 parsecs away Travel
\|	\|	codeincomplete.com AI, ML, and Large Language Models \| Jake Gordon	2.5 parsecs away Travel
\|	\|	Personal Website for Jake Gordon	2.5 parsecs away Travel
\|	\|	deepmind.google An empirical analysis of compute-optimal large language model training - Google DeepMind	1.2 parsecs away Travel
\|	\|	We ask the question: "What is the optimal model size and number of training tokens for a given compute budget?" To answer this question, we train models of various sizes and with various numbers...	1.2 parsecs away Travel
\|	\|	emanueleferonato.com Stencyl complete Concentration game \| Emanuele Feronato	12.6 parsecs away Travel
\|		[AI summary] A programmer shares a tutorial on creating a Concentration game prototype using Stencyl and encourages readers to download the source code and check their high scores.	12.6 parsecs away Travel