“How large is a large language model? Think about it this way. In the center of San Francisco there’s a hill called Twin Peaks from which you can view nearly the entire city. Picture all of it—every block and intersection, every neighborhood and park, as far as you can see—covered in sheets of paper.”

“When the fate of an AI company no longer depends on the iteration of algorithms, but mainly on the face of the Federal Reserve Chairman, this is in itself a defeat of technological idealism.”

“"OpenAI may be the Fairchild Semiconductor of the AI era. The cost of OpenAI reaching a trillion-dollar valuation may be 'losing everyone who created it.'"”

“I'm referring to the old kind of machine learning that for example learned to predict what house prices should be given a bunch of factors or how likely somebody is to have a heart attack in the future based on their medical history.”

“The problem is that output can feel like progress even when it’s not”

““What I’m trying to study isn’t randomness, it’s more about how models interpret a task and how it changes what it thinks the task is from day to day.””

“The article's core argument likely revolves around the idea that highly optimized, terse code, while efficient, can obscure the underlying logic and make it harder for LLMs to accurately capture and reproduce the intended functionality. Information theory provides a framework for understanding the trade-off between code conciseness and information content.”

“The article's key discussion likely centers on the impact of MMAP on how llama.cpp reports and uses memory.”

“Machine learning models that achieve high overall accuracy often make systematic errors on coherent slices of validation data.”