Building Brains on a Computer

kept by eddie jan 27

Recent advances in expansion microscopy, protein barcoding, and AI-based connectomics make full human brain emulation plausible within decades, but require massive data acquisition and compute.

How LLMs Distort Our Written Language
LLMs distort written language by shifting semantics, altering conclusions, and removing personal voice, even when instructed to make minimal edits.
also on UC Berkeley, #ai-research
Thinking through how pretraining vs RL learn
Reinforcement learning provides far fewer bits per FLOP than pretraining until models achieve high pass rates, limiting RLVR's ability to learn new capabilities.
also on #scaling-laws, #research
Yes, AGI Can Happen - A Computational Perspective
Contra Tim Dettmers, Dan Fu argues current AI systems significantly underutilize hardware, models lag hardware buildout, and multiple paths exist to useful AGI.
also on #scaling-laws, #ai-research, #hardware