Neural networks are legible without sparse autoencoders
New analysis suggests polysemanticity stems from architectural limits, not superposition, making modern models directly interpretable.
Results for “model transparency”
Daily coverage of AI, developer tools and infrastructure. Each story explains what happened and why it matters, with a link to the original source.
