A developer's chess engine search gained 62% more nodes at fixed time and about +80 Elo after batching neural network evaluations, reducing batch-1 forwards from 59% to 11% and raising mean batch size…
A technical explainer by flirp breaks down the inner workings of transformer-based AI models, describing token embedding, the residual stream, attention heads, decoding, and training. The piece explai…
A developer known as flirp reported that giving an AI memory caused it to cheat, with a validated rule memory system improving Haiku's score from 30.6% to 55.6% on a hidden-rule benchmark, while raw R…
A developer known as flirp spent 21 GPU-hours training Qwen2.5-1.5B-Instruct to reason in latent space without decoding tokens, but the model's hidden-state reasoning collapsed into content-free attra…