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About Latent Heat
Latent Heat is a single-editor technical publication established in 2026 that focuses on experiments with small machine learning models running on ordinary consumer hardware. The site publishes a chronological log of research notes covering topics such as transformer architectures, model interpretability, search algorithms, training techniques, and chess engine development. Several entries document attempts to build or compress small chess-playing models, benchmark them against engines like Stockfish, and test approaches such as distillation and concept injection. The publication explicitly includes negative and inconclusive results alongside positive findings, and categorizes posts with tags like "negative-result," "small-models," and "evaluation."
- Website
- latentheat.dev
- Categories
- Research
