• LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.
• attention — The mechanism that lets a model weigh which earlier words matter for the word it's currently processing — the core operation of a transformer.
• inference — Running a trained model to get answers — the phase where AI is actually used, as opposed to trained.

Temperature 0 is not deterministic because kernels change reduction strategy with batch size, not because GPUs are parallel. Batch-invariant kernels make inference bitwise reproducible and collapse the train/inference gap in on-policy RL.

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