A journey through the memory wall, KV caches, batch economics, speculative decoding, and custom silicon — explaining why everything in AI slows down before it gets faster.
The sequel exploring what comes after inference economics — architectures and techniques that reshape how models think.
Practical techniques for shrinking giant AI brains: compression, mixture of experts, pruning, merging, and recovery training.
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