may not be entirely original and could be influenced by the training data.
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1L nanoGPT, d=4, 2h
Finding these optimization opportunities can itself be a significant undertaking. It requires end-to-end understanding of the spec to identify which behaviors are observable and which can safely be elided. Even then, whether a given optimization is actually spec-compliant is often unclear. Implementers must make judgment calls about which semantics they can relax without breaking compatibility. This puts enormous pressure on runtime teams to become spec experts just to achieve acceptable performance.