@TheAhmadOsman: Inference Engineering simply is - Encodings that can be loaded - Operations on said encodings implemented by backends -…
Summary
A tweet explains the core components of inference engineering: loadable encodings, backend operations, and native hardware arithmetic, with a discussion on kernels and GPU efficiency.
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Cached at: 09/19/26, 11:08 PM
Inference Engineering simply is
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Encodings that can be loaded
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Operations on said encodings implemented by backends
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Arithmetics executed natively by hardware via the operations above
Those 3 things combined pay top $$$ nowadays btw
Ahmad (@TheAhmadOsman): Kernels implement specific tensor programs, not models
Model semantics → shapes → kernels → instructions → runtime → silicon
Your GPU behaves like a very expensive space heater without these things handled well
From my upcoming article on Kernels, Hardware, and Models
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