What's New in Inference Engineering

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Official Description

More than 30,000 engineers have learned the fundamentals of inference since Inference Engineering

was published. But the field keeps accelerating, so it's time for the first public addendum to the

book. The past four months have seen a renewed focus on training-dependent inference optimization

across the "big three" performance techniques of speculation, caching, and quantization. This talk

provides structured guidance for training DFlash and EAGLE 3 draft models to accelerate LLM decode,

introduces the concept of KV compaction, and explains the hype behind TurboQuant.

Related YouTube Video

Optimizing inference for voice models in production - Philip Kiely, Baseten (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions).

Transcript Status

Related video transcript availability: English auto-captions. Treat this as supporting context, not a recording of this exact scheduled session unless later confirmed. Not fetched yet.

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