What this lesson covers.
This module is one of 42 in the curriculum. Below is the canonical interactive lesson — tabs, cards, and diagrams from the source repo, rendered inside the course shell. An audio narration runs alongside it - the sticky player at the top of the page plays the full Module 17 clip.
If you prefer to read first and play with the demos after, the interactive lesson sits below this section. If you'd rather hear it narrated while you scroll, hit play on the sticky audio bar at the top — or just let it autoplay.
The lesson itself.
The Inference Highway
Generating tokens requires running the entire transformer neural network for every single word. See why native generation is slow, how the KV Cache prevents redundant work, and how Speculative Decoding uses a smaller model to predict the future.
Redundant Computation
State Reuse
Draft & Validate
Further reading.
The canonical references for this module. External links open in a new tab.
What to read next.
Use the pager below to move sequentially through the curriculum, or jump to any module from the course index. Each track has a "Prereq: ↑ foundation" callout so you can backfill anything that wasn't clear.