NewCost and speed
Speeding up language models for travel applications
Our short summary of Amazon’s engineering write-up. The full story, with all the detail, is on their blog.
Read the full write-up on amazon.science (opens in a new tab)Problem
Large language models were too slow and expensive for travel site queries, hurting user experience and revenue.
Solution
They trained a smaller model using knowledge distillation and added Medusa heads to predict several tokens at once, cutting cost and latency dramatically.
Cost under one‑third, up to 20× faster
Research behind this, on AI Papers DailyDForkTree: Accelerating Speculative Decoding with Fork-Aware Block Diffusion Draft Trees
Want the architecture, code and numbers? They’re in the original post.
Read the full write-up on amazon.science (opens in a new tab)