The What, Why, and How of Tokenisation in Machine Learning

I enjoyed chapter 7 on finetuning. It jams a lot of detail into the 50 pages she takes to explain things. Some areas had more detail than you’d expect, and others less, but overall this was a solid summary / review. Core Narrative: Fine-tuning represents a significant technical and organisational investment that should be approached as a last...

This chapter was all about RAG and agents. It’s only 50 pages, so clearly there’s only so much of the details she can get into, but it was pretty good nonetheless and there were a few things in here I’d never really read. Also Chip does a good job bringing the RAG story into the story about agents, particularly in terms of how she defines agents....

This chapter represents a crucial bridge between academic research and production engineering practice in AI system evaluation. What sets it apart is the Chip’s very balanced perspective - neither succumbing to the prevalent hype in the field nor becoming overly academic. Instead, she melds together practical insights with theoretical...

Really enjoyed this chapter. My tidied notes from my readings follow below. 150 pages in and we’re starting to get to the good stuff :) Overview and Context This chapter serves as the first of two chapters (Chapters 3 and 4) dealing with evaluation in AI Engineering. While Chapter 4 will delve into evaluation within systems, Chapter 3 addresses...

Had the first of a series of meet-ups I’m organising in which we discuss Chip Huyen’s new book. My notes from reading the chapter follow this, and then I’ll try to summarise what we discussed in the group. At a high-level, I really enjoyed the final part of the chapter where she got into how she was thinking about the practice of ‘AI Engineering’...