Data and computers
Behind every model there is data, mathematics, software and physical computers.
The chapter at a glance
Collecting data
Training on chips in data centres
A model with parameters
Use: tokens in the context window
An app with tools and rules
Monitoring and maintenance
In this chapter
- 1What is data for AI?Data is the examples or measurements a model learns from or draws its answers from.
- 2Algorithm, model and app: what is the difference?These three words are often mixed up, but they describe different things.
- 3Parameters, tokens and contextThree terms that help you understand what a model stores and what it sees during a conversation.
- 4Chips, data centres and energyAI runs on physical infrastructure: chips, memory, electricity and networks.
- 5Training a model versus using itAn important distinction: a model is first built, then put to use.
- 6What is synthetic data?Synthetic data is generated by a computer instead of every example being measured directly in the real world.
- 7What happens once a model goes live?Deploying a model is the start of its working life, not the end of the work.