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Compute

As explained in Introduction to Generative AI, Second Edition

Compute is the computational processing capacity required to train, run, or adapt machine-learning models.

Compute capacity is part of the infrastructure behind AI systems. Building and running them can involve substantial ongoing compute and energy costs, tying access to investment in chips, data centers, and other infrastructure. section 11.5

Costs and revenue

Leading AI providers, including OpenAI, face inference and infrastructure costs that far exceed subscription revenue, relying on funding and strategic partnerships to offset expenses. section 11.5

How Introduction to Generative AI, Second Edition covers it

How deep it goes
Links compute to infrastructure and operating costs, but does not explain how processing capacity works technically.
Examples
Cites AI providers whose inference and infrastructure expenses far exceed subscription revenue.
What you can do after
Evaluate how compute and infrastructure costs shape AI investment and potential affordability.
How it connects
Connects compute with chips, data centers, foundation models, inference, and energy costs.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Introduction to Generative AI, Second Edition. The section links point to the parts of the book it draws on.