# Compute

> The processing power used to train and run AI systems, usually measured in calculations performed.

Source: https://www.superintelligence.com.au/glossary/compute/

In AI, compute means the amount of calculation a system needs, and the hardware that does it. Training a large model involves an enormous number of arithmetic steps carried out on specialised chips in large data centres. The more compute a training run uses, the more it costs in chips, electricity and time.

Compute matters because it has been one of the main drivers of recent progress. Many researchers argue that models get more capable largely because they are trained with far more compute than earlier ones. That is why access to chips has become a topic of business planning and government policy, and why some proposals for oversight focus on the size of a training run.

People disagree about how far this can continue. Some expect steady gains as long as more compute is available. Others point to limits in data, energy, cost or the methods themselves. Compute is also not the whole story: better designs and better training methods can achieve more with the same amount.

Related: https://www.superintelligence.com.au/glossary/flop.md, https://www.superintelligence.com.au/glossary/scaling-laws.md, https://www.superintelligence.com.au/glossary/test-time-compute.md, https://www.superintelligence.com.au/glossary/frontier-lab.md