AI · · 5 min
Why compute capacity matters for AI
Access to compute shapes which problems an organisation can realistically work on. A look at the practical implications.
Model quality, iteration speed, and the size of problems a team can take on are all bounded by available compute.
Iteration speed
Teams that can run experiments quickly learn faster. Long queues and slow jobs reduce the number of ideas that get tested.
Locality
Where compute sits relative to data affects cost, performance, and compliance. For sensitive data, local capacity can be a requirement rather than a preference.
Efficiency
Capacity is not only about quantity. Well-run infrastructure extracts more useful work from the same hardware.