AI Compute
AI compute is the processing capacity used to train and run AI models, measured in chips, cluster hours or the cost of the calculations performed.
Why It Matters
Compute has become a scarce input that companies contract for years ahead, and access to it now separates the firms that can build frontier models from those that cannot.
Related Terms
- GPUA GPU is a processor built to perform many calculations in parallel. Designed for graphics, it turned out to suit the mathematics of neural networks, and it is the workhorse of AI training and inference.
- TPUA TPU is a chip designed specifically for machine learning workloads, built by an operator for use in its own data centres rather than sold as a general component.
- AI InfrastructureAI infrastructure is the physical and technical base that AI runs on: the chips, servers, networking, storage, data centres and power supply needed to train models and serve them to users.
- Compute AdvantageA compute advantage is secured access to processing capacity at a scale or price competitors cannot match, through owned facilities, long-term supply contracts or custom chips.
- InferenceInference is the act of running a trained model to produce an output: the answer, image or prediction a user actually receives, as distinct from the training that created the model.
VANTAGE52 Coverage
Published reporting filed under the topics behind this concept.
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