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Chip giant NvidiaZDNET
•86% Informative
Nvidia has long dominated what's known as the "training" of neural networks, the compute-intensive task of fashioning and refashioning the neural "weights" of the network until they reach optimal performance.
The MLCommons , the industry consortium that compiles multiple benchmark reports each year on AI chip performance, announced numbers for how different chips perform when training neural nets for a variety of tasks.
All of the results submitted, whether from Nvidia , Intel , AMD or Google , use only one of two x86 CPUs, Intel 's XEON or AMD 's EPYC .
Firmus Technologies' cloud computing system took between 45 million and 46 million Jules to train the network using 512 H100 chips.
The cost of training AI has been a hot-button issue in recent years , both in terms of cost burden and the environmental burden.
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