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AI Supercomputing New Product Icon 

Microsoft Azure

The trend toward the use of massive AI models to power a large number of tasks is changing how AI is built. The advantage of large scale models is that they only need to be trained once with massive amounts of data using AI supercomputing, enabling them to then be “fine-tuned” for different tasks and domains with much smaller datasets and resources. Training models at this scale requires large clusters of hundreds of machines with specialized AI accelerators interconnected by high-bandwidth networks inside and across the machines. The work that we have done on large-scale compute clusters, leading network design, and the software stack, including Azure Machine Learning, ONNX Runtime, and other Azure AI services, to manage it is directly aligned with our AI at Scale strategy.

Other product: Azure HPC

Other product: Azure Quantum

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