What runs ChatGPT? Inside Microsoft’s AI supercomputer Sponsored Content by Microsoft/NVIDIA
Wonder what it takes to run the infrastructure that hosts ChatGPT with over 100 million users today? Get an inside look at the AI supercomputer infrastructure built to run ChatGPT and other large language models. Go behind the scenes with Mark Russinovich, Microsoft Azure CTO, in this Microsoft Mechanics show and learn:
- How Microsoft collaborated with NVIDIA to deliver purpose-built AI infrastructure with NVIDIA GPUs
- How Project Forge checkpointing works to restore job states if a long training job fails or needs to be migrated
- How we used Low Ranking Adaptive (LoRA) fine-tuning to update a fraction of the base model for more training throughput and smaller checkpoints
- How UK-based company, Wayve, is using Azure’s AI supercomputer infrastructure for self-driving cars
- And how Confidential Computing works with Azure AI to combine datasets without sharing personally identifiable information for secure multiparty collaborations.
Why purpose-built Infrastructure for AI
AI is one of the most inspiring areas of technology evolution and is emerging as a key differentiator for businesses worldwide. Performance requirements for AI, however, are significantly different from other enterprise applications. Unlike conventional workloads, increasingly sophisticated AI models with billions of parameters require massive amounts of processing power plus lightning-fast networking and storage.
Advancements in AI infrastructure are at the foundation of that revolution. AI infrastructure is what powers your AI innovations and AI workloads require infrastructure built specifically for compute-intensive, large-scale AI workloads. An “AI-first” approach to infrastructure can accelerate model training and inference, increase performance and accuracy, and accelerate AI innovation.
Microsoft provides full stack cloud infrastructure purpose-built for AI. Engineered at every layer for AI, Azure AI infrastructure provides performance, scalability, and built-in security needed to build, train, and deploy the most demanding AI workloads with confidence, at any scale.
Learn more about Azure AI capabilities:
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