Azure's leadership in AI consumption provides unparalleled insights into designing cloud infrastructure for AI workloads.

Google Cloud will offer a virtual machine with a 180 teraflop TPU version 2 device, running TensorFlow programs quickly.

We're providing a full spectrum of compute options, from serverless Azure functions to Azure Container apps, to optimize performance for agentic scenarios.

Elon Musk's xAI is building a data center with 200,000 GPUs, which is currently the largest cluster, surpassing those of Meta and OpenAI, which have 128,000 and 100,000 GPUs respectively.

We're expanding Azure with over 70 data center regions, more than any other provider, to support the growing demands of AI workloads.

Nvidia's key advantage lies in its integrated solution, which includes networking with InfiniBand, CUDA software, and a developer-friendly experience, allowing AI researchers to effectively program GPU clusters as a unified system.

Azure's development began around 2005-2006, as AWS was gaining traction, and we recognized the need for a cloud platform to compete effectively.

Microsoft is proud of its Azure infrastructure, which now needs to be retrofitted to become AI factories.

At Fireworks, we manage the complexity of AI application scaling by utilizing a virtual cloud infrastructure that ensures high quality and reliability in GPU selection.