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Satya Nadella

@satyanadella5,342,503 subscribers

Chairman and CEO at Microsoft

Shorts

Our newest AI accelerator Maia 200 is now online in Azure. Designed for industry-leading inference efficiency, it delivers 30% better performance per dollar than current systems. And with 10+ PFLOPS FP4 throughput, ~5 PFLOPS FP8, and 216GB HBM3e with 7TB/s of memory bandwidth it's optimized for large-scale AI workloads. It joins our broader portfolio of CPUs, GPUs, and custom accelerators, giving customers more options to run advanced AI workloads faster and more cost-effectively on Azure.

Our newest AI accelerator Maia 200 is now online in Azure. Designed for industry-leading inference efficiency, it delivers 30% better performance per dollar than current systems. And with 10+ PFLOPS FP4 throughput, ~5 PFLOPS FP8, and 216GB HBM3e with 7TB/s of memory bandwidth it's optimized for large-scale AI workloads. It joins our broader portfolio of CPUs, GPUs, and custom accelerators, giving customers more options to run advanced AI workloads faster and more cost-effectively on Azure.

845,903 views

Another first for our AI fleet... a supercomputing cluster of NVIDIA GB300s with 4600+ GPUs and featuring next gen InfiniBand. First of many as we scale to hundreds of thousands of GB300s across our DCs, and rethink every layer of the stack across silicon, systems, and software to support next gen AI workloads.

Another first for our AI fleet... a supercomputing cluster of NVIDIA GB300s with 4600+ GPUs and featuring next gen InfiniBand. First of many as we scale to hundreds of thousands of GB300s across our DCs, and rethink every layer of the stack across silicon, systems, and software to support next gen AI workloads.

723,492 views

Today we’re introducing Copilot Mode in Edge, our first step in reinventing the browser for the AI age. My favorite feature is multi-tab RAG. You can use Copilot to analyze your open tabs, like I do here with papers our team has published in nature journals over the last year. And there is a lot more to come, including built-in actions so you can delegate tasks as you browse.

Today we’re introducing Copilot Mode in Edge, our first step in reinventing the browser for the AI age. My favorite feature is multi-tab RAG. You can use Copilot to analyze your open tabs, like I do here with papers our team has published in nature journals over the last year. And there is a lot more to come, including built-in actions so you can delegate tasks as you browse.

704,497 views

Counting down to a new Build in San Francisco. Hope you’ll join us!

Counting down to a new Build in San Francisco. Hope you’ll join us!

200,716 views

3/ Notebooks: With Web + Work + Pages, you can ideate with AI and collaborate with other people. It has entirely changed my workflow. And now with Notebooks, I can organize all of my heterogeneous data for a project, whether it’s Pages, docs, websites, team meetings – and Copilot will ground itself just on that content. And this might be the best part: I can turn it all into a new modality like an audio overview. For example, I can collect all the latest things I’m reading about agents and agent frameworks, and then I can listen to it.

3/ Notebooks: With Web + Work + Pages, you can ideate with AI and collaborate with other people. It has entirely changed my workflow. And now with Notebooks, I can organize all of my heterogeneous data for a project, whether it’s Pages, docs, websites, team meetings – and Copilot will ground itself just on that content. And this might be the best part: I can turn it all into a new modality like an audio overview. For example, I can collect all the latest things I’m reading about agents and agent frameworks, and then I can listen to it.

266,189 views

With Web + Work + Pages, you can now ideate with AI and collaborate with other people. It’s just magical. You can learn more here:

With Web + Work + Pages, you can now ideate with AI and collaborate with other people. It’s just magical. You can learn more here:

163,177 views

5/ Model choice! Switch between OpenAI and Anthropic in Researcher to get the best fit for the job.

5/ Model choice! Switch between OpenAI and Anthropic in Researcher to get the best fit for the job.

47,122 views

Videos

Grok is coming to Azure Foundry! Thanks Elon Musk for joining us at Build to talk about what it means for devs.
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satyanadella's profile picture

If intelligence is the log of compute… it starts with a lot of compute! And that’s why we’re scaling our GPU fleet faster than anyone else. Just last year, we added over 2 gigawatts of new capacity – roughly the output of 2 nuclear power plants. And today we’re going further, announcing the world's most powerful AI datacenter, located in southeastern Wisconsin. Fairwater is a seamless cluster of hundreds of thousands of NVIDIA GB200s, connected by enough fiber to circle the Earth 4.5 times. It will deliver 10x the performance of the world’s fastest supercomputer today, enabling AI training and inference workloads at a level never before seen. For AI training workloads, you need compute at exponential scale. That’s why we designed the datacenter, GPU fleet, and network together as one integrated system. This ensures a single job can run from day 1 at exponential scale across thousands of GPUs. Fairwater uses a liquid-cooled closed-loop system for cooling GPUs that requires zero water for operations after construction. And we’re matching all of the energy that is consumed with renewable sources. And of course, it is just one of several similar sites we’re lighting up across our 70+ regions. We have multiple identical Fairwater datacenters under construction in other locations across the US, in addition to our AI infrastructure already deployed in over 100 datacenters around the world, powering model training, test-time compute, RL tuning, and real-time inference at global scale. Too often during times like this, people go with the current and only later wonder, how did we get here? With Fairwater, we're charting a new path: doing the hard engineering work, bringing compute, network, and storage into one highly scaled cluster, and designing closed-loop energy systems to meet real-world computing needs. And partnering with local communities to ensure it's thoughtfully done in a way that is sustainable, creates new jobs, and expands opportunity. We are thrilled to see this take hold in Wisconsin, and we are just getting started.

Satya Nadella

2,017,898 views • 8 months ago

satyanadella's profile picture

Today we announced our new Fairwater datacenter in Atlanta, connected with our first Fairwater site in Wisconsin and our broader Azure footprint to create the world’s first AI superfactory. Fairwater exemplifies our vision for a fungible fleet: infra that can serve any workload, anywhere, on fit-for-purpose accelerators and network paths, with maximum performance and efficiency. AI workloads have evolved beyond large-scale pre-training. Today, they encompass fine-tuning, reinforcement learning (RL), synthetic data generation, evaluation pipelines, and more. Fairwater is built to support this full lifecycle: Max density: Fairwater’s two-story design and liquid cooling system lets us place racks in three dimensions and pack them with GPUs as densely as possible, minimizing cable runs and improving latency and effective bandwidth. Fleet: Each Fairwater DC can integrate hundreds of thousands of the latest NVIDIA GPUs into a single coherent cluster. This provides flexible infra that can support the full spectrum of workloads, and ensure no GPU is left unnecessarily idle. And that’s on top of the more than 100,000 GB300s coming online this quarter alone for inference across the rest of our fleet. For us, it’s all about turning every gigawatt into the maximum number of useful tokens. Not every GW is created equal! Planet-scale: Every Fairwater DC will connect through our continent-spanning AI WAN to prior generations of AI supercomputers, forming a truly fungible pool of compute. This enables developers to scale beyond the capacity of a single site and dynamically land workloads on the right infra for their needs. Together, these innovations let us bring together different generations of silicon and AI systems across DCs and geos into a single elastic system that scales seamlessly across training and inference workloads And this elastic AI capacity is all available alongside all the other cloud services (compute, storage, databases, app services) that AI agents and workloads need. This is what we mean when we talk about building a fungible fleet – a single, unified platform that pushes the limits of performance per watt and per dollar. Read more:

Satya Nadella

906,607 views • 6 months ago