正在加载视频...

视频加载失败

📣Announcing Microsoft Azure Boost DPU: our first in-house DPU! Specifically architected to take on cloud-based, data-centric workloads, future DPU-equipped servers will run cloud storage workloads at 3X less power and 4X the performance of existing servers. #MSIgnite

36,263 次观看 • 1 年前 •via X (Twitter)

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Before becoming Microsoft’s new CEO in 2014, Satya Nadella wrote a 10-page memo to the board as part of the selection process. He discussed the details of the memo on the BG2 podcast: ▫️Elevator pitch: Two phrases he used were “ambient intelligence” and “ubiquitous computing” (his PR folks told him to dumb it down and he remade the pitch to “mobile first, cloud first layer”, and has executed on exactly that over the past decade). ▫️Mental model of Microsoft = cloud infrastructure is core: “One of the things I've always resisted is thinking of our Cloud the way the market segments it…I don't allocate my capital thinking ‘here is the Azure capital, here is the M365 capital, here is gaming [capital]’ I kind of think, ‘hey, there's a cloud [infrastructure]. That's the core theory of the firm for me. On top of it, I have a set of workloads. One of those workloads happens to be Azure. The other one is M365 [then] Dynamics [then] gaming’…That was all in that memo and pretty much has played out.” ▫️Selling the cloud pivot: “We had a 98% / 99% gross margin business in our servers and clients [division]. People said, ‘oh, good news, you now can move to the cloud and maybe you'll have some margin. [But we already had margin].’[...] My gut was [that cloud first would be] less gross margin but the TAM is bigger…we'll sell more to small businesses. We will sell more in aggregate, in terms of even upsells like the consumption would increase.” Nadella -- who was running Microsoft's Server and Tools Business (which housed Azure) -- also noted that he was able to sell his vision because he was an “insider” (he joined Microsoft in 1992). As a result, his criticisms of the business would also be a criticism of himself. As Brad Gerstner and Bill Gurley note in the podcast, Nadella joined when Microsoft was worth $300B and has seen its market cap since grow 10x to $3.25T (one of the best public market CEO runs ever). *** Full podcast def worth a listen:

Trung Phan

131,772 次观看 • 1 年前

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

908,065 次观看 • 9 个月前