Starting from a background in computer engineering, Alex Starnes created his dream career as a product and user experience designer. Learn how his bold moves in life and design have paid off at NVIDIA. #NVIDIAlife Learn more: https://nvda.ws/4r1rndM
About us
Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.
- Website
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http://www.nvidia.com
External link for NVIDIA
- Industry
- Computer Hardware Manufacturing
- Company size
- 10,001+ employees
- Headquarters
- Santa Clara, CA
- Type
- Public Company
- Founded
- 1993
- Specialties
- GPU-accelerated computing, artificial intelligence, deep learning, virtual reality, gaming, self-driving cars, supercomputing, robotics, virtualization, parallel computing, professional graphics, and automotive technology
Locations
Employees at NVIDIA
Updates
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This week on NVIDIA Newsroom: • NVIDIA wins every MLPerf Training v5.1 benchmark, powered by Blackwell Ultra. • San Jose Mayor Matt Mahan joins the NVIDIA AI Podcast to share how AI is reshaping city life. • ICYMI: NVIDIA CEO Jensen Huang’s GTC D.C. keynote on America’s next Apollo moment. Read the latest:
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The new Fairwater AI datacenter in Atlanta, powered by hundreds of thousands NVIDIA Blackwell and Blackwell Ultra GPUs leveraging the NVIDIA GB200 and GB300 NVL72 rack-scale systems with Spectrum-X Ethernet, is pushing boundaries for performance, sustainability, and AI infrastructure. Proud to be a part of the next chapter in AI innovation alongside Microsoft.
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: https://lnkd.in/e82Dm2jQ
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Mixture-of-Experts (MoE) models like DeepSeek-R1 unlock new levels of capability—but only if they can scale efficiently. That’s where extreme hardware–software co-design at rack-scale comes in. With NVIDIA Blackwell and NVIDIA Dynamo, AI service providers can transform clusters into intelligent inference systems—achieving 10× performance and revenue while reducing cost per token. Now, with NVIDIA Dynamo integrating with major cloud providers that same breakthrough performance is available to cloud customers—including Amazon Web Services (AWS), Google Cloud, Microsoft Azure, and Oracle Cloud. Learn more: https://nvda.ws/4hUXcki
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In the latest #MLPerf Training v5.1 round, NVIDIA swept all seven benchmarks. The NVIDIA Blackwell Ultra GPU made its MLPerf Training debut, delivering large leaps for LLM pretraining and LLM fine-tuning performance, supercharged by the world’s first FP4 training submissions with NVFP4. Learn more: https://nvda.ws/4oxGv0T
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Discover what’s new in AI learning and certification in the November edition of the NVIDIA Training newsletter. Explore new DLI Learning Paths, watch GTC DC labs on demand, and dive deeper into professional #GenerativeAI certifications for LLMs and agentic AI. You’ll also find new developer and AI infrastructure courses, plus upcoming instructor-led workshops running through February. Read the full issue ⤵️ #NVIDIAcertification #agenticAI
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NVIDIA CEO Jensen Huang outlines the next phase of accelerated computing and AI — from national AI infrastructure and quantum computing to robotics and reindustrialization. Broadcast from the nation’s capital, #NVIDAIGTC Washington, D.C. highlights how NVIDIA and its partners are advancing America’s AI leadership. Watch the keynote > https://nvda.ws/3Wei6Rs
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💡 Discover how the intersection of supercomputing and science is being redefined. Join our NVIDIA #SC25 Fireside Chat to hear directly from the minds shaping the future of #HPC. Our own Ian Buck will lead a discussion with global leaders: Ceren Susut (U.S. Department of Energy (DOE)), Dan Stanzione (Texas Advanced Computing Center (TACC)), Thomas Lippert (Jülich Supercomputing Centre (JSC)), and Satoshi Matsuoka (RIKEN). Gain insights into how AI is revolutionizing drug discovery, astrophysics, materials science, and more. 📅 Monday, November 17, 4:00 – 5:30 p.m. CT (Doors open at 3:30) 📌 Reserve your spot: https://nvda.ws/47nWdWh
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From the transistor to the internet, every leap forward has shaped America’s destiny. Now, a new industrial revolution begins — powered by AI and NVIDIA accelerated computing. This is America’s next Apollo moment. This is the age of AI. Watch the story unfold → https://nvda.ws/3JQpMGT
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This week in the NVIDIA Newsroom weekly newsletter: • NVIDIA CEO Jensen Huang is awarded the Queen Elizabeth Prize for Engineering • Deutsche Telekom and NVIDIA launch the world’s first Industrial AI Cloud • The rise of U.S. reindustrialization, powered by AI Catch up on the headlines and what’s next ⬇️.