
ChatGPT is just the start.
With computing now advancing at what he called lightspeed, NVIDIA founder and CEO Jensen Huang today announced a broad set of partnerships with Google, Microsoft, Oracle and a range of leading businesses that bring new AI, simulation and collaboration capabilities to every industry.
The warp drive engine is accelerated computing, and the energy source is AI, Huang said in his keynote at the company's GTC conference. The impressive capabilities of generative AI have created a sense of urgency for companies to reimagine their products and business models.
In a sweeping 78-minute presentation anchoring the four-day event, Huang outlined how NVIDIA and its partners are offering everything from training to deployment for cutting-edge AI services. He announced new semiconductors and software libraries to enable fresh breakthroughs. And Huang revealed a complete set of systems and services for startups and enterprises racing to put these innovations to work on a global scale.
Huang punctuated his talk with vivid examples of this ecosystem at work. He announced NVIDIA and Microsoft will connect hundreds of millions of Microsoft 365 and Azure users to a platform for building and operating hyperrealistic virtual worlds. He offered a peek at how Amazon is using sophisticated simulation capabilities to train new autonomous warehouse robots. He touched on the rise of a new generation of wildly popular generative AI services such as ChatGPT.
And underscoring the foundational nature of NVIDIA's innovations, Huang detailed how, together with ASML, TSMC and Synopsis, NVIDIA computational lithography breakthroughs will help make a new generation of efficient, powerful 2-nm semiconductors possible.
The arrival of accelerated computing and AI come just in time, with Moore's Law slowing and industries tackling powerful dynamics -sustainability, generative AI, and digitalization, Huang said. Industrial companies are racing to digitalize and reinvent into software-driven tech companies - to be the disruptor and not the disrupted, Huang said.
Acceleration lets companies meet these challenges. Acceleration is the best way to reclaim power and achieve sustainability and Net Zero, Huang said.
GTC: The Premier AI Conference GTC, now in its 14th year, has become one of the world's most important AI gatherings. This week's conference features 650 talks from leaders such as Demis Hassabis of DeepMind, Valeri Taylor of Argonne Labs, Scott Belsky of Adobe, Paul Debevec of Netflix, Thomas Schulthess of ETH Zurich and a special fireside chat between Huang and Ilya Sutskever, co-founder of OpenAI, the creator of ChatGPT.
More than 250,000 registered attendees will dig into sessions on everything from restoring the lost Roman mosaics of 2,000 years ago to building the factories of the future, from exploring the universe with a new generation of massive telescopes to rearranging molecules to accelerate drug discovery, to more than 70 talks on generative AI.
The iPhone Moment of AI NVIDIA's technologies are fundamental to AI, with Huang recounting how NVIDIA was there at the very beginning of the generative AI revolution. Back in 2016 he hand-delivered to OpenAI the first NVIDIA DGX AI supercomputer - the engine behind the large language model breakthrough powering ChatGPT.
Launched late last year, ChatGPT went mainstream almost instantaneously, attracting over 100 million users, making it the fastest-growing application in history. We are at the iPhone moment of AI, Huang said.
NVIDIA DGX supercomputers, originally used as an AI research instrument, are now running 24/7 at businesses across the world to refine data and process AI, Huang reported. Half of all Fortune 100 companies have installed DGX AI supercomputers.
DGX supercomputers are modern AI factories, Huang said.
NVIDIA H100, Grace Hopper, Grace, for Data Centers Deploying LLMs like ChatGPT are a significant new inference workload, Huang said. For large-language-model inference, like ChatGPT, Huang announced a new GPU - the H100 NVL with dual-GPU NVLink.
Based on NVIDIA's Hopper architecture, H100 features a Transformer Engine designed to process models such as the GPT model that powers ChatGPT. Compared to HGX A100 for GPT-3 processing, a standard server with four pairs of H100 with dual-GPU NVLink is up to 10x faster.
H100 can reduce large language model processing costs by an order of magnitude, Huang said.
Meanwhile, over the past decade, cloud computing has grown 20% annually into a $1 trillion industry, Huang said. NVIDIA designed the Grace CPU for an AI- and cloud-first world, where AI workloads are GPU accelerated. Grace is sampling now, Huang said.
NVIDIA's new superchip, Grace Hopper, connects the Grace CPU and Hopper GPU over a high-speed 900GB/sec coherent chip-to-chip interface. Grace Hopper is ideal for processing giant datasets like AI databases for recommender systems and large language models, Huang explained.
Customers want to build AI databases several orders of magnitude larger, Huang said. Grace Hopper is the ideal engine.
DGX the Blueprint for AI Infrastructure The latest version of DGX features eight NVIDIA H100 GPUs linked together to work as one giant GPU. NVIDIA DGX H100 is the blueprint for customers building AI infrastructure worldwide, Huang said, sharing that NVIDIA DGX H100 is now in full production.
H100 AI supercomputers are already coming online.
Oracle Cloud Infrastructure announced the limited availability of new OCI Compute bare-metal GPU instances featuring H100 GPUs.
Additionally, Amazon Web Services announced its forthcoming EC2 UltraClusters of P5 instances, which can scale in size up to 20,000 interconnected H100 GPUs.
This follows Microsoft Azure's private preview announcement last week for its H100 virtual machine, N
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