NVIDIA CEO Brings Generative AI to SIGGRAPH

As generative AI continues to sweep an increasingly digital, hyperconnected world, NVIDIA founder and CEO Jensen Huang made a thunderous return to SIGGRAPH, the world's premier computer graphics conference.

The generative AI era is upon us, the iPhone moment if you will, Huang told an audience of thousands Tuesday during an in-person special address in Los Angeles.

News highlights include the next-generation GH200 Grace Hopper Superchip platform, NVIDIA AI Workbench - a new unified toolkit that introduces simplified model tuning and deployment on NVIDIA AI platforms - and a major upgrade to NVIDIA Omniverse with generative AI and OpenUSD.

The announcements are about bringing all of the past decade's innovations - AI, virtual worlds, acceleration, simulation, collaboration and more - together.

Graphics and artificial intelligence are inseparable, graphics needs AI, and AI needs graphics, Huang said, explaining that AI will learn skills in virtual worlds, and that AI will help create virtual worlds.

Fundamental to AI, Real-Time Graphics Five years ago at SIGGRAPH, NVIDIA reinvented graphics by bringing AI and real-time ray tracing to GPUs. But while we were reinventing computer graphics with artificial intelligence, we were reinventing the GPU altogether for artificial intelligence, Huang said.

The result: increasingly powerful systems such as the NVIDIA HGX H100, which harnesses eight GPUs - and a total of 1 trillion transistors - that offer dramatic acceleration over CPU-based systems.

This is the reason why the world's data centers are rapidly transitioning to accelerated computing, Huang told the audience. The more you buy, the more you save.

To continue AI's momentum, NVIDIA created the Grace Hopper Superchip, the NVIDIA GH200, which combines a 72-core Grace CPU with a Hopper GPU, and which went into full production in May.

Huang announced that NVIDIA GH200, which is already in production, will be complemented with an additional version with cutting-edge HBM3e memory.

He followed up on that by announcing the next-generation GH200 Grace Hopper superchip platform with the ability to connect multiple GPUs for exceptional performance and easily scalable server design.

Built to handle the world's most complex generative workloads, spanning large language models, recommender systems and vector databases, the new platform will be available in a wide range of configurations.

The dual configuration - which delivers up to 3.5x more memory capacity and 3x more bandwidth than the current generation offering - comprises a single server with 144 Arm Neoverse cores, eight petaflops of AI performance, and 282GB of the latest HBM3e memory technology.

Leading system manufacturers are expected to deliver systems based on the platform in the second quarter of 2024.

A packed house at the SIGGRAPH professional graphics conference attended NVIDIA founder and CEO Jensen Huang's keynote address. NVIDIA AI Workbench Speeds Adoption of Custom Generative AI To speed custom adoption of generative AI for the world's enterprises, Huang announced NVIDIA AI Workbench. It provides developers with a unified, easy-to-use toolkit to quickly create, test and fine-tune generative AI models on a PC or workstation - then scale them to virtually any data center, public cloud or NVIDIA DGX Cloud.

AI Workbench removes the complexity of getting started with an enterprise AI project. Accessed through a simplified interface running on a local system, it allows developers to fine-tune models from popular repositories such as Hugging Face, GitHub and NGC using custom data. The models can then be shared easily across multiple platforms.

While hundreds of thousands of pretrained models are now available, customizing them with the many open-source tools available can be challenging and time consuming.

In order to democratize this ability, we have to make it possible to run pretty much everywhere, Huang said.

With AI Workbench, developers can customize and run generative AI in just a few clicks. It allows them to pull together all necessary enterprise-grade models, frameworks, software development kits and libraries into a unified developer workspace.

Everybody can do this, Huang said.

Leading AI infrastructure providers - including Dell Technologies, Hewlett Packard Enterprise, HP Inc., Lambda, Lenovo and Supermicro - are embracing AI Workbench for its ability to bring enterprise generative AI capability to wherever developers want to work - including a local device.

Huang also announced a partnership between NVIDIA and startup Hugging Face, which has 2 million users, that will put generative AI supercomputing at the fingertips of millions of developers building large language models and other advanced AI applications.

Developers will be able to access NVIDIA DGX Cloud AI supercomputing within the Hugging Face platform to train and tune advanced AI models.

This is going to be a brand new service to connect the world's largest AI community to the world's best training and infrastructure, Huang said.

In a video, Huang showed how AI Workbench and ChatUSD bring it all together: allowing a user to start a project on a GeForce RTX 4090 laptop and scale, seamlessly to a workstation, or the data center as it grows more complex.

Using Jupyter Notebook, a user can prompt the model to generate a picture of Toy Jensen in space. When the model provides a result that doesn't work, because it's never seen Toy Jensen, the user can fine-tune the model with eight images of Toy Jensen and then prompt it again to get a correct result.

Then with AI Workbench, the new model can be deployed to an enterprise application.

New NVIDIA Enterprise 4.0 Software Advances AI Deployment In a further step to accelerate the adoption of generative AI, NVIDIA announced the latest versio

LINK:	https://blogs.nvidia.com/blog/2023/08/08/siggraph-2023-special-address...
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