AI at the Edge

Artificial intelligence (AI) is increasingly being integrated into engineering design and simulation tools. NVIDIA and its partner Dell Technologies have been at the forefront of supporting this evolution with AI-ready workstations equipped with powerful NVIDIA RTX™ GPUs driving Autodesk software.

At Autodesk University 2024 (AU 2024), NVIDIA and Dell will take part in a panel discussion laying out the role of workstations in AI-enabled workflows for engineering and other industries and workflows. The session, titled AI at the Edge: The Role of Local Compute, will take place Wednesday Oct. 16 at 3 pm PDT, and includes experts from NVIDIA, Dell, and Intel.

AU 2024 is being held in San Diego, CA, on October 15-17.

At the 2023 event, Autodesk rolled out its Autodesk AI platform, focused on automating tasks for engineers to help them iterate more quickly, augment creative problem solving, and improve their productivity. Some of those tasks include more quickly generating proportional 3D models, dynamic navigation of design data, markup assist, real-time analysis, generative design, and the ability to leverage previous designs and modeling to inform new concepts. This year, the company is expected to expand further on the AI capabilities within its Fusion platform. 

The Oct. 16 panel discussion will help users: 

• Describe the types of AI workloads that are best suited for cloud implementation and those that should be run locally.
• Evaluate your technology stack to respond to current and future AI features.
• Identify use cases for AI features and their enabling system configurations.

Session moderator Ken Flannigan, Director of AEC Alliances and Solutions at Dell Technologies, says that panelists will discuss potential AI workflows and examples as well. 

“A lot of the AI functions that people are familiar with are not necessarily happening locally on their machine. This session is all about the role of local compute when it comes to AI,” Flannigan said. “In some cases, the data may be too big to load to the cloud which can introduce latency and operational costs that are not practical.” In other cases, users may not be able to load data to the cloud because of security sensitivities or because of agreements with their customers.

Earlier this year, Dell announced its latest AI-ready workstations (in its Precision line of professional hardware) and AI PCs (in Dell’s non-workstation brand computers) to help enable such workflows.

“The primary thing that drives AI workstations is performance, but they are focused on AI calculations,” said Matt Allard, Director of Strategic Alliances at Dell Technologies, who will participate in the panel at AU.  “This is where NVIDIA is of particular interest, because the NVIDIA RTX™ GPUs include dedicated AI processing circuits called Tensor cores. Because the number of Tensor cores in the GPU scales AI processing capability across NVIDIA’s product line, customers can scale their AI performance based on their workflows and compute capacity needs. You need a balanced system with good RTX GPUs, good CPUs, and plenty of memory and storage for handling large language models (LLMs).”

Flannigan said that many engineering, construction and architecture users already have Dell hardware that is equipped with AI-ready features. “They have machines that can open up large assemblies and do simulations, and a lot of those same components can also support multi-feature AI workloads,” he said. “The AI features need to be supported by your hardware, on top of the design and productivity applications you are already using.”

Dell will demonstrate 10 AI-enabled use cases in its booth #314, as well discuss those use cases during the presentation.

For example, Flannigan mentioned reality capture and neural radiance fields, which can allow users to convert video into a point cloud or 3D mesh. That process has traditionally been fairly clunky and time consuming, but AI features can streamline that process and make it much easier and more useful for engineers. 

“You can take your phone down a city street, shoot some video and turn that into a radiance field,” Flannigan said. “AI is not just about LLMs. It is opening up new ways of working. The hardware underpinning these capabilities has to be there to manage those workloads.”

You can read more about the AU 2024 panel discussion here. 

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