A research paper released last month describes ways generative AI can assist one of the most complex engineering efforts: designing semiconductors.
The work demonstrates how companies in highly specialized fields can train large language models (LLMs) on their internal data to build assistants that increase productivity.
Few pursuits are as challenging as semiconductor design. Under a microscope, a state-of-the-art chip like an NVIDIA H100 Tensor Core GPU (above) looks like a well-planned metropolis, built with tens of billions of transistors, connected on streets 10,000x thinner than a human hair.
Multiple engineering teams coordinate for as long as two years to construct one of these digital megacities.
Some groups define the chip’s overall architecture, some craft and place a variety of ultra-small circuits, and others test their work. Each job requires specialized methods, software programs and computer languages.
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SOURCE:
Silicon Volley: Designers Tap Generative AI for a Chip Assist
Semiconductor engineers show how a specialized industry can customize large language models to gain an edge using NVIDIA NeMo.
October 30, 2023 by Rick Merritt
