Artificial intelligence (AI) has been the buzzword of 2023, and generative AI seems to be at the forefront of this technology. Big tech companies have been making efforts to integrate this technology into their suite of products, with Google's Pixel 8 series already featuring multiple AI features. On the other hand, Samsung's next smartphone, the Galaxy S24, could also get an AI boost. Amidst such reports, Apple is also reportedly planning to bring AI to its devices, namely the iPhone, with iOS 18. Check out all the AI features coming to iOS 18.
Nvidia’s NeMo taps generative AI in designing semiconductor chips
31.10.2023 - 18:17 / venturebeat.com / Ai
In a research paper released today, Nvidia semiconductor engineers showcased how generative artificial intelligence (AI) can assist in the complex process of designing semiconductors.
The study demonstrated how specialized industries can leverage large language models (LLMs) trained on internal data to create assistants that enhance productivity.
The research, utilizing Nvidia NeMo, highlights the potential for customized AI models to provide a competitive edge in the semiconductor field.
Semiconductor design is a highly challenging endeavor, involving the meticulous construction of chips containing billions of transistors on 3D circuitry maps that are like city streets — but thinner than a human hair.
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It requires the coordination of multiple engineering teams over a span of years. Each team specializes in different aspects of chip design, employing specific methods, software programs, and computer languages.
Mark Ren, an Nvidia Research director, was the lead author of the paper.
“I believe over time large language models will help all the processes, across the board,” Ren said in a statement.
The paper was announced by Bill Dally, Nvidia’s chief scientist, during a keynote at the International Conference on Computer-Aided Design held in San Francisco.
“This effort marks an important first step in applying LLMs to the complex work of designing semiconductors,” said Dally, in a statement. “It shows how even highly specialized fields can use their internal data to train useful generative AI models.”
The research team at Nvidia developed a custom LLM called ChipNeMo, trained on the company’s internal data, to generate and optimize software and assist human designers. The long-term goal is to apply generative AI to every stage of chip design, leading to substantial gains in overall productivity. The initial use cases explored by the team include a chatbot, a code generator, and an analysis tool.
The most well-received use case thus far is an analysis tool that automates the time-consuming task of maintaining updated bug descriptions. And a prototype chatbot that helps engineers find technical documents quickly and a code generator that creates snippets of specialized software for chip designs are also under development.
The research paper focuses on the team’s efforts to gather design data and create a specialized generative AI model. This process can be applied to any industry. The team started with a foundation model and used Nvidia NeMo, a framework for building, customizing, and deploying generative
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