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2023-03-22

Nvidia Announces Tech for Speeding up Chip Design at AI Conference

March 21 (Reuters) - Nvidia Corp Chief Executive Jensen Huang on Tuesday unveiled a new product for

Nvidia Announces Tech for Speeding up Chip Design at AI Conference

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Analysts are watching for the Santa Clara, California-based company to give more details about how it plans to widen accessibility to processing power like that used to develop fast-rising technologies such as the chatbot ChatGPT.</p><p>Last month, Huang told investors it would launch its own cloud computing service to offer more readily available access to large systems built with its chips.</p><p>Nvidia has come to dominate the field for selling chips used to developing generative AI technologies, which can answer questions with human-like text or generate fresh images based on a text prompt.</p><p>Those new technologies rely on the use of thousands of Nvidia chips at once to train the AI systems on huge troves of data. 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Analysts are watching for the Santa Clara, California-based company to give more details about how it plans to widen accessibility to processing power like that used to develop fast-rising technologies such as the chatbot ChatGPT.</p><p>Last month, Huang told investors it would launch its own cloud computing service to offer more readily available access to large systems built with its chips.</p><p>Nvidia has come to dominate the field for selling chips used to developing generative AI technologies, which can answer questions with human-like text or generate fresh images based on a text prompt.</p><p>Those new technologies rely on the use of thousands of Nvidia chips at once to train the AI systems on huge troves of data. Microsoft Corp, for example, built a system with more than 10,000 Nvidia chips for startup company OpenAI to use in developing the technologies that underpin its wildly popular ChatGPT.</p><p>Huang on Tuesday announced a new technology called CuLitho to speed up the design and manufacturing of semiconductors. The software uses Nvidia&#39;s chips to speed up the step that sits between the software-based design of a chip and the physical fabrication of the lithography masks used to print that design on a piece of silicon.</p><p>The design of the masks has to be modified to account for the fact that many of the features on a chip will be smaller than the wavelength of the light used in the printing process, a step called optical proximity correction. Those calculations could take a traditional computing chip two weeks to complete, but Nvidia said Tuesday that its chips and software can handle the task overnight and reduce the electricy used from 35 megawatts to 5 megawatts.</p><p>Nvidia said it is working with ASML Holding, Synopsys Inc and Taiwan Semiconductor Manufacturing Co to bring the technology to market. Huang said TSMC will start readying the technology for production in June.</p><p>Huang also said that Nvidia is working with AT&amp;T Inc to make dispatching trucks more efficient and with quantum computing researchers to speed software development.</p><p>While Nvidia faces competition in the AI chip marketfrom Advanced Micro Devices (AMD) and several startup companies, the company has more than 80% of the market for chips used in training AI systems.</p><p>The boom in AI has helped drive Nvidia shares up 77% this year, compared with a rise of 11.5% in the Nasdaq Composite Index. With a market capitalization of $640 billion, Nvidia has grown to become about five times more valuable than longtime rival Intel Corp.</p></body></html>\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"NVDA":"英伟达"},"source_url":"","is_english":true,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"1124810976","content_text":"March 21 (Reuters) - Nvidia Corp Chief Executive Jensen Huang on Tuesday unveiled a new product for speeding up the design of semiconductors as it rolled out an array of new artificial intelligence technologies based around its chips and software.Huang made the remarks at GTC, the company's annual conference for software developers. Analysts are watching for the Santa Clara, California-based company to give more details about how it plans to widen accessibility to processing power like that used to develop fast-rising technologies such as the chatbot ChatGPT.Last month, Huang told investors it would launch its own cloud computing service to offer more readily available access to large systems built with its chips.Nvidia has come to dominate the field for selling chips used to developing generative AI technologies, which can answer questions with human-like text or generate fresh images based on a text prompt.Those new technologies rely on the use of thousands of Nvidia chips at once to train the AI systems on huge troves of data. Microsoft Corp, for example, built a system with more than 10,000 Nvidia chips for startup company OpenAI to use in developing the technologies that underpin its wildly popular ChatGPT.Huang on Tuesday announced a new technology called CuLitho to speed up the design and manufacturing of semiconductors. The software uses Nvidia's chips to speed up the step that sits between the software-based design of a chip and the physical fabrication of the lithography masks used to print that design on a piece of silicon.The design of the masks has to be modified to account for the fact that many of the features on a chip will be smaller than the wavelength of the light used in the printing process, a step called optical proximity correction. Those calculations could take a traditional computing chip two weeks to complete, but Nvidia said Tuesday that its chips and software can handle the task overnight and reduce the electricy used from 35 megawatts to 5 megawatts.Nvidia said it is working with ASML Holding, Synopsys Inc and Taiwan Semiconductor Manufacturing Co to bring the technology to market. Huang said TSMC will start readying the technology for production in June.Huang also said that Nvidia is working with AT&T Inc to make dispatching trucks more efficient and with quantum computing researchers to speed software development.While Nvidia faces competition in the AI chip marketfrom Advanced Micro Devices (AMD) and several startup companies, the company has more than 80% of the market for chips used in training AI systems.The boom in AI has helped drive Nvidia shares up 77% this year, compared with a rise of 11.5% in the Nasdaq Composite Index. 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