Category: Misc

As generative AI experiences rapid growth, the community has stepped up to foster this expansion in two significant ways: swiftly publishing state-of-the-art…

As generative AI experiences rapid growth, the community has stepped up to foster this expansion in two significant ways: swiftly publishing state-of-the-art foundational models, and streamlining their integration into application development and production. NVIDIA is aiding this effort by optimizing foundation models to enhance performance, allowing enterprises to generate tokens faster…

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European neobank bunq is debunking financial fraudsters with the help of NVIDIA accelerated computing and AI. Dubbed “the bank of the free,” bunq offers online banking anytime, anywhere. Through the bunq app, users can handle all their financial needs exclusively online, without needing to visit a physical bank. With more than 12 million customers and
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“Generative AI is reshaping industries and opening new opportunities for innovation and growth,” NVIDIA founder and CEO Jensen Huang said in an address ahead of this week’s COMPUTEX technology conference in Taipei. “Today, we’re at the cusp of a major shift in computing,” Huang told the audience, clad in his trademark black leather jacket. “The
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NVIDIA today announced that the world’s leaders in robot development are adopting the NVIDIA Isaac™ robotics platform for the research, development and production of the next generation of AI-enabled autonomous machines and robots.

NVIDIA today announced that major Taiwanese electronics makers are using the company’s technology to transform their factories into more autonomous facilities with a new reference workflow. The workflow combines NVIDIA Metropolis vision AI, NVIDIA Omniverse™ physically based rendering and simulation, and NVIDIA Isaac™ AI robot development and deployment.

Fueled by generative AI, enterprises globally are creating “AI factories,” where data comes in and intelligence comes out. Critical to this movement are validated systems and reference architectures that reduce the risk and time involved in deploying specialized infrastructure that can support complex, computationally intensive generative AI workloads. At the COMPUTEX trade show, NVIDIA today
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Manufacturers face increased pressures to shorten production cycles, enhance productivity, and improve quality, all while reducing costs. To address these…

Manufacturers face increased pressures to shorten production cycles, enhance productivity, and improve quality, all while reducing costs. To address these challenges, they’re investing in industrial digitalization and AI-enabled digital twins to unlock new possibilities from planning to operations. Developers at Pegatron, an electronics manufacturer based in Taiwan, used NVIDIA AI…

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With the growing emphasis on environmental, social, and governance (ESG) investments and initiatives, manufacturers are looking for new ways to increase energy…

With the growing emphasis on environmental, social, and governance (ESG) investments and initiatives, manufacturers are looking for new ways to increase energy efficiency and sustainability across their operations. One area of opportunity in electronics manufacturing is the performance of run-in test rooms, which are essential for ensuring the reliability, quality, and safety of the world’s…

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Whether you’re working on-premises or in the cloud, NVIDIA NIM inference microservices provide enterprise developers with easy-to-deploy optimized AI models…

Whether you’re working on-premises or in the cloud, NVIDIA NIM inference microservices provide enterprise developers with easy-to-deploy optimized AI models from the community, partners, and NVIDIA. Part of NVIDIA AI Enterprise, NIM offers a secure, streamlined path forward to iterate quickly and build innovations for world-class generative AI solutions. Using a single optimized container…

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Deploying generative AI in the enterprise is about to get easier than ever. NVIDIA NIM, a set of generative AI inference microservices, will work with KServe, open-source software that automates putting AI models to work at the scale of a cloud computing application. The combination ensures generative AI can be deployed like any other large
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