NVIDIA CEO Jensen Huang spoke at the Edison Electric Institute's annual meeting, discussing the future of the energy sector and the role of AI in the next industrial revolution. The event was attended by over a thousand utility and energy industry executives. Huang emphasized the bright future of digital intelligence and the energy sector, citing the application of AI to increase efficiency in utilities.

Source: https://blogs.nvidia.com/

Erik Pounds is a director of product marketing at NVIDIA, where he focuses on data science and edge computing platforms. He previously led marketing at SwiftStack and held leadership roles in product management at companies including EMC, Brocade, Drobo, and BitTorrent. Erik holds a Bachelor of Science in business administration from the University of San Francisco.

Source: https://blogs.nvidia.com/

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Source: https://blogs.nvidia.com/

Source: https://blogs.nvidia.com/

Source: https://blogs.nvidia.com/

NVIDIA has been ranked as the second-best place to work in America, according to Glassdoor's list of best employers for 2024. The company has risen in the rankings, indicating a positive work environment and employee satisfaction.

Source: https://blogs.nvidia.com/

Veronica Miller, a refugee from Eritrea, shares her family's story of resilience and courage. Her parents escaped war and settled in East Orange, New Jersey, where they faced discrimination and struggled to find jobs. Miller's parents worked in the shipping industry and later became a cab driver and home health aide, respectively. Miller credits her parents' strength for making her life possible.

Source: https://blogs.nvidia.com/

Source: https://blogs.nvidia.com/

According to UNESCO, 3,000 indigenous languages are at risk of disappearing by the end of the century, with three-quarters of the total facing extinction. This means that one indigenous language could disappear every two weeks. UNESCO is sounding the alarm about the alarming rate of language loss.

Source: https://blogs.nvidia.com/

NVIDIA achieved exceptional performance in the MLPerf Training v4.0 benchmarks, more than tripling the performance on the large language model (LLM) benchmark compared to its previous record-setting submission. The achievement was made possible through the use of an AI supercomputer featuring 11,616 NVIDIA H100 Tensor Core GPUs connected with NVIDIA Quantum-2 InfiniBand networking.

Source: https://blogs.nvidia.com/