NVIDIA’s GPU platform is leading the way in supercomputing, surpassing CPUs in efficiency for AI, science, and business. The shift from CPUs to GPUs represents a historic transition in computing, with over 85% of top supercomputers now using GPUs.

Machine learning evolved from CPUs to GPUs in 2012, unlocking new possibilities for AI. GPUs deliver more operations per watt, making exascale computing practical. NVIDIA GPUs outperform CPUs in energy efficiency, with a 4.5x advantage in performance.

NVIDIA’s AI supercomputing platform goes beyond GPUs, incorporating networking, memory, and more for a full-stack solution. Open-source libraries like CUDA-X accelerate workflows, with Snowflake integrating NVIDIA A10 GPUs for faster data science.

The transition from CPUs to GPUs is driving AI’s next frontier with three scaling laws: pretraining, post-training, and test-time scaling. GPUs enable higher performance in AI models, with advancements in generative AI transforming industries like robotics and autonomous vehicles.

Recommender systems powered by GPUs are transforming e-commerce, with a 1% increase in accuracy translating to billions more in sales. The shift to generative AI is reshaping hyperscalers and infrastructure investments, driving trillions of dollars in industry transformations.

AI is evolving from virtual to physical applications, with generative, agentic, and physical AI reshaping industries. Agentic AI promises autonomous digital workers, while physical AI embodied robots are poised to disrupt manufacturing and healthcare by 2050.

NVIDIA’s AI advancements are set to transform every market, with AI becoming a fundamental part of the computing stack. The virtuous cycle of AI is driving new supercomputing platforms, opening up vast opportunities across industries.

Read more at NVIDIA: 3 Ways NVIDIA Is Powering the Industrial Revolution