Kicking off the first in a series of global GPU Technology Conferences, NVIDIA co-founder and CEO Jen-Hsun Huang today at GTC China unveiled technology that will accelerate the deep learning revolution that is sweeping across industries. Huang spoke in front of a crowd of more than 2,500 scientists, engineers, entrepreneurs and press, gathered in Beijing for a day devoted to deep learning and AI. On stage he announced the Tesla P4 and P40 GPU accelerators for inferencing production workloads for AI services and, a small, energy-efficient AI supercomputer for highway driving -- the NVIDIA DRIVE PX 2 for AutoCruise. The new Tesla GPUs deliver massive leaps in efficiency and speed -- 45x compared to CPU-only systems -- for inferencing production workloads for AI services like voice-activated applications and movie and product recommendation engines. And they do it at a fraction of the cost of CPU systems.
Nvidia (NVDA) on Tuesday unveiled a palm-sized AI computer to be used by China internet giant Baidu's (BIDU) self-driving cars. Among a series of AI and other announcements it made at a chip industry conference in China, Nvidia said the new Drive PX 2 artificial-intelligence platform for "AutoCruise" functions will let vehicles use "deep neural networks to process data from multiple cameras and sensors." It said the product will let Baidu and other customers "accelerate production of automated and autonomous vehicles." Nvidia stock fell 1.5% in the stock market today, to 59.87, after rising 2% at the open. Baidu stock fell 1.2% Tuesday, to 181.90.
The annual Consumer Electronics Show, in Las Vegas has become the best place to learn about what's coming to cars. This year, however, the wild new capabilities rolling through CES, and into the auto industry, went from an open secret to headline grabbing news. As a result, it was an incredible week for us. Since we unveiled our AI computing platform for autonomous vehicles at CES last year, DRIVE PX 2 has become the core of the AI revolution sweeping the auto industry. That became clear with the show's opening keynote Wednesday from NVIDIA Co-Founder and CEO Jen-Hsun Huang, who announced our new AI Co-Pilot for the car built on DRIVE PX 2, as well as our ever expanding AI Car ecosystem of partners.
NVIDIA today unveiled the NVIDIA DGX-1, the world's first deep learning supercomputer to meet the unlimited computing demands of artificial intelligence. The NVIDIA DGX-1 is the first system designed specifically for deep learning -- it comes fully integrated with hardware, deep learning software and development tools for quick, easy deployment. It is a turnkey system that contains a new generation of GPU accelerators, delivering the equivalent throughput of 250 x86 servers.1 The DGX-1 deep learning system enables researchers and data scientists to easily harness the power of GPU-accelerated computing to create a new class of intelligent machines that learn, see and perceive the world as humans do. It delivers unprecedented levels of computing power to drive next-generation AI applications, allowing researchers to dramatically reduce the time to train larger, more sophisticated deep neural networks. NVIDIA designed the DGX-1 for a new computing model to power the AI revolution that is sweeping across science, enterprises and increasingly all aspects of daily life.
SANTA CLARA, CA--(Marketwired - Apr 17, 2017) - NVIDIA ( NASDAQ: NVDA) today announced that its deep learning platform is now available as part of Baidu Cloud's deep learning service, giving enterprise customers instant access to the world's most adopted AI tools. The new Baidu Cloud offers the latest GPU computing technology, including Pascal architecture-based NVIDIA Tesla P40 GPUs and NVIDIA deep learning software. It provides both training and inference acceleration for open-source deep learning frameworks, such as TensorFlow and PaddlePaddle. "Baidu and NVIDIA are long-time partners in advancing the state of the art in AI," said Ian Buck, general manager of Accelerated Computing at NVIDIA. "Baidu understands that enterprises need GPU computing to process the massive volumes of data needed for deep learning.