In his SC17 presentation, NVIDIA CEO Jensen Huang said the company’s Volta architecture for GPUs is now available on every major cloud service to deliver AI and HPC.
Insights: Machine Learning and Artificial Intelligence
Machine learning and artificial intelligence have arrived in the data center, changing the face of the hyperscale server farm as racks begin to fill with ASICs, GPUs, FPGAs and supercomputers. The race to leverage machine learning is led by the industry’s marquee names, including Google, Facebook and IBM. As usual, the battlefield runs through the data center, with implications for the major cloud platforms and chipmakers like Intel and NVIDIA.
Avitas Systems’ drone inspection service is bringing AI data-crunching to remote locations with the NVIDIA DGX Station “supercomputer in a box.”
This week Microsoft unveiled Project Brainwave, a deep learning acceleration platform the latest fruits of its collaboration with Intel on FPGA-based computing.
Artificial intelligence experts showed off impressive new applications of AI at the O”Reilly Artificial Intelligence Conference, but also wrestled with the tensions about hype, language and the societal impact of this technology.
Will artificial intelligence and robotics manage the data centers of the future? At DCD Webscale, LitBit and Wave2Wave discussed new AI products to streamline data center management and address the industry’s staffing challenges.
The rise of specialized computing is bringing powerful new server hardware into the data center, a trend seen in new tech from Google, NVIDIA, AMD, ARM, Intel and Microsoft.
NVIDIA is looking to accelerate sales of its AI hardware to hyperscale computing providers through tighter partnerships with original design manufacturers (ODMs), who have become key players in the cloud hardware ecosystem.
The data center’s role in the economy will be transformed by technologies like AI, virtual reality, voice assistants, autonomous vehicles and robots, according to futurist Steve Brown.
At the Open Compute Summit, Microsoft and NVIDIA unveiled a new hyperscale GPU accelerator for artificial intelligence workloads in the cloud. The HGX-1 harnesses eight NVIDIA Tesla P100 GPUs and high-speed interconnects.
Ponemon Institute and Vertiv are pleased to present the results of an original benchmark study to determine average costs to support 1 kW of compute capacity in today’s data centers. The purpose of this study is to analyze the major cost components in supporting compute capacity so that organizations can more effectively identify opportunities to reduce costs and make informed decisions about future capacity. To learn more download this white paper.