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Rapid GPU Evolution at Chinese Web Giant Tencent

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Like other major hyperscale web companies, China's Tencent, which operates a massive network of ad, social, business, and media platforms, is increasingly reliant on two trends to keep pace. The first is not surprising--efficient, scalable cloud computing to serve internal and user demand. The second is more recent and includes a wide breadth of deep learning applications, including the company's own internally developed Mariana platform, which powers many user-facing services. When the company introduced its deep learning platform back in 2014 (at a time when companies like Baidu, Google, and others were expanding their GPU counts for speech and image recognition applications) they noted their main challenges were in providing adequate compute power and parallelism for fast model training. "For example," Mariana's creators explain, "the acoustic model of automatic speech recognition for Chinese and English in Tencent WeChat adopts a deep neural network with more than 50 million parameters, more than 15,000 senones (tied triphone model represented by one output node in a DNN output layer) and tens of billions of samples, so it would take years to train this model by a single CPU server or off-the-shelf GPU."


Can AI End Checkout Lines? NVIDIA Blog

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New Zealand's IMAGR and Silicon Valley's Mashgin aim to make checking out of grocery stores and company cafeterias a walk in the park. IMAGR makes SmartCart, an ordinary grocery cart with an AI computing video camera attached. Mashgin customizes its system for each company's cafeteria, and its deep learning algorithm learns new items as more people use it. Using our TITAN X GPU and the TensorFlow deep learning framework, IMAGR initially trained its algorithms on images of grocery store products.


IBM and Nvidia make deep learning easy for AI service creators with a new bundle

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On Monday, IBM announced that it collaborated with Nvidia to provide a complete package for customers wanting to jump right into the deep learning market without all the hassles of determining and setting up the perfect combination of hardware and software. The company also revealed that a cloud-based model is available as well that eliminates the need to install local hardware and software. To trace this project, we have to jump back to September when IBM launched a new series of "OpenPower" servers that rely on the company's Power8 processor. The launch was notable because this chip features integrated NVLink technology, a proprietary communications link created by Nvidia that directly connects the central processor to a Nvidia-based graphics processor, namely the Tesla P100 in this case. Server-focused x86 processors provided by Intel and AMD don't have this type of integrated connectivity between the CPU and GPU.


Supermicro(R) Introduces NVIDIA(R) Pasca(TM) GPU-Enabled Server Solutions Featuring NVIDIA Tesla(R) P100 GPUs

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Super Micro Computer, Inc. (SMCI), a global leader in compute, storage, networking technologies and green computing today announced the general availability of its SuperServer solutions optimized for NVIDIA Tesla P100 accelerators with the new Pascal GPU architecture. "The new SuperServers deliver superior energy-efficient performance for compute-intensive data analytics, deep learning and scientific applications while minimizing power consumption." With the convergence of Big Data Analytics, the latest GPU architectures, and improved Machine Learning algorithms, Deep Learning applications require processing power of multiple GPUs that must communicate efficiently and effectively to expand the GPU network. Supermicro (SMCI), the leading innovator in high-performance, high-efficiency server technology is a premier provider of advanced server Building Block Solutions for Data Center, Cloud Computing, Enterprise IT, Hadoop/Big Data, HPC and Embedded Systems worldwide.


Nvidia CEO bets on artificial intelligence as the future of computing

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Huang said deep learning will be the basis for the entire computer industry, including data centers and the cloud, for years to come. Huang also said he believes AI and deep learning will transform data centers and cloud services. Rajat Monga, a Google technical lead and manager of TensorFlow, an open source software library for machine learning that was developed at Google, said the company thinks deep learning will infuse every Google service, including new areas such as robotics. It's what he called the world's first car computing platform powered by deep learning.