SambaNova says just one quarter of a rack's worth of its DataScale computer can replace 64 separate Nvidia DGX-2 machines taking up multiple racks of equipment, when crunching various deep learning tasks such as natural language processing tasks on neural networks with billions of parameters such as Google's BERT-Large. The still very young market for artificial intelligence computers is spawning interesting business models. On Wednesday, SambaNova Systems, the Palo Alto-based startup that has received almost half a billion dollars in venture capital money, announced general availability of its dedicated AI computer, the DataScale and also announced an as-a-service offering where you can have the machine placed in your data center and rent its capacity for $10,000 a month. "What this is, is a way for people to gain quick and easy access at an entry price of $10,000 per month, and consume DataScale product as a service," said Marshall Choy, Vice President of product at SambaNova, in an interview with ZDNet via video. "I'll roll a rack, or many racks, into their data center, I'll own and manage and support the hardware for them, so they truly can just consume this product as a service offering."
We are now looking for a Senior Deep Learning Research Scientist: NVIDIA is searching for a world-class researcher in deep learning to join our applied research team. We are passionate about deep learning applied to computer vision, audio, text and other domains, with the goal of improving specific problems encountered in NVIDIA's products. After building prototypes that demonstrate the promise of your research, you will work with product teams to help them integrate your ideas into products. If you're interested in researching and applying the latest advances in the deep learning revolution to solve real-life problems, this team may be an outstanding fit for you! What You'll Be Doing Conceive deep learning approaches to solving particular product problems.
We invite you to join Intel's Next Generation & Standards (NGS) Group and the 5G revolution! We are a global team of passionate engineers and technologists from diverse industry backgrounds, working together to realize a world of connected computing. Intel's NGS team is chartered with developing advanced prototypes of various technologies to deliver innovative and state of the art wireless experiences into the market within the Internet of Things, 5G Next Generation Wearable and IoT solutions and other world-class wireless connectivity technologies and products. The Next Generation and Standards Group's mission is to lead standards, ecosystem, and prototyping development efforts across Intel for advanced wireless communications IP, starting with 5G and beyond. This group brings together a panorama of competencies including standards creation, ecosystem development, use case and business development in creating advanced prototypes and technologies that propel Intel's leadership.
Photoshop could become a thing of the past thanks to new technology that can touch-up badly damaged photos. The Nvidia software uses AI and deep-learning algorithms to predict what a missing portion of a picture should look like and recreate it with incredible accuracy. As well as restoring old physical photos that have been damaged, the technique could also be used to fix corrupted pixels or bad edits made to digital files. Graphics specialist Nvidia, based in Santa Clara, California trained its neural network using a variety of irregular shaped holes in images. The system then determined what was missing from each and filled in the gaps.
This proclamation, from NVIDIA co-founder, president, and CEO Jensen Huang at the GPU Technology Conference (GTC), held from March 26 to March 29 in San Jose, Calif., only hints at this company's growing impact on state-of-the-art computing. Read also: Nvidia's new supercomputer Clara designed to act as hospital processing hub Nvidia's physical products are accelerators (for third-party hardware) and the company's own GPU-powered workstations and servers. Jensen Huang, co-founder, president, and CEO at Nvidia, presents the sweep of the company's growing AI Platform at GTC 2018 in San Jose, Calif. On the hardware front, the headlines from GTX built on the foundation of Nvidia's graphical processing unit advances. If the "feeds and speeds" stats mean nothing to you, let's put them into the context of real workloads.
Nvidia launched hardware and software improvements to its deep learning computing platform that deliver a 10 times performance boost on deep learning workloads compared with the previous generation six months ago. In the past five years, programmers have made huge advances in AI, first by training deep learning neural networks based on existing data. This allows a neural network to recognize an image of a cat, for instance. The second step is inferencing, or applying the learning capability to new data that has never been seen before, like spotting a cat in a picture that the neural network has never been shown. At the GPU Technology Conference (GTC) event in San Jose, California, Nvidia CEO Jensen Huang didn't announce a new graphics processing unit (GPU).
Abeja: This Japanese startup, founded in 2012, creates AI software for retailers and manufacturers and is backed by Salesforce and NTT DOCOMO, among others. Deepgram: This Mountain, View, Calif., startup has created AI that understands human speech. Deepgram's goal: help computers understand what you mean, communicate in real time and leave you satisfied, not frustrated. Deep Instinct: This Tel Aviv startup pioneered the use of AI zero-day attack protection -- using deep learning to identify attacks on vulnerabilities that haven't yet been made public. Entropix: You know those crime shows that show computer-equipped sleuth's enhancing grainy images?
You won't need to buy a rack of 400 servers if you have one high-powered Nvidia DGX-1 supercomputer with a Volta GPU sitting on your desktop. The DGX-1 supercomputer -- which looks like a regular rack server -- gets most of its computing power from eight Tesla V100 GPUs. The GPU, the first one based on the brand-new Volta architecture, was introduced at the company's GPU Technology Conference in San Jose, California, on Wednesday. "It comes out of the box, plug it in and go to work," said Nvidia's CEO Jen-Hsun Huang during a keynote speech. But the DGX-1 with Tesla V100 computer is expensive.
H2O.ai and Nvidia today announced that they have partnered to take machine learning and deep learning algorithms to the enterprise through deals with Nvidia's graphics processing units (GPUs). Mountain View, Calif.-based H20.ai has created AI software that enables customers to train machine learning and deep learning models up to 75 times faster than conventional central processing unit (CPU) solutions. The company made the announcement at Nvidia's GPU Tech event in San Jose, Calif. H2O.ai will offer its machine learning algorithms in a newly minted GPU-edition and its Deep Water product on Nvidia GPUs. In addition, H2O.ai's platform will now be optimized for the Nvidia's DGX-1 AI processor.
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.