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AtScale 6.0 and Kinetica 6.1 announced; SAP gets NVIDIA GPU religion

ZDNet

AtScale builds virtual (non-materialized) OLAP (online analytical processing) cubes over data in Hadoop, an approach which meshes nicely with front-end BI tools like Tableau which were designed for such models and repositories. But as it does so, people are increasingly understanding that federating that data with their more conventional database engines, including MPP (massively parallel processing) data warehouses, is imperative. Well, today's round of news includes a non-Tableau related item: NVIDIA GPUs are now finding their way into SAP data centers and, by extension, its cloud services too. Leonardo Machine Learning Foundation services -- including SAP Brand Impact, which automatically analyzes large volumes of videos to detect brand logos in moving images (and, by extension, ROI on product placements), and SAP Service Ticket Intelligence, which categorizes service tickets and provides resolution recommendations for the service center agent -- will feature NVIDIA Volta-trained models behind the scenes.


Proposition: No speed limit on NVIDIA Volta with rise of AI - IBM Systems Blog: In the Making

#artificialintelligence

We're excited about the launch of NVIDIA's Volta GPU accelerators.Together with the NVIDIA NVLink "information superhighway" at the core of our IBM Power Systems, it provides what we believe to be the closest thing to an unbounded platform for those working in machine learning and deep learning and those dealing with very large data sets. Servers with POWER9 and Volta, with its second-generation NVIDIA NVLink, PCI-Express 4, and Memory Coherence technologies, and unprecedented internal bandwidth, will blow people away. Our IBM and NVIDIA partnership around these new technologies will surface for the first time in the U.S. Department of Energy Summit Supercomputer at the Oak Ridge National Laboratory and the Sierra Supercomputer at the Lawrence Livermore National Laboratory, which are pushing the boundaries of big data science and simulation. AI applications data distributed deep learning gpu hardware IBM Cognitive Systems ibm power systems ibm power9 ibm powerai ibm research Lawrence Livermore National Laboratory Memory Coherence NVIDIA NVIDIA NVLink NVIDIA Volta Oak Ridge National Laboratory PCI-Express 4 power systems power9 Power9 chip powerai Sierra Supercomputer software Summit Supercomputer U.S. Department of Energy Your email address will not be published.Required fields are marked *


5 Reasons Why Your Data Science Team Needs The DGX Station

#artificialintelligence

I immediately pulled a container and started work on a CNTK NCCL project, the next day pulled another container to work on a TF biomedical project. By running Nvidia Optix 5.0 on a DGX Station, content creators can significantly accelerate training, inference and rendering (meaning both AI and graphics tasks). Flexibility to do AI work at the desk, data center, or edge The Fastest Personal Supercomputer for Researchers and Data Scientists 15. www.nvidia.com/dgx-station However, for our current projects we need a compute server that we have exclusive access to." By running Nvidia Optix 5.0 on a DGX Station, content creators can significantly accelerate training, inference and rendering (meaning both AI and graphics tasks).


Data scientists: Data Science is next big thing in decision-making - The Economic Times

@machinelearnbot

Sunrise Sectors: As per the Analytics India Report 2017, big data and decision sciences are the next sunrise sectors. Many of them admit that they haven't been able to leverage its benefits due to the shortfall in talent and because of this dearth of highly skilled human resources, professionals with big data skills will command huge salaries. TimesPro Decision Sciences: TimesPro, a part of Times Professional Learning, offers three avenues to explore decision sciences as a career through a combination of basic and advanced-level courses for students at different levels of understanding and growth in their careers. The three comprehensive programmes -- post-graduate diploma in data science, post-graduate diploma in advance data sciences and certificate in advance decision science -- are divided into modules, with a special focus on all important aspects of artificial intelligence (AI), analytics, internet of things, deep learning and machine learning.


Just What the Doctor Ordered: Smarter Systems for AI-Assisted Radiology The Official NVIDIA Blog

#artificialintelligence

The research team at the Center for Clinical Data Science (CCDS) today received the world's first purpose-built AI supercomputer from the all-new portfolio of NVIDIA DGX systems with Volta. In only eight months -- beginning in December when the center received NVIDIA's first generation DGX-1 AI supercomputer -- CCDS data scientists have successfully trained machines to "see" abnormalities and patterns in medical images. Now, having just received the world's first NVIDIA DGX-1 with Volta supercomputer and with an all-new DGX Station, the world's first personal AI supercomputer coming later this month, CCDS will build upon its groundbreaking research to develop a host of new training algorithms and bring the power of AI directly to doctors. The new DGX-1 with Volta delivers groundbreaking AI computing power three times faster than the prior DGX generation, providing the performance of up to 800 CPUs in a single system.


Want to be a software developer? Time to learn AI and data science

#artificialintelligence

It's also going to have a measurable impact on software development, with developers becoming more like data scientists, an AI official with Nvidia believes. "Coders are going to change their skill sets," with more data science and AI skills, McHugh said. Aside from its impacts on software development, McHugh said at the recent Global Artificial Intelligence Conference in Silicon Valley that AI would impact the internet of things (IoT), providing intelligent applications to work with IoT devices and process the collected data. Time to learn AI and data science" was originally published by InfoWorld.


Why the AI hype cycle won't end anytime soon

#artificialintelligence

Increasingly affordable AI maintenance and the increased speed of calculations thanks to GPU are significant factors in the unbridled growth of AI. The astonishing results that were achieved on training a neural network on GPU cards made Nvidia a key player, with 70 percent of the market share that Intel failed to gain. Compared with the results from the analog algorithms, and thanks to the combination of machine learning and big data, previously "unsolvable" problems are now being solved. Machine learning algorithms can directly analyze thousands of previous cases of different types of diseases and make their own conclusions as to what constitutes a sick individual versus a healthy individual, and consequently help diagnose dangerous conditions including cancer.


Why the AI hype cycle won't end anytime soon

#artificialintelligence

Increasingly affordable AI maintenance and the increased speed of calculations thanks to GPU are significant factors in the unbridled growth of AI. The astonishing results that were achieved on training a neural network on GPU cards made Nvidia a key player, with 70 percent of the market share that Intel failed to gain. Compared with the results from the analog algorithms, and thanks to the combination of machine learning and big data, previously "unsolvable" problems are now being solved. Machine learning algorithms can directly analyze thousands of previous cases of different types of diseases and make their own conclusions as to what constitutes a sick individual versus a healthy individual, and consequently help diagnose dangerous conditions including cancer.


Earnings Preview: What To Expect From Nvidia on Tuesday

Forbes

CES, the world's largest annual consumer technology trade show, runs through January 8 and features 3,800 exhibitors showing off their latest products and services to more than 165,000 attendees. Nvidia Corporation, incorporated on February 24, 1998, focuses on personal computer (PC) graphics, graphics processing unit (GPU) and also on artificial intelligence (AI). The Company's GPU product brands are aimed at specialized markets, including GeForce for gamers; Quadro for designers; Tesla and DGX for AI data scientists and big data researchers, and GRID for cloud-based visual computing users. The Company's Tegra brand integrates an entire computer onto a single chip, and incorporates GPUs and multi-core central processing units (CPUs) to drive supercomputing for mobile gaming and entertainment devices, as well as autonomous robots, drones and cars.


The democratization of the supercomputers

#artificialintelligence

Initially built as monolithic machines for highly niche applications such as weather forecasting, new drug discovery and academic research, HPC systems are now being routinely used in industries ranging from manufacturing and retailing to financial services and e-commerce. Market intelligence firm Intersect360 Research projects that the total HPC revenue worldwide, including sales of servers, storage systems and software, will grow at a compound annual growth rate (CAGR) of 5.2% over 2015-2020--reaching $36.9 billion in 2020 from $28.6 billion. The growth rate may appear slight at first glance, but becomes significant if one considers the fact that the overall server revenue has been declining globally: it declined 1.9% in the fourth quarter of 2016 and 5.8% in the third quarter of the same year, according to research firm Gartner Inc. Prakash Mallya, managing director, South Asia, Intel Corp., says that Intel has "a strong play in democratizing HPC". Research firm International Data Corporation's estimates show worldwide spending on AI is expected to grow to $47 billion in 2020, up from $8 billion in 2016.