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The Intersection of AI and HPC

The insideBIGDATA Guide to Deep Learning & Artificial Intelligence is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting area of technology. This is the third in a series of articles providing content extracted from the guide. The topic for this segment is the intersection of artificial intelligence (AI) and high performance computing (HPC).

Dr. Eng Lim Goh on New Trends in Big Data and Deep Learning for Artificial Intelligence

In this video from SC16, Dr. Eng Lim Goh from HPE/SGI discusses new trends in HPC Energy Efficiency and Deep Learning for Artificial Intelligence. “Recently acquired by Hewlett Packard Enterprise, SGI is a trusted leader in technical computing with a focus on helping customers solve their most demanding business and technology challenges.”

The Difference between AI, Machine Learning and Deep Learning

The insideBIGDATA Guide to Deep Learning & Artificial Intelligence is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting area of technology. This is the second in a series of articles providing content extracted from the guide. The topic for this segment is the difference between AI, machine learning and deep learning.

insideBIGDATA Guide to Deep Learning and Artificial Intelligence

The insideBIGDATA Guide to Deep Learning & Artificial Intelligence is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting area of technology. In this guide, we take a high-level view of AI and deep learning in terms of how it’s being used and what technological advances have made it possible. We also explain the difference between AI, machine learning and deep learning, and examine the intersection of AI and HPC. We present the results of a recent insideBIGDATA survey, “insideHPC / insideBIGDATA AI/Deep Learning Survey 2016,” to see how well these new technologies are being received. Finally, we take a look at a number of high-profile use case examples showing the effective use of AI in a variety of problem domains.

insideBIGDATA Guide to Artificial Intelligence & Deep Learning

In this guide we explain the difference between AI, machine learning and deep learning, and includes highlights of the insideBIGDATA audience survey. To learn more about AI and deep learning download this guide.

ZTE Wireless Institute Achieves Performance Breakthrough for Deep Learning with Intel FPGAs

Intel and ZTE, a leading technology telecommunications equipment and systems company, have worked together to reach a new benchmark in deep learning and convolutional neural networks (CNN). The technology is what many companies in Internet search and AI are trying to advance, and includes picture search and matching, as one example.

Deep Learning by Yann LeCun

The Institute for Scientific Computing Research (ISCR) sponsored the talk below entitled “Deep Learning” on April 16, 2015, at the Lawrence Livermore National Laboratory. The talk was presented by Yann LeCun, director of AI research at Facebook and professor of data science, computer science, neural science and electrical engineering at NYU.

Personalization and Scalable Deep Learning with MXNET

The presentation below by Alex Smola is “Personalization and Scalable Deep Learning with MXNET” from the MLconf San Francisco, 2016. User return times and movie preferences are inherently time dependent. In this talk, Alex shows how this can be accomplished efficiently using deep learning by employing an LSTM (Long Short Term Model). Moreover, he shows how to train large scale distributed parallel models using MXNet efficiently.

Cross-Channel Advertising with Large-Scale Consumer Graphs

In this contributed article, Deb Ray, Chief Data Officer at VideoAmp discusses an important technique where the complexity of cross-channel targeting and measurement is solved by building a large-scale graph of consumers and their connected devices.

Cray Works with Industry Leaders to Reach New Performance Milestone for Deep Learning at Scale

Cray Inc. announced the results of a deep learning collaboration between Cray, Microsoft, and the Swiss National Supercomputing Centre (CSCS) that expands the horizons of running deep learning algorithms at scale using the power of Cray supercomputers. Running larger deep learning models is a path to new scientific possibilities, but conventional systems and architectures limit the problems that can be addressed, as models take too long to train. Cray worked with Microsoft and CSCS, a world-class scientific computing center, to leverage their decades of high performance computing expertise to profoundly scale the Microsoft Cognitive Toolkit.