In this special guest feature, Carla Leibowitz, Head of Strategy and Marketing at Arterys, discusses how deep learning tools can aid physicians in determining a patient’s condition more quickly and accurately and what promise this holds for personalized care.
In this contributed article, Arun Goyal, Founder at Octal Info Solution, discusses how big data is positioned to influence AI as a major disruption in the industry.
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 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.
Lexalytics®, on leader in cloud and on-prem text analytics solutions, announced that it is unveiling the Magic Machines™ AI Labs in Amherst, MA, to speed innovation in artificial intelligence (AI). In stealth mode for the past year, Magic Machines has been focusing on “force-multiplying” AI technologies.
Conversica, Inc., a leader in artificial intelligence-powered business conversations, announced significant enhancements to its flagship product, the Conversica® AI Sales Assistant. Conversica leverages artificial intelligence (AI) to take on routine business conversations like contacting and qualifying sales leads, freeing up human salespeople to close more deals.
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.
Loom Systems, announced an AI-powered operational analytics platform used for real-time detection and resolution for any type of application. Targeted at DevOps and IT professionals, Loom instantly analyzes logs and semi-structured machine data for immediate visibility into a company’s digital environment.
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.
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.