1 October 21st, 2016

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Deep Learning is the fastest-growing field in artificial intelligence (AI).

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Ranking #1 on Gartner’s Top 10 Strategic Technology Trends for

20171. AI and Advanced Machine Learning

2. Intelligent Apps3. Intelligent Things4. VR and AR5. Digital Twin6. Blockchain and Distributed Ledgers7. Conversational Systems8. MeshApp and Service Architecture9. Digital Technology Platforms10. Adaptive Security Architecture

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“Applied AI and advanced machine learning give rise to a

spectrum of intelligent implementations, including physical devices as well as apps and services These implementations will be

delivered as a new class of obviously intelligent apps as well as provide embedded

intelligence for a wide range of mesh devices and existing

software and service solutions.” -David Cearley

Vice President and Gartner Fellow in Gartner Research

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For More Information on Gartner’s Top 10 Strategic Technology Trends for 2017

READ HERE

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Changing the Landscape with Deep Learning and Accelerated Analytics

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Here are the “Top Five” stories highlighting how Deep Learning and AI are accelerating innovation this week…

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Gartner: AI To Become a Top Business Investment Priority

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1It's a technology that businesses will increasingly trust in decision-making, Gartner analysts said Monday at the research firm's annual Symposium/ITxpo here. In the next three to five years, Gartner predicts that 50 percent of all analytical interactions will be delivered via artificial intelligence, and many of the insights will be gleaned through verbal interactions. People already know and interact with A.I. systems through IBM's Watson, IPSoft's Amelia, Apple's Siri, Microsoft's Cortana and Google Assistant.

PCWorld ArticleKeep up HERE with the latest Deep Learning and AI News

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Microsoft Reach Human Parity in Conversational Speech Recognition

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2Microsoft has made a major breakthrough in speech recognition, creating a technology that recognizes the words in a conversation as well as a person does. In a paper published Monday, a team of researchers and engineers in Microsoft Artificial Intelligence and Research reported a speech recognition system that makes the same or fewer errors than professional transcriptionists. The researchers reported a word error rate (WER) of 5.9 percent, down from the 6.3 percent WER the team reported just last month.

Microsoft Blog ArticleExplore HERE on Microsoft’s other application with GPUs

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What Deep Learning Can Do For Your Business

NVIDIA Blog Article

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3It’s easy to understand that for companies like Google, Facebook, Amazon, Netflix and others, machine learning is a powerful tool. But as you can see from the above examples – beer, personal loans, oil wells, basketball – most businesses these days are, too, or will be soon. Most companies have jumped on that bandwagon. CEOs and CTOs recognized there was value in collecting all this data around their business processes. Phase two was about finding more sophisticated ways to query that data … Phase three, which we’re entering now, brings to bear machine learning techniques on the data.

Check out the other parts of the multi-part series explaining the fundamentals of deep learning by Michael Copeland HERE

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READ MORE

White House Push to Use AI For Cancer Research

Reuters Article

4The $1 billion moonshot project was announced by Obama during his State of the Union address in January. Since then Biden, whose son Beau died last year at age 46 from brain cancer, has announced multiple investments and collaborations in support of the project.The Cancer Moonshot initiative has also spurred Defense Department to use artificial intelligence to analyze its collection of tissue from tumors to look for patterns.The U.S. Patent and Trademark Office has launched a pilot program to cut in half the time to review certain cancer therapy patent applications from an average of about two years to less than 12 months.

Read HERE on Washington’s largest AI Conference being hosted by NVIDIA

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OLCF Dives Into Deep Learning with DGX-1 Supercomputer

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5The OLCF’s recent purchase of an NVIDIA DGX-1, the first supercomputer engineered specifically for deep learning, should help lab staff and users take scientific deep learning applications to the next level. Using multiple GPUs, the DGX-1’s optimized hardware and software make it easier for researchers to build and refine their models. “This system not only simplifies the development of deep learning algorithms but also cuts down on the time needed to optimize and port code, freeing up scientists to focus more on knowledge discovery,” said OLCF data and visualization expert Jamison Daniel.

ORNL Article

Check out our latest DGX-1 Delivery to NYU HERE

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How can Deep Learning Impact your Business?www.nvidia.com/deep-learning