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Podcast: Cybersecurity Challenges in a World of AI

“From home assistants like the Amazon Echo to Google’s self-driving cars, artificial intelligence is slowly creeping into our lives. These new technologies could be enormously beneficial, but they also offer hackers unique opportunities to harm us. For instance, a self-driving car isn’t just a robot—it’s also an internet-connected device, and may even have a cell phone number.”

Artificial Intelligence: It’s No Longer Science Fiction

“Computational science has come a long way with machine learning (ML) and deep learning (DL) in just the last year. Leading centers of high-performance computing are making great strides in developing and running ML/DL workloads on their systems. Users and algorithm scientists are continuing to optimize their codes and techniques that run their algorithms, while system architects work out the challenges they still face on various system architectures. At SC16, I had the honor of hosting three of HPC’s thought leaders in a panel to get their ideas about the state of Artificial Intelligence (AI), today’s challenges with the technology, and where it’s going.”

Deep Learning & HPC: New Challenges for Large Scale Computing

“In recent years, major breakthroughs were achieved in different fields using deep learning. From image segmentation, speech recognition or self-driving cars, deep learning is everywhere. Performance of image classification, segmentation, localization have reached levels not seen before thanks to GPUs and large scale GPU-based deployments, leading deep learning to be a first class HPC workload.”

Defining AI, Machine Learning, and Deep Learning

“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 also present the results of a recent insideBIGDATA survey 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.”

Agenda Posted for Next Week’s HPC Advisory Council Stanford Conference

“Over two days we’ll delve into a wide range of interests and best practices – in applications, tools and techniques and share new insights on the trends, technologies and collaborative partnerships that foster this robust ecosystem. Designed to be highly interactive, the open forum will feature industry notables in keynotes, technical sessions, workshops and tutorials. These highly regarded subject matter experts (SME’s) will share their works and wisdom covering everything from established HPC disciplines to emerging usage models from old-school architectures and breakthrough applications to pioneering research and provocative results. Plus a healthy smattering of conversation and controversy on endeavors in Exascale, Big Data, Artificial Intelligence, Machine Learning and much much more!”

IBM Adds TensorFlow Support for PowerAI Deep Learning

Today IBM announced that its PowerAI distribution for popular open source Machine Learning and Deep Learning frameworks on the POWER8 architecture now supports the TensorFlow 0.12 framework that was originally created by Google. TensorFlow support through IBM PowerAI provides enterprises with another option for fast, flexible, and production-ready tools and support for developing advanced machine learning products and systems.

CUDA Made Easy: An Introduction

“CUDA C++ is just one of the ways you can create massively parallel applications with CUDA. It lets you use the powerful C++ programming language to develop high performance algorithms accelerated by thousands of parallel threads running on GPUs. Many developers have accelerated their computation- and bandwidth-hungry applications this way, including the libraries and frameworks that underpin the ongoing revolution in artificial intelligence known as Deep Learning.”

Podcast: Supercomputing Cancer Research and the Human Brain

In this WUOT podcast, Jack Wells from ORNL describes how the Titan supercomputer helps advance science. “The world’s third-most powerful supercomputer is located in Oak Ridge, and though it bears the imposing name TITAN, its goals and capabilities are more quotidian than dystopian. After that, WUOT’s Megan Jamerson tells us about a project at ORNL that uses TITAN to help humans digest vast sums of information from medical reports. If successful, the project could create new understandings about the demographics of cancer.”

Video: AI – The Next HPC Workload

“From new cloud offerings on AWS and Azure, to Summit and Sierra, the 150+ PF supercomputers being built by the US in 2017, new AI workloads are driving the rapid growth of GPU accelerated HPC systems. For years, HPC simulations have generated ever increasing amounts of big data, a trend further accelerated by GPU computing. With GPU Deep Learning and other AI approaches, a larger amount of big data than ever can now be used to advance scientific discovery.”

Podcast: How Deep Learning Will Reshape Our Cities

In this AI Podcast, Lynn Richards, president and CEO of the Congress for New Urbanism and Charles Marohn, president and co-founder of Strong Towns, describe how AI will reshape our cities. “AI will do much more than automate driving. It promises to help create more liveable cities. And help put expensive infrastructure where we need it most.”