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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.”

Apply Now for Summer of HPC 2017 in Barcelona

“The PRACE Summer of HPC is an outreach and training program that offers summer placements at top High Performance Computing centers across Europe to late-stage undergraduates and early-stage postgraduate students. Up to twenty top applicants from across Europe will be selected to participate. Participants will spend two months working on projects related to PRACE technical or industrial work and produce a report and a visualization or video of their results.”

Podcast: Engineering Practical Machine Learning Systems

In This Week in Machine Learning podcast, Xavier Amatriain from Quora discusses the process of engineering practical machine learning systems. Amatriainis a former machine learning researcher who went on to lead the recommender systems team at Netflix, and is now the vice president of engineering at Quora, the Q&A site. “What the heck is a multi-arm bandit and how can it help us.”

Experts Weigh in on 2017 Artificial Intelligence Predictions

In this presentation from Nvidia, top AI experts from the world’s most influential companies weigh in on predicted advances for AI in 2017. “In 2017, intelligence will trump speed. Over the last several decades, nations have competed on speed, intent to build the world’s fastest supercomputer,” said Ian Buck, VP of Accelerated computing at Nvidia. “In 2017, the race will shift. Nations of the world will compete on who has the smartest supercomputer, not solely the fastest.”

Podcast: Do It Yourself Deep Learning

In this AI Podcast, Bob Bond from Nvidia and Mike Senese from Make magazine discuss the Do It Yourself movement for Artificial Intelligence. “Deep learning isn’t just for research scientists anymore. Hobbyists can use consumer grade GPUs and open-source DNN software to tackle common household tasks from ant control to chasing away stray cats.”

Podcast: Deep Learning 101

In this AI Podcast, Host Michael Copeland speaks with NVIDIA’s Will Ramey about the history behind today’s AI boom and the key concepts you need to know to get your head around a technology that’s reshaping the world. “AI has been described as ‘Thor’s Hammer’ and ‘the new electricity.’ But it’s also a bit of a mystery – even to those who know it best. We’ll connect with some of the world’s leading AI experts to explain how it works, how it’s evolving, and how it intersects with every facet of human endeavor.”

GPU Accelerated Servers for Deep Learning Applications

Applications such as machine learning and deep learning require incredible compute power, and these are becoming more crucial to daily life every day. These applications help provide artificial intelligence for self-driving cars, climate prediction, drugs that treat today’s worst diseases, plus other solutions to more of our world’s most important challenges. There is a multitude of ways to increase compute power but one of the easiest is to use the most powerful GPUs.

New AMD Radeon Instinct Rolls Out to Accelerate Machine Intelligence

“New Radeon Instinct accelerators will offer organizations powerful GPU-based solutions for deep learning inference and training. Along with the new hardware offerings, AMD announced MIOpen, a free, open-source library for GPU accelerators intended to enable high-performance machine intelligence implementations, and new, optimized deep learning frameworks on AMD’s ROCm software to build the foundation of the next evolution of machine intelligence workloads.”

Nvidia Powers Deep Learning for Healthcare at SC16

In this video from SC16, Abdul Hamid Al Halabi from Nvidia describes how the company is accelerating Deep Learning for Healthcare. “From Electronic Health Records (EHR) to wearables, every year the flood of heterogeneous healthcare data increases exponentially. Deep learning has the power to unlock the potential within this data.Harnessing the power of GPUs, healthcare and medical researchers are able to design and train more sophisticated neural networks—networks that can accelerate high-throughput screening for drug discovery, guide pre-operative strategies, or work in conjunction with traditional techniques and apparatus to detect invasive cancer cells in real-time during surgery.”

Podcast: Where Deep Learning Is Going Next

In this Nvidia podcast, Bryan Catanzaro from Baidu describes how machines with Deep Learning capabilities are now better at recognizing objects in images than humans. “AI gets better and better until it kind of disappears into the background,” says Catanzaro — NVIDIA’s head of applied deep learning research — in conversation with host Michael Copeland on this week’s edition of the new AI Podcast. “Once you stop noticing that it’s there because it works so well — that’s when it’s really landed.”