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Andrew Ng Leaving Baidu for Next Chapter in AI

“As the founding lead of the Google Brain project, and more recently through my role at Baidu, I have played a role in the transformation of two leading technology companies into “AI companies.” But AI’s potential is far bigger than its impact on technology companies. I will continue my work to shepherd in this important societal change. In addition to transforming large companies to use AI, there are also rich opportunities for entrepreneurship as well as further AI research.”

Intel’s Diane Bryant on How AI Will Change Lives

“Artificial Intelligence will deliver the next wave of societal transformation on parallel with the industrial, technical and internet revolutions that preceded it. As our AI-fueled future evolves, we have a tremendous opportunity to address opportunities from scare resource utilization and scientific exploration to inclusion and human rights expansion. Intel Executive VP Diane Bryant will share Intel’s vision for unleashing AI as well as a perspective on how to accelerate the delivery of #AIforgood.”

Overview of the HGX-1 AI Accelerator Chassis

“The Project Olympus hyperscale GPU accelerator chassis for AI, also referred to as HGX-1, is designed to support eight of the latest “Pascal” generation NVIDIA GPUs and NVIDIA’s NVLink high speed multi-GPU interconnect technology, and provides high bandwidth interconnectivity for up to 32 GPUs by connecting four HGX-1 together. The HGX-1 AI accelerator provides extreme performance scalability to meet the demanding requirements of fast growing machine learning workloads, and its unique design allows it to be easily adopted into existing datacenters around the world.”

Day-Long Deep Learning Track Comes to ISC 2017

Today ISC 2017 announced a day-long Deep Learning track on June 21 as part of its technical program. The full conference takes place June 18-21 in Frankfurt, Germany. “The overwhelming success of deep learning has triggered a race to build larger artificial neural networks, using growing amounts of training data in order to allow computers to take on more complex tasks. Such work will challenge the computational feasibility of deep learning of this magnitude, requiring massive data throughput and compute power. Hence, implementing deep learning at scale has become an emerging topic for the high performance computing community.”

Podcast: Using GPUs and AI to Fight Cybercrime

“Cybersecurity is a cat-and-mouse game where the mouse always has long had the upper hand because it’s so easy for new malware to go undetected. Dr. Eli David, an expert in computational intelligence and CTO of Deep Instinct, wants to use AI to change that, bringing the GPU-powered deep learning techniques underpinning modern speech and image recognition to the vexing world of cybersecurity.”

Nvidia Brings AI to the Cloud with the HGX-1 Hyperscale GPU Accelerator

Today, Microsoft, NVIDIA, and Ingrasys announced a new industry standard design to accelerate Artificial Intelligence in the next generation cloud. “Powered by eight NVIDIA Tesla P100 GPUs in each chassis, HGX-1 features an innovative switching design based on NVIDIA NVLink interconnect technology and the PCIe standard, enabling a CPU to dynamically connect to any number of GPUs. This allows cloud service providers that standardize on the HGX-1 infrastructure to offer customers a range of CPU and GPU machine instance configurations.”

Andrew Ng on why Artificial Intelligence is the New Electricity

“Electricity transformed industries: agriculture, transportation, communication, manufacturing. I think we are now in that phase where AI technology has advanced to the point where we see a clear path for it to transform multiple industries.” Specifically, Ng sees AI being particularly influential in entertainment, retail, and logistics.

Podcast: How Humans Bias AI

In this AI Podcast, Kris Hammond from Narrative Science explains that while it’s easy to think of AI as cold, unbiased, and objective, it is also very good at repeating our own bias against us. “I am not saying that we should give ourselves over to algorithmic decision-making. We should always remember that just as the machine is free of the cognitive biases that often defeat us, we have information about the world that the machine does not. My argument is that, with intelligent systems, we now have the opportunity to be genuinely smarter.”

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.”