In a brilliant Circulation article published last week, Siontis et al. count the ways with which machine learning could help treat atrial fibrillation. As you'll quickly find out, there are a lot of different teams out there trying different things. Atrial fibrillation (abbreviated as AF) is the most common arrhythmia in man. In AF, half of the cardiac chambers (the atria) stop contracting normally and start flailing about. In addition to the increased workload of the remaining cardiac chambers (the ventricles), AF also hugely increases the risk of stroke.

AI software innovator Mipsology today announced that its Zebra neural network accelerating software has been integrated into the latest build of Xilinx's Alveo U50 data center accelerator card, the industry's first low profile adaptable accelerator with PCIe Gen 4 support. Zebra's ease-of-use and high throughput enable the Alveo U50 to compute convolutional neural networks with zero effort. This is the latest in a series of Zebra-enhanced Xilinx boards that enable inference acceleration for a wide variety of sophisticated AI applications. "The level of acceleration that Zebra brings to our Alveo cards puts CPU and GPU accelerators to shame," said Ramine Roane, Xilinx's Vice President of marketing. "Combined with Zebra, Alveo U50 meets the flexibility and performance needs of AI workloads and offers high throughput and low latency performance advantages to any deployment."

You're just a few precious miles from home when heavy traffic and those three cups of coffee hit at the same moment. There isn't a bottle mouth big enough to handle the cold brew you've got gurgling in your gut. While we've all been caught out like this at some point down here on Earth, this week we have a glimpse at how NASA will provide bathroom facilities on the moon. Tesla may push the boundaries of automotive technology but its production process is a bit of a mess. In a recent initial quality survey from JD Power and Associates, Tesla customers reported 250 build defects (misaligned body panels, shoddy paintwork, things of that nature) per 100 vehicles.

Walter Bender, the Chief Learning Architect at Sorcero and the founder of Sugar Labs and One Laptop One Child, shared with IBL News how transparent AI will revolutionize online learning following his talk at the Open edX conference last month in San Diego. The main goal, he posits, is "to leverage what makes us human to become part of the learning process." His talk, "Beyond the Black Box: How Transparent AI can Transform Learning," focused on the strides that Sorcero is making with AI and online learning. With his extensive experience in academia and accessible and open online education, he says his experiences were "a case study for transparency, for providing tools and a framework." The natural extension from this was to switch gears and talk about AI, the "tool du jour in machine learning these days."

This is the second part of an article discussing new areas of game theory that are influencing deep reinforcement learning systems. The first part focused on types of games that we are actively seeing in multi-agent reinforcement learning systems. Today, I would like to cover three new areas of deep learning theory that can influence new generations of reinforcement learning systems. Game theory plays a fundamental factor in modern artificial intelligence(AI) solutions. Specifically, deep reinforcement learning(DRL) is an area of AI that embraced game theory as a first-class citize.

For years, Brent Hecht, an associate professor at Northwestern University who studies AI ethics, felt like a voice crying in the wilderness. When he entered the field in 2008, "I recall just agonizing about how to get people to understand and be interested and get a sense of how powerful some of the risks [of AI research] could be," he says. To be sure, Hecht wasn't--and isn't--the only academic studying the societal impacts of AI. But the group is small. "In terms of responsible AI, it is a sideshow for most institutions," Hecht says.

Naheed Kurji is the President and CEO of Cyclica, a Toronto-based biotechnology company that leverages artificial intelligence and computational biophysics to reshape the drug discovery process. Cyclica leverages artificial intelligence and computational biophysics to reshape the drug discovery process. Can you discuss in what way AI is used in this process? Technology has played a critical role in drug discovery dating back to the '80s. However, the drug discovery and development process is still very inefficient, time consuming and expensive, costing more than 2 billion dollars over 12 years.

Baidu will no longer participate in the Partnership on AI (PAI) alliance amid deteriorating relations between the US and China. PAI is a US-led alliance which aims to foster the ethical development and deployment of AI technologies. Baidu was the only Chinese member. The loss of Baidu's expertise and any representation from China is devastating for PAI. Ethical AI development requires global cooperation to set acceptable standards which help to ensure safety while not limiting innovation.

Almost three years ago, Bill Gates wrote an open letter to the graduating class of 2017 and it's still very relevant today. He offered advice for those looking to make a big impact in the world, and three fields they should consider: artificial intelligence, energy and biosciences. We have only begun to tap into all the ways it will make people's lives more productive and creative. The second is energy, because making it clean, affordable, and reliable will be essential for fighting poverty and climate change. The third is the biosciences, which are ripe with opportunities to help people live longer, healthier lives."

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