Professor Yale Patt, the Ernest Cockrell, Jr. Centennial Chair in Engineering at The University of Texas at Austin has been named the 2016 recipient of the Benjamin Franklin Medal in Computer and Cognitive Science by the Franklin Institute. Patt is a renowned computer architect, whose research has resulted in transformational changes to the nature of high-performance microprocessors, including the first complex logic gate implemented on a single piece of silicon. He has received ACM's highest honors both in computer architecture (the 1996 Eckert-Mauchly Award) and in education (the 2000 Karl V. Karlstrom Award). He is a Fellow of the ACM and the IEEE and a member of the National Academy of Engineering. Derek Chiou, an associate professor of Electrical and Computer Engineering at The University of Texas at Austin, conducted an extensive interview of Patt, covering his formative years to his Ph.D. in 1966, his career since then, and his views on a number of issues. Presented here are excerpts from that interview; the full interview is available via the link appearing on the last page of this interview. DEREK CHIOU: Let's start with the influences that helped shape you into who you are. I have often heard you comment on your actions as, "That's the way my mother raised me." YALE PATT: In my view my mother was the most incredible human being who ever lived. Born in Eastern Europe, with her parents' permission, at the age of 20, she came to America by herself. A poor immigrant, she met and married my father, also from a poor immigrant family, and they raised three children. We grew up in one of the poorer sections of Boston. Because of my mother's insistence, I was the first from that neighborhood to go to college. My brother was the second. My sister was the third. You have often said that as far as your professional life is concerned, she taught you three important lessons. Almost everyone in our neighborhood quit school when they turned 16 and went to work in the Converse Rubber factory, which was maybe 100 yards from our apartment. She would have none of it.

The University of Washington School of Law is delighted to announce a public workshop on the law and policy of artificial intelligence, co-hosted by the White House and UW's Tech Policy Lab. The event places leading artificial intelligence experts from academia and industry in conversation with government officials interested in developing a wise and effective policy framework for this increasingly important technology. The event is free and open to the public but requires registration. Jack M. Balkin is Knight Professor of Constitutional Law and the First Amendment at Yale Law School. He is the founder and director of Yale's Information Society Project, an interdisciplinary center that studies law and new information technologies.

Overwatch sounds like a game I shouldn't want to play: a hero-focused team shooter that seems aimed at players given to godlike acts of ballistic skill. But I should know better. This is Blizzard we're talking about, after all, a studio that turned a generic fantasy-verse born from a niche real-time strategy game into a global online roleplaying sensation. After chatting with Overwatch co-director Jeffrey Kaplan, I'm almost convinced it's a game for me--the sort of lapsed, Quake-era clanner who has lost interest in competitive shooters. Here, by way of our lightly edited conversation, is a rundown of why.

Martha Kim is an Associate Professor of Computer Science at Columbia University. She holds a PhD in Computer Science and Engineering from the University of Washington and a bachelors in Computer Science from Harvard University. Martha's research interests are in computer architecture, parallel programming, compilers, and low-power computing. Her current research focuses on hardware and software techniques to improve the usability of hardware accelerators, data-centric accelerator design, and application-level power management. This work has been funded by the National Science Foundation, DARPA, the Center for Future Architectures Research (C-FAR), and Intel Corporation.

The killing of Afghan Taliban leader Mullah Mohammed Akhtar Mansour in a U.S. drone strike was greeted Sunday by Kabul's political leadership as a game-changer in efforts to end the long insurgent war plaguing Afghanistan. In a rare show of unity, President Ashraf Ghani and Chief Executive Abdullah Abdullah both welcomed the news of Mansour's death as the removal of a man who unleashed violence against innocent civilians in Afghanistan and was widely regarded as an obstacle to peace within the militant group. Mansour, believed to be in his 50s, was killed when a U.S. drone fired on his vehicle in the southwestern Pakistan province of Baluchistan, although there were conflicting accounts whether the airstrike occurred Friday or Saturday. He had emerged as the successor to Taliban founder Mullah Mohammad Omar, whose 2013 death was only revealed last summer. Mansour "engaged in deception, concealment of facts, drug-smuggling and terrorism while intimidating, maiming and killing innocent Afghans," Ghani said in a statement on his official Twitter account.

I love the feeling of having a new way to think about the world. I especially love when there's some vague idea that gets formalized into a concrete concept. Information theory is a prime example of this. Information theory gives us precise language for describing a lot of things. How uncertain am I? How much does knowing the answer to question A tell me about the answer to question B? How similar is one set of beliefs to another? I've had informal versions of these ideas since I was a young child, but information theory crystallizes them into precise, powerful ideas. These ideas have an enormous variety of applications, from the compression of data, to quantum physics, to machine learning, and vast fields in between. Unfortunately, information theory can seem kind of intimidating. I don't think there's any reason it should be. In fact, many core ideas can be explained completely visually! Before we dive into information theory, let's think about how we can visualize simple probability distributions. We'll need this later on, and it's convenient to address now. As a bonus, these tricks for visualizing probability are pretty useful in and of themselves! Sometimes it rains, but mostly there's sun! Let's say it's sunny 75% of the time. It's easy to make a picture of that: Most days, I wear a t-shirt, but some days I wear a coat. Let's say I wear a coat 38% of the time. It's also easy to make a picture for that! What if I want to visualize both at the same time?

Everywhere you turn these days there are more and more automated processes appearing all the time. From automatic vacuum cleaners to self-order counters at restaurants, to cars that automatically park themselves, robots are all around us in one way or another and physics is no different. In using the latest artificial intelligence to do the same tasks as people, we are not only saving time and money but saving on resources too. A recent physics experiment developed by physicists from The Australian National University (ANU) and the University of New South Wales at the Australian Defence Force Academy (UNSW ADFA) was shown to be completed by artificial intelligence (AI) just as a human would. The test was to create a replica of "Laser Beam" experiment that won the 2001 Nobel Prize and produced an extremely cold gas trapped in a laser beam (known as Bose-Einstein condensate) and the incredible AI literally taught itself how to do the experiment, from start to finish, in under one hour!

Professor Bart Baesens is a professor at KU Leuven (Belgium), and a lecturer at the University of Southampton (United Kingdom). He has done extensive research on analytics, customer relationship management, web analytics, fraud detection, and credit risk management. His findings have been published in well-known international journals (e.g. Machine Learning, Management Science, IEEE Transactions on Neural Networks, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Evolutionary Computation, Journal of Machine Learning Research, …) and presented at international top conferences. He is also author of the books Credit Risk Management: Basic Concepts, published by Oxford University Press in 2008; and Analytics in a Big Data World published by Wiley in 2014. His research is summarized at www.dataminingapps.com.

At its 10th annual I/O developer conference, Google CEO Sundar Pichai and his lieutenants doubled down on artificial intelligence as the next big phase of computing. Machine learning was a common thread in Google's latest products and launches - Google Home, Google's Assistant, Duo and Allo, and Instant Apps. As the event unfolded, it outlined Pichai's vision of what kind of company Google wants to be. Every decade, a new era of computing arrives that pretty much shapes everything we do. During the event, Pichai noted that saying that Google aims to be more assistive and provide a more ambient experience.

"Think about just how interconnected the world is now," said Matt Gould, the co-founder of Arria NLG, a prominent enterprise in the development and deployment of Natural Language Generation (NLG) technologies worldwide. "Think about it from just a personal context. How much data are you generating personally every day?" Modern, connected humans interact constantly online with computers, mobile phones, and many other devices. They pay bills, watch movies, purchase products, interact with medical professionals, use fitness apps, listen to music, and work online. "That whole drifting miasma of invisible data is spilling off you constantly and consistently, and it's happening for at least half the world's population now," said Gould during a recent DATAVERSITY phone interview.