Since its inauguration in 1966, the ACM A.M. Turing Award has recognized major contributions of lasting importance to computing. Through the years, it has become the most prestigious award in computing. To help celebrate 50 years of the ACM Turing Award and the visionaries who have received it, ACM has launched a campaign called "Panels in Print," which takes the form of a collection of responses from Turing laureates, ACM award recipients and other ACM experts on a given topic or trend. For our fourth and final Panel in Print, we invited 2014 ACM A.M. Turing Award recipient MICHAEL STONEBRAKER, 2013 ACM Prize recipient DAVID BLEI, 2007 ACM Prize recipient DAPHNE KOLLER, and ACM Fellow VIPIN KUMAR to discuss trends in big data. Gartner estimates that there are currently about 4.9 billion connected devices (cars, homes, appliances, industrial equipment, among others) generating data.

On May 11, 1997, a computer showed that it could outclass a human in that most human of pursuits: playing a game. The human was World Chess Champion Garry Kasparov, and the computer was IBM's Deep Blue, which had begun life at Carnegie Mellon University as a system called ChipTest. One of Deep Blue's creators, Murray Campbell, talked to the IDG News Service about the other things computers have learned to do as well as, or better than, humans, and what that means for our future. What follows is an edited version of that conversation. IDGNS: Is it true that you and Deep Blue joined IBM at the same time?

Garry Kasparov, one of the greatest chess players of all time, is famous for his pair of faceoffs against the IBM supercomputer Deep Blue. Kasparov won the first match against the computer, 4-2, in 1996, but lost in the rematch, 3½-2½, in 1997. He recently published a book, "Deep Thinking," about the experience. Business Insider recently spoke with Kasparov about Deep Blue, his thoughts on AI, and machine advancements over the past 20 years -- and how he sees the interplay between machine intelligence and humanity. This interview has been edited for clarity and length. Garry Kasparov: AI as a concept is surrounded by mythology. Most of the things we mention we understand. You know, if we say "white," we all see it's white. If we talk about elements of computer science or some general items, we are in agreement.

I'd love to talk more about Flowcast, but I'm still not able to shake the image of you making a robotic submarine run by San Diego poolside (laughs). As a STEM enthusiast, I have been in awe of IBM Watson's capabilities. And I feel it's an honor to be talking to someone who has contributed to its capabilities. Now, let's come back to Flowcast. Can you share more information and shed more light on how Flowcast came about?

Microsoft executive Todd Holmdahl has led teams to invent profitable new computing hardware products before. His latest project is his first with a chance of hauling in a Nobel Prize in physics as well as new revenue if it succeeds. Holmdahl previously oversaw the hardware design of the Xbox and Xbox360 consoles, which rake in billions for Microsoft each year. Late last year he was appointed the leader of a swelling band of mathematicians, physicists, and engineers trying to add mighty computers powered by quantum physics to Microsoft's menu of cloud computing services. Holmdahl speaks about quantum computing like a tech executive would a new line of business, not a speculative physics or R&D project.

On January 22nd, two days after President Trump was inaugurated, he received a memo from his new Secretary of Defense, James Mattis, recommending that the United States launch a military strike in Yemen. In a forty-year career, Mattis, a retired Marine Corps general and a veteran of the wars in Afghanistan and Iraq, had cultivated a reputation for being both deeply thoughtful and extremely aggressive. By law and by custom, the position of Defense Secretary is reserved for civilians, but Mattis was still a marine at heart. He had been out of the military for only three years (the rule is seven), and his appointment required Congress to pass a waiver. For the first time in his professional life, he was going to the Pentagon in a suit and tie. Mattis urged Trump to launch the raid swiftly: the operation, which was aimed at one of the leaders of Al Qaeda in Yemen, required a moonless night, and the window for action was approaching. Under previous Administrations, such attacks entailed ...

Despite all the innovations around us, kids still need as much encouragement as possible to become the next mad genius to push us into the future, which is what Amazon CEO Jeff Bezos did during a recent talk at The Museum of Flight in Seattle. SEE ALSO: Forget about Mars for a minute: Let's talk about these rad moon missions Staying true to the theme of the facility, Bezos launched into an almost Elon Musk-like talk on his private space travel company Blue Origin and why humans should go to space and what challenges we face. "I want to see millions of people living and working in space," said Bezos to a large group of children who asked some pretty damn smart questions about space travel. "I think we should build a permanent human settlement on one of the poles of the moon," said Bezos, explaining how robots could land supplies on the moon before humans arrive. "It's time to go back to the moon, but this time to stay." "I want to see millions of people living and working in space."

Kaggle's annual March Machine Learning Mania competition drew 442 teams to predict the outcomes of the 2017 NCAA Men's Basketball tournament. In this winner's interview, Kaggler describes how he came in 5th place by stepping back from solution mode and taking the time to plan out his approach to the the project methodically. I have been working in credit risk model development in the banking industry for approximately 10 years. I have been lucky to receive exposure to big data and data science through previous roles but decided I wanted to teach myself R and to improve my machine learning knowledge. The best opportunity seemed to be to utilise Kaggle datasets where I could to help with this.

By their own admission, Jack Ma is uncomfortable with Artificial Intelligence (AI) and Elon Musk is scared. But why? Contrary to popular perception AI is old. To be precise it's 51-years old, widely acknowledged to have been born at a conference at Dartmouth College in 1956. That conference was attended by a diverse group of people. Three of them presented the Logic Theorist, the world's first true artificial intelligence programme. Two of them were Allen Newell and Herbert Simon.

AI was very popular 30 years ago, then disappeared, and is now making a big come back because of new robotic technologies: driver-less cars, automated diagnostic, IoT (including vacuum cleaning and other household robots), automated companies with zero employee, soldier robots, and much more. Will AI replace data scientists? I think so, though data scientists will be initially replaced by "low intelligence" yet extremely stable and robust systems. There has been a lot of discussions about the automated statistician. I am myself developing data science techniques such as Jackknife regression that are simple, robust, suitable for black-box, machine-to-machine communications or other automated use, and easy to understand and pilot by the layman, just like a Google driver-less car can be "driven" by an 8 years old kid.