Medical applications of AI are replete with promise, but stymied by opacity: with lives on the line, concerns over AI models' often-inscrutable reasoning – and as a result, possible biases embedded in those models – largely prevent scaled applications of AI for medical treatment, no matter how promising the underlying research. Recently, researchers from Mederrata Research (a nonprofit aiming to use data-driven techniques to preempt medical errors), Sound Prediction (a digital health informatics company aiming to create transparent AI models) and the NIH leveraged supercomputing at the Pittsburgh Supercomputing Center (PSC) to design a method for recreating the benefits of AI models in medicine with more explicability. The root of the team's approach is multilevel modeling (MLM, not to be confused with multilevel marketing). Through MLM, groups of similar cases are bundled and differential equations are used to identify a limited set of controlling factors for each case, allowing for easier – and more consistent – identification of the model's reasoning compared to post-hoc analyses of more opaque models. The researchers designed and applied the AI toward predicting – and explaining – readmission and death among Medicare patients following a hospital visit, training the model on three years of data (2009-2011) and testing it on a fourth (2012).

Setting aside the relatively recent rise of electronic signatures, personalized stamps have been a popular form of identification for formal documents in East Asia. These identifiers – easily forged, but culturally ubiquitous – are the subject of research by Raja Adal, an associate professor of history at the University of Pittsburgh. But, it turns out, the human expertise required to study these stamps at scale was prohibitive – so Adal turned to supercomputer-powered AI to lend a hand. "[From] the perspective of the social sciences, what matters is not that these instruments are impossible to forge--they're not--but that they are part of a process by which documents are produced, certified, circulated and approved," Adal explained in an interview with Ken Chiacchia of the Pittsburgh Supercomputing Center (PSC). "In order to understand the details of this process, it's very helpful to have a large database. But until now, it was pretty much impossible to easily index tens of thousands of stamps in an archive of documents, especially when these documents are all in a language like Japanese, which uses thousands of different Chinese characters."

However, with increasingly expanding weather data sets and looming deadlines, it is nearly impossible for them to monitor all storm formations -- especially smaller-scale ones -- in real time. Now, there is a computer model that can help forecasters recognize potential severe storms more quickly and accurately, thanks to a team of researchers at Penn State, AccuWeather, Inc., and the University of Almería in Spain. They have developed a framework based on machine learning linear classifiers -- a kind of artificial intelligence -- that detects rotational movements in clouds from satellite images that might have otherwise gone unnoticed. This AI solution ran on the Bridges supercomputer at the Pittsburgh Supercomputing Center. In their study, the researchers analyzed more than 50,000 historical U.S. weather satellite images.

The Pittsburgh Supercomputing Center received five @HPCwire awards, including one for poker AI'Libratus' The Pittsburgh Supercomputing Center (PSC) received not one, but five HPCwire awards at the 2017 International Conference for High-Performance Computing (HPC), Networking, Storage and Analysis (SC17) on Sunday, Nov. 12. One of the three Readers' Choice Awards that PSC received was for Best Use of AI: CMU School of Computer Science "Libratus" AI on PSC's "Bridges" wins Brains vs. AI competition. HPCwire represents the leading trade publication in the supercomputing community and their annual Readers' and Editors' Choice Awards, given out at the start of the annual supercomputing conference, are well respected in that community. The awards are determined based on a nomination and voting process among the HPCwire community as well as selections from the publication's editors. In addition to Best Use of AI, PSC received two more Readers' Choice Awards -- Outstanding Leadership in HPC (Nick Nystrom, Interim Director, PSC) and Best Use of HPC in Energy (PSC with Texas A&M uses OpenFOAM on PSC Bridges & Texas Advanced Computing Center's Stampede to better understand coolant & heat transfer in high-temperature-jet reactors).

Libratus, an artificial intelligence developed by Carnegie Mellon University, made history by defeating four of the world's best professional poker players in a marathon 20-day poker competition, called "Brains Vs. Once the last of 120,000 hands of Heads-up, No-Limit Texas Hold'em were played on Jan. 30, Libratus led the pros by a collective $1,766,250 in chips. The developers of Libratus -- Tuomas Sandholm, professor of computer science, and Noam Brown, a Ph.D. student in computer science -- said the sizable victory is statistically significant and not simply a matter of luck. "The best AI's ability to do strategic reasoning with imperfect information has now surpassed that of the best humans," Sandholm said. This new milestone in artificial intelligence has implications for any realm in which information is incomplete and opponents sow misinformation, said Frank Pfenning, head of the Computer Science Department in CMU's School of Computer Science. Business negotiation, military strategy, cybersecurity and medical treatment planning could all benefit from automated decision-making using a Libratus-like AI. "The computer can't win at poker if it can't bluff," Pfenning said. "Developing an AI that can do that successfully is a tremendous step forward scientifically and has numerous applications.

"That was anticlimactic," Jason Les said with a smirk, getting up from his seat. Unlike nearly everyone else in Pittsburgh's Rivers Casino, Les had just played his last few hands against an artificially intelligent opponent on a computer screen. After his fellow players -- Daniel McAulay next to him and Jimmy Chou and Dong Kim in an office upstairs -- eventually did the same, they started to commiserate. The consensus: That AI was one hell of a player. The four of them had spent the last 20 days playing 120,000 hands of heads-up, no-limit Texas Hold'em against an artificial intelligence called Libratus created by researchers at Carnegie Mellon University. A similar scene had unfolded two years prior when Les, Kim and two other players decisively laid the smackdown on another AI called Claudico. The players hoped to put on a repeat performance, finish up the event January 30th, and ride the rush of endorphins until they got home and resumed their usual games of online poker.

That was anticlimactic," Jason Les said with a smirk, getting up from his seat. Unlike nearly everyone else in Pittsburgh's Rivers Casino, Les had just played his last few hands against an artificially intelligent opponent on a computer screen. After his fellow players -- Daniel McAulay next to him and Jimmy Chou and Dong Kim in an office upstairs -- eventually did the same, they started to commiserate. The consensus: That AI was one hell of a player. The four of them had spent the last 20 days playing 120,000 hands of heads-up, no-limit Texas Hold'em against an artificial intelligence called Libratus created by researchers at Carnegie Mellon University. A similar scene had unfolded two years prior when Les, Kim and two other players decisively laid the smackdown on another AI called Claudico. The players hoped to put on a repeat performance, finish up the event on January 30th, and ride the rush of endorphins until they got home and resumed their usual games of online poker. The fight wasn't even close. All told, Libratus won by a more than 1.7 million (virtual) dollars, and just like that, the second Brains vs. AI competition came to a close. To understand what these players were up against and what makes Libratus work, let's go back to a time before all hope of victory was lost. For the four men playing against Libratus, victory didn't always seem impossible. The AI was in the lead from the get-go, building an impressive streak of wins for the first three days. Day four saw the gap narrow by $40,000, and a string of successes on day six brought the humans to within $50,000 of the lead. "In the start here, we lost the first day," Les explained. And then we were losing, but then we fought back up to nearly equal. We were feeling really confident! We know how to play, we're going to be able to win."

Marking a major step forward for artificial intelligence (AI), Libratus, an AI developed by Carnegie Mellon University (CMU), has resoundingly beaten four of the best heads-up no-limit Texas hold'em poker players in the world in a marathon, 20-day competition. After 20 days and a collective 120,000 hands played, Libratus closed out the competition Monday leading the pros by a collective $1,766,250 in chips. "I'm just impressed with the quality of poker Libratus plays," pro player Jason Les, a specialist in heads-up no-limit Texas hold'em like the other three players, said at a press conference yesterday morning. "They made algorithms that play this game better than us. We make a living trying to find vulnerabilities in strategies. That's what we do every day when we play heads-up no-limit. We tried everything we could and it was just too strong."

Marking a major step forward for artificial intelligence (AI), Libratus, an AI developed by Carnegie Mellon University (CMU), has resoundingly beaten four of the best heads-up no-limit Texas hold'em poker players in the world in a marathon, 20-day competition. After 20 days and a collective 120,000 hands played, Libratus closed out the competition Monday leading the pros by a collective $1,766,250 in chips. "I'm just impressed with the quality of poker Libratus plays," pro player Jason Les, a specialist in heads-up no-limit Texas hold'em like the other three players, said at a press conference yesterday morning. "They made algorithms that play this game better than us. We make a living trying to find vulnerabilities in strategies. That's what we do every day when we play heads-up no-limit. We tried everything we could and it was just too strong."

Researchers have developed an Artificial Intelligence (AI) bot that beat professional players in a 20-day poker tournament. The bot, named Libratus, beat four of the World's best Heads-Up No-Limit Texas Hold'Em poker players at a casino in Pittsburgh, Pennsylvania. Libratus won the tournament after 120,000 hands, winning with a lead of $1.7 million in virtual poker chips. Professor of computer science Tuomas Sandholm said: 'The best AI's ability to do strategic reasoning with imperfect information has now surpassed that of the best humans' The AI was developed at Carnegie Mellon University (CMU) by Professor Tuomas Sandholm and his PhD student Noam Brown. They said that the AI's victory wasn't just a matter of luck - it was statistically significant.