IBM's Watson system beat two former Jeopardy! game show champions on television February 14-16, 2011. Details of the Match in the NY Times story Computer Wins on Jeopardy!: Trivial, It's Not. (Feb. 17, 2011).
As she met her fellow captains and competitors, all multiweek winners on the game show (including me), she was surprised how familiar everyone seemed to be with each other. Back in 2014, when she made her first appearance, "I didn't know a single person who had ever been on the show," Julia told me. But this time, she marveled, "everyone else seems to have known each other, either personally or by reputation, for decades." They shared years of experience on Jeopardy's secret farm team: quiz bowl. Of the 18 "All-Stars" in the tourney, all but Julia and two others had played the academic competition known as quiz bowl in high school or college.
Last night was full of surprises. Surprise number two: Eric Trump can successfully answer a Jeopardy! SEE ALSO: Just 13 very upsetting photos of Donald Trump Jr. Not only does this famously intelligent person get the answer correct (brother in law), he also answers the question in the form of a question. He goes on to add suggestive emoji of a fist punching the American flag.
IBM Research undertook a challenge to build a computer system that could compete at the human champion level in real time on the American TV quiz show, Jeopardy. The extent of the challenge includes fielding a real-time automatic contestant on the show, not merely a laboratory exercise. The Jeopardy Challenge helped us address requirements that led to the design of the DeepQA architecture and the implementation of Watson. After three years of intense research and development by a core team of about 20 researchers, Watson is performing at human expert levels in terms of precision, confidence, and speed at the Jeopardy quiz show. Our results strongly suggest that DeepQA is an effective and extensible architecture that can be used as a foundation for combining, deploying, evaluating, and advancing a wide range of algorithmic techniques to rapidly advance the field of question answering (QA).
Almost every word has more than one meaning. Modern search engines solve this problem using knowledge bases. Yago was one of the first knowledge bases, developed by scientists at the Max Planck Institute for Informatics in Saarbrücken and the Télécom ParisTech in Paris. Last week, the researchers received an award for their work on Yago from the most important scientific journal in the field of artificial intelligence. Today, they are releasing Yago's source code.
Of course this is the Watson that was built by IBM to understand answers on Jeopardy and come up with the right questions. Since his appearance on the game show in 2011, IBM has expanded Watson's talents, building on the algorithms that allow him to read and derive meaning from natural language. And among other functions, IBM adapted Watson for use in medicine. Toronto Western, part of the University Health Network, is the first hospital in Canada to use Watson for research in Parkinson's, a neurological disorder. The centre has a track record of running clinical trials for off-label drug use, which means taking a drug approved for treatment of one condition and repurposing it for another.
David Ferrucci will deliver a keynote at the O'Reilly Artificial Intelligence Conference in NYC, June 26-29, 2017. His colleague Jennifer Chu-Caroll will also give a talk, "Beyond the state of the art in reading comprehension," at the same conference. Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. In this episode of the Data Show, I spoke with David Ferrucci, founder of Elemental Cognition and senior technologist at Bridgewater Associates.
The Artificial Intelligence revolution is here. We are moving further into an age, where the imagination stirred from our childhood spent watching movies, is now becoming reality. Leading us into this age are the typical (and untypical) tech giants, who are fiercely competing for the next break through. Project Oxford is Microsoft's venture into the world of artificial intelligence and deep learning. It takes in several key areas, including image, facial, text and speech recognition, and hopes to implement the technology into its computer operating systems and smartphone software.
IBM announced Thursday, Jan. 9, 2014 that it's investing over $1 billion to give its Watson cloud computing system its own business division and a new home in the heart of New York City (AP Photo/Seth Wenig, File) Don't technology companies who promote AI as the way forward also have an obligation to retrain our workforce to deal with the coming job disruption? Artificial intelligence, strong and weak, comes with a lot of moral implications. Weak AI (what we have now, Siri, Alexa, Waze, sophisticated IVR systems, etc…) is going to take jobs away from workers. It has been for years, since the very first attempts. If a programmer can predict it, and a computer can do it, eventually companies will stop paying people to do that job.
Earlier this month, the nation watched as Watson, a computer system designed by IBM, drubbed the two all time champions of Jeopardy. It was a much more difficult challenge than, say, beating a grandmaster at chess. To win, Watson had to navigate the vagaries of human speech, the idioms, the puns, the cultural references -- all the things, in short, that make language delightful and deeply machine unfriendly. Journalist Stephen Baker spent a year behind the scenes, as the team of IBM engineers struggled to design and build Watson in time for the show. He tells the story of project Watson, and what it means for the future, in his new book, "Final Jeopardy: Man vs. Machine and the Quest to Know Everything."