Watson AI Fails to Destroy Humans in First Round of Jeopardy

Humans fight on as IBM's artificial intelligence ends its first day of Jeopardy competition

2 min read
Watson AI Fails to Destroy Humans in First Round of Jeopardy

UPDATE: See who prevailed -- man or machine? -- in the third and final round!

You can relax: so far, we humans aren't completely redundant, as IBM's Watson artificial intelligence system managed to not answer every single question instantly and correctly in the first round of a three day Jeopardy exhibition match with past champions Ken Jennings and Brad Rutter.

After round one (which was as far as today's show got), Watson was tied with Brad for first with $5000, and Ken Jennings was in third with $2000. It's worth mentioning that Watson led for most of the round, with a few incorrect questions setting it back significantly towards the end. Watson definitely showed more 'common sense' than I was expecting, but it still seemed burdened with a fair amount of the 'so smart it's kinda dumb' that computers are known for. It definitely didn't get everything right, displaying a significant number of low-certainty answers (below its buzzing threshold) as well as buzzing in with several answers that seemed pretty far off. It also managed to give an incorrect answer to a question that Ken had incorrectly answered with the same answer moments before, which is a bug that I bet is getting resolved as we speak.

While I was honestly hoping that Watson would do slightly better, I'm relieved that it at least ended up tied for first. Irrespective of expectations, I feel like Watson turned in an impressive performance, and I think that's one of the most important aspects of this exhibition... In my experience, the overall perception that the general public has of the current state of robotics and artificial intelligence is some mix of Roomba, the Terminator, and Commander Data, which is (to put it mildly) somewhat inaccurate and unrealistic. So, it's good to see a state-of-the-art AI system put on a credible public performance, complete with some fallability to keep us feeling comfortably in control.

The next segment (featuring the the second round plus Final Jeopardy) airs on ABC tonight, with the final match on Wednesday.

[ Watson ]

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Robot with threads near a fallen branch

RoMan, the Army Research Laboratory's robotic manipulator, considers the best way to grasp and move a tree branch at the Adelphi Laboratory Center, in Maryland.

Evan Ackerman
LightGreen

“I should probably not be standing this close," I think to myself, as the robot slowly approaches a large tree branch on the floor in front of me. It's not the size of the branch that makes me nervous—it's that the robot is operating autonomously, and that while I know what it's supposed to do, I'm not entirely sure what it will do. If everything works the way the roboticists at the U.S. Army Research Laboratory (ARL) in Adelphi, Md., expect, the robot will identify the branch, grasp it, and drag it out of the way. These folks know what they're doing, but I've spent enough time around robots that I take a small step backwards anyway.

This article is part of our special report on AI, “The Great AI Reckoning.”

The robot, named RoMan, for Robotic Manipulator, is about the size of a large lawn mower, with a tracked base that helps it handle most kinds of terrain. At the front, it has a squat torso equipped with cameras and depth sensors, as well as a pair of arms that were harvested from a prototype disaster-response robot originally developed at NASA's Jet Propulsion Laboratory for a DARPA robotics competition. RoMan's job today is roadway clearing, a multistep task that ARL wants the robot to complete as autonomously as possible. Instead of instructing the robot to grasp specific objects in specific ways and move them to specific places, the operators tell RoMan to "go clear a path." It's then up to the robot to make all the decisions necessary to achieve that objective.

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