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A sobering message about the future at AI's biggest party
Blaise Aguera y Arcas praised the revolutionary technique known as deep learning that has seen teams like his get phones to recognize faces and voices. He also lamented the limitations of that technology, which involves designing software called artificial neural networks that can get better at a specific task by experience or seeing labeled examples of correct answers.
"We're kind of like the dog who caught the car," Aguera y Arcas said. Deep learning has rapidly knocked down some longstanding challenges in AI—but doesn't immediately seem well suited to many that remain. Problems that involve reasoning or social intelligence, such as weighing up a potential hire in the way a human would, are still out of reach, he said. "All of the models that we have learned how to train are about passing a test or winning a game with a score [but] so many things that intelligences do aren't covered by that rubric at all," he said.
(Score: 2, Interesting) by Anonymous Coward on Sunday December 15 2019, @06:40PM (1 child)
When you're going the wrong way it doesn't matter how fast you go - you're not going to get to your destination. That's the problem we face today. For problems with nice clean domains we can, with varying degree of effort and ingenuity, build systems that are generally headed in the right direction. And for these systems more power will generally give you a better answer though you tend to start hitting an asymptotic 0 on returns pretty fast, for most problems.
The ideal was that these problems would over time be able to be generalized into bigger, more complex, problems. Beat atari games, then you beat nintendo games, and next thing you know you have an AI rolling through Skyrim and the game of life is ultimately just a matter of more power with a bit more cleverness. But that ideal was wrong. We're finding ourselves unable to solve some basic problems, and those that we can solve don't really generalize to much of anything except stuff that can be mapped to a near identical domain.
Waymo is specifically what I was alluding to with my previous post. I don't think most people realize what they're doing. They're using white-listed routes with extensive hand-coded adjustments supported with extensive dependence on radar/lidar to minimize the damage from network screw ups, and then a fleet of 'remote support technicians' on top of all of this that will remotely take control of the vehicles when everything else fails. You're going to see cars without a visible human driver, but all you're really looking at is a fleet of rail trolleys without visible rails. Really quite handy nonetheless, but not exactly some giant leap forward.
None other than the CEO of Waymo has stated, quite confidently, that it will be decades before we see significant numbers of self driving vehicles on the roads. At the time I thought this was because he was out of touch or simply didn't know what he was talking about. Then I got to work with AI for a couple of years. And yeah, he has one quote that sums up everything so well, "You don't know what you don't know until you're actually in there and trying to do things.". It's just not what it seems like it should be, even if you have a substantial background in AI relevant technologies.
I think we'll see within a couple of years, as companies probably decide better of dropping ever more money into the AI hole, that the robot apocalypse has, for now, been postponed. You could throw a billion times more power at everything, and none of these problems would even slightly change. The problem is no longer power. You can still get better solutions with more power from the domains were AI fits, but the problem is that the really interesting and useful domains are the very ones where it doesn't fit!
(Score: 2) by barbara hudson on Sunday December 15 2019, @07:02PM
I've seen ordinary cars do self-driving. Driver on their phones, crash. It's a self-correcting problem. Sort of.
Same as distracted walking.
It took a couple of generations for people to adapt to cars as a safe and integral part of their lives. Same can probably be said about smartphones.
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