What Google DeepMind Means for A.I.
newyorker.com
What Google DeepMind Means for A.I.
1–10 of 94 posts
Re: What Google DeepMind Means for A.I.
#2The article says humans can do "transfer learning" while machine can't. It shouldn't be impossible to implement transfer learning in machines too.
Re: What Google DeepMind Means for A.I.
#3The article says humans can do "transfer learning" while machine can't. It shouldn't be impossible to implement transfer learning in machines too.
Statistical learning models of transfer learning have been published in several venues over the past few years.
Re: What Google DeepMind Means for A.I.
#4"video games" (read "world simulator").
The important thing about their work is that it is deliberately marching down the path of more and more complex world simulations.
We experience the world at one second per second. To learn to walk we must first fall, and we fall at 32 feet/second^2. There's a hard limit on how fast we can make mistakes (like tripping) and so there is a hard limit on how fast we can learn.
Computers can experience a simulated world at many hours per second. When they're learning to walk in a simulated world they can fail, and learn, thousands of times before we've finished our first step.
This ratio of simulated experience to real world time is also going up. Eventually the minimum amount of time it takes to grow a toddler like AI in simulation will be just under the time an AI researcher is willing to wait for results. When that happens we'll see a real improvement in the quality of AIs.
Re: What Google DeepMind Means for A.I.
#5"video games" (read "world simulator"). The important thing about their work is that it is deliberately marching down the path of more and more complex world simulations. We experience the world at one second per second. To learn to walk we must first fall, and we fall at 32 feet/second^2. There's a hard limit on how fast we can make mistakes (like tripping) and so there is a hard limit on how fast we can learn. Comp…
For now real-world simulations at the complexity level of 'a toddler' run at a very small fraction of real time.
Re: What Google DeepMind Means for A.I.
#6"video games" (read "world simulator"). The important thing about their work is that it is deliberately marching down the path of more and more complex world simulations. We experience the world at one second per second. To learn to walk we must first fall, and we fall at 32 feet/second^2. There's a hard limit on how fast we can make mistakes (like tripping) and so there is a hard limit on how fast we can learn. Comp…
Producing a simulated toddler is way beyond our current capabilities, no matter how much simulated experience we give it. We simply don't know (yet) how to program said toddler's brain.
Re: What Google DeepMind Means for A.I.
#7The article says humans can do "transfer learning" while machine can't. It shouldn't be impossible to implement transfer learning in machines too.
I don't see anywhere it says machines can't; it says DeepMind doesn't. There are a few philosophers who believe human thought is more or less magic and can't be replicated in any way but all of the arguments I've seen are either deeply flawed logically or are so specific as to more or less read they can't "be" human, which I'll accept as true but isn't terribly interesting.
Re: What Google DeepMind Means for A.I.
#8> “They can find their way across a room,” Mason said. “They can see stuff, and as the light and shadows change they can recognize that it’s still the same stuff. They can understand and manipulate objects in space.”
Isn't this just adding extra dimensions to the input space? We have 2D now (plus time?), we're missing Z, sound, sensation, maybe emotions. Each added dimension gives the algorithm exponentially more bits to crunch but if computer speed is doubling every 2 years or so, why is this so obviously a dead-end to Mason?
Re: What Google DeepMind Means for A.I.
#9"video games" (read "world simulator"). The important thing about their work is that it is deliberately marching down the path of more and more complex world simulations. We experience the world at one second per second. To learn to walk we must first fall, and we fall at 32 feet/second^2. There's a hard limit on how fast we can make mistakes (like tripping) and so there is a hard limit on how fast we can learn. Comp…
There are two sides to this, world simulation and AI. As the other replies already said, current AI isn't close to toddler-level (there's no reasoning going on in the DeepMind work, just statistical correlation). We're also way off on the world simulation side - show me a realistic world simulator that can run close to realtime. Physically-based rendering is indeed impressive but this only accounts for visual perception and learning to walk involves much more than that.
Re: What Google DeepMind Means for A.I.
#10> “They can find their way across a room,” Mason said. “They can see stuff, and as the light and shadows change they can recognize that it’s still the same stuff. They can understand and manipulate objects in space.” Isn't this just adding extra dimensions to the input space? We have 2D now (plus time?), we're missing Z, sound, sensation, maybe emotions. Each added dimension gives the algorithm exponentially more bit…
I think the distinction is that the algorithm gets to observe the 2D space directly, whereas the whole notion of 3D space has to be learned from 2D projections.
Also, note that the games they do best on have a nice clear objective function: Montezuma's Revenge on the other hand does not have such a numeric objective to optimise.
To be fair, Hassabis does freely concede these limitations in his talks (at least in the ones targeted to academic audiences), and it will be certainly interesting to see where they go from here.