The Ledger
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Pedro Domingos predicts Backprop alone will not reach general AI
“I actually do not believe that that's the case. I think Backprop will not get us there.”
Domingos: Mandating total model explainability literally makes deep learning illegal
“And at the end of the day, you know, you can't, like the European Union, mandate that every model has to be explainable, right? Because then, if you read that law literally, it makes deep learning illegal, right?”
Pedro Domingos: Very little of current machine learning capability has been deployed
“With the existing machine learning technology, of what we can do with that, how much have we done? Very little so far. So there's enormous amount for, enormous scope to do things there. Not just in finance, but in a lot of other fields, right?”
Domingos: AI is too early to predict 20 years into the future
“I would say we are so much in the beginning that we can't even really picture where we're going to be 20 years from now.”
Domingos: The hardest problem in AI is learning representation
“The hardest problem in AI is coming up with a representation. Once you've done that, the rest follows, and when you don't do that, you don't really get very far”
Domingos: AI is an amazing tool for authoritarianism
“AI can be a great tool for democracy. It is also unfortunately an amazing tool for authoritarianism.”
Domingos: Dumb AI is vastly more dangerous than smart AI
“The real danger of AI is not that computers will get too smart and take over the world. The real danger is that computers are too stupid, and they've already taken over the world, right? Computers are making decisions about us the whole time, and they're dumb,…”
Domingos: Future human work will shift to setting goals and verifying AI output
“So we humans, right, I can see a future where our full-time occupation is to tell the, you know, algorithms what we want to do, set the objective function, set the boundaries, and then verify the solutions all the time, continuously.”
Domingos: Major deep learning wins come from combining multiple techniques
“A lot of the things that people think of as successes of deep learning are actually successes of combining deep learning with other things.”
Domingos: Geoffrey Hinton hasn't made capsule networks work yet despite right intuition
“I think capsule networks are a very interesting, you know I like the intuition behind capsule networks. I think they point in the right direction. I think Jeff hasn't quite been able to make them work yet.”
Domingos: Machine learning's five major paradigms haven't changed since the 1950s
“There's been enormous progress. The five major paradigms are exactly the same as they were then.”
Domingos: Terminator-style AI scenarios are not happening anytime soon
“Terminator isn't happening anytime soon. First of all, because the technology isn't there, but second of all, because there is this, I mean, like a lot of these, I think, errors that people made come from anthropomorphizing AI.”
Pedro Domingos: Every major ML algorithm can theoretically learn any function
“On a theoretical level, every one of these major machine learning algorithms has a theorem that says if you give it enough data, it can learn any function.”
Domingos: State-of-the-art AI models have more connections than many animals
“Having said that, if you look at the number of connections that the state-of-the-art machine learning systems for some of these problems have, they're more than many animals. So we're actually at the point where the, you know, they have hundreds of millions or…”