why aren't all 7 resolved? a statement only gets an assessment when the public
record can support or contradict it. opinions and what-ifs never can, and 0 checkable
ones are still open, waiting for their date. predictions held up or didn't;
assertions are supported or contradicted. on every card:
▮▮▮▮▮ certainty ·
▮▮▮▮▮ debate potential. speakers are clickable
Prediction Not checkable as stated
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.”
Prediction Not checkable as stated
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.”
Prediction Not checkable as stated
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.”
Assertion Not checkable as stated
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.”
Prediction Not checkable as stated
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.”
Assertion Supported
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.”
Assertion Supported
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…”