[phyzix5761]

Yes, the guy with a PhD in Machine Intelligence, co-author of Reinforcement Learning: An Introduction, which is universally considered the bible of the field, recipient of the AAAI fellowship award and the Turing Award, and the inventor of Temporal Difference Learning doesn't know what he's talking about.

[dwd]

Sure, but does that mean he's right all the time about all things, including everything in his own field?

He is saying no generative AI is going to produce output that is both good and novel because it is always derivative. And then adds a generative AI (Claude Code) into his list of AI that have produced output that he feels is good and novel, invalidating what he is arguing.

"...no matter how many instances of white swans we may have observed, this does not justify the conclusion that all swans are white."

[zeroonetwothree]

If you read it he says that CC has additional aspects beyond ordinary GAI, namely the ability to verify. That aspect is necessary for GAI to be good and novel.

Although personally I think code doesn’t actually need to be very novel so it’s actually the best example.

[lowbloodsugar]

“When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong.”

https://en.wikipedia.org/wiki/Clarke%27s_three_laws

[E-Reverance]

I don't completely disagree but its worth noting how new a lot of the empirical evidence in favour of LLMs are, so its not impossible to be a tad ignorant of the present