He's embedded in a social and professional world that has every incentive to believe the current state of AI progress is real and important and should be hyped to the stars. I am unsurprised to read such frothing soothsaying as a result.
It remains to be seen if LLMs would do any good in the "theory-building" heavy fields of math. They have certainly proven themselves in branches of math where the progress is verifiable, but fields like AG commonly have papers that do not concretely solve a problem but provide a new perspective/framework. This is iterated upon if other mathematicians find the construction rich and interesting enough, which eventually leads to breakthroughs.
LLMs have yet to show that they can meaningfully make such helpful abstractions. Not saying that it can't be done, but I wouldn't write such doomer posts just as yet.
The academic market in the US is very bad and in the EU only marginally better. China seems to prefer domestic talent now.
Outside of academia there are only a few niche industries still hiring. Mag7 is drying up. The semi-private research institutes want seniors with grants or customers in pocket, not fresh phds with no connections.
Probably only getting worse in the near term.
There are a few specific applications that are still good. Medical imaging seems okay for now. Advanced signal processing is still a viable route. Consumer robotics, possibly.
> I feel like at this point, both the prophets of AI utopia like Ray Kurzweil, and of AI doom like Eliezer Yudkowsky, could be forgiven for asking: dude, will you listen to us YET?
What did Kurzweil or Yudkowsky predict that actually came to pass?
I assign this Scott no points for bringing up Penrose as a straw man. That’s a very old canard.
bwaaaaaa! ha ha ha bwaaaaa!
wheeeeeeuew!
is the title what happens from too much ketamine?
or is the hype machine being tasked with streeeetching things out for one more quarter? bills, elections, push back,lack of relevance, that sort of stuff.
He's embedded in a social and professional world that has every incentive to believe the current state of AI progress is real and important and should be hyped to the stars. I am unsurprised to read such frothing soothsaying as a result.
It remains to be seen if LLMs would do any good in the "theory-building" heavy fields of math. They have certainly proven themselves in branches of math where the progress is verifiable, but fields like AG commonly have papers that do not concretely solve a problem but provide a new perspective/framework. This is iterated upon if other mathematicians find the construction rich and interesting enough, which eventually leads to breakthroughs.
LLMs have yet to show that they can meaningfully make such helpful abstractions. Not saying that it can't be done, but I wouldn't write such doomer posts just as yet.
Reports of our demise are greatly exaggerated.
Soon we will all just be human cattle owner by billionaires who own all the technology used to keep us poor and indoors.
Oh, no - that's actually now.
the billionaires currently see the problem as how to properly read the ownership tag.
Someone close to me is about to embark on a maths PhD. I'm curious about what advice people here would have for people in that position.
I think it depends what they’re hoping to get out of it.
The academic market in the US is very bad and in the EU only marginally better. China seems to prefer domestic talent now.
Outside of academia there are only a few niche industries still hiring. Mag7 is drying up. The semi-private research institutes want seniors with grants or customers in pocket, not fresh phds with no connections.
Probably only getting worse in the near term.
There are a few specific applications that are still good. Medical imaging seems okay for now. Advanced signal processing is still a viable route. Consumer robotics, possibly.
Learn a trade that involves using your hands.
So don't bother with higher education at all?
At least until robotic dexterity catches up.
> I feel like at this point, both the prophets of AI utopia like Ray Kurzweil, and of AI doom like Eliezer Yudkowsky, could be forgiven for asking: dude, will you listen to us YET?
What did Kurzweil or Yudkowsky predict that actually came to pass?
I assign this Scott no points for bringing up Penrose as a straw man. That’s a very old canard.
bwaaaaaa! ha ha ha bwaaaaa! wheeeeeeuew! is the title what happens from too much ketamine? or is the hype machine being tasked with streeeetching things out for one more quarter? bills, elections, push back,lack of relevance, that sort of stuff.