I don't really get this sentiment. You can be in a competitive environment, but it means nothing if the incentives are skewed.
Ever heard of "a race to the bottom"? That's a competitive environment too, after all, and no one thinks it's positive when applied to humans.
This seems like some variant of "why don't you short the market and become rich". It doesn't work like that.
Should be interesting to see what happens to the programming profession when there isn't anyone around anymore who actually knows programming.
I said as much - https://news.ycombinator.com/item?id=48870324 - prepare to be downvoted.
many children have an unlimited capacity to ask "why?". many adults are the same
if the abilities of AI are finite, then we will continue to have burning curiosity, questions to ask, and discoveries to make
The first type happens when you are enthusiastically engaged in a topic, which LLMs will likely enhance.
The second type happens as a by-product of solving a, perhaps deeply uncomfortably, difficult problem. This is what people are talking about when they say LLMs will hamper human cognition. Instead of sitting there for an hour and struggling, people will instead reflexively give in and ask an LLM to solve it for them.
I think in most cases, understanding is the point. we don't expect students to derive general relativity before doing astrophysics. re-invention is only a tool for understanding
The flip side is even more interesting. There’s a great number of electrical engineers with significant physics backgrounds who don’t really understand how electricity actually works, but they can still solve useful problems. By understanding I mean they can describe what underlying physical phenomena reactance represents etc.
When the child is able to go to YouTube and find a tutorial rather than having to puzzle it out, yes, it absolute does. We've seen this for decades now.
> its output can be novel or good, but rarely both at the same time.
> rarely
That is not a viewpoint they can't do something useful and new.
With that criteria, he could be talking about anyone.
I find it rare that people critiquing AI today, actually hold people to the same standards. Or are as enthusiastic about referencing ways machines keep surpassing us, as for ways they have not yet, when speaking about limits for progress.
LLMs are fundamentally limited by their architecture to only return a token predicted by a statistical inference, essentially lossy decompression.
It's like arguing that taking an image, compressing it with JPEG and low quality, then decompressing it into something blurry with some random color values thrown in is creating new art.
No one is arguing that everything a human has created is good. No one is arguing that LLMs can't be useful.
Sutton is arguing that it can't be novel. Cherry picking a couple of words doesn't change his argument, which is very clear.