I don't think anyone is saying it's poisonous here? The people were hired to do a job and they didn't do it. Feels like you're being disingenuous, if there's one thing i know about AI employees, it's that they use LLMs, like, all the time.
Are you having trouble following the metaphor? In it, I would be the conspiracy theorist saying it’s poisonous, and OpenAI would be the government saying it’s harmless but it’s also a fireable offense to feed it to us and we’ve hired a second set of contractors to watch for any violation of this rule.
(I’m not trying to be disingenuous, though I am trying to express a niche viewpoint. Hopefully, my willingness to take the metaphorical role of conspiracy theorist is understood as epistemic humility.)
Nope, not having trouble following it, but the metaphor leaves out an important link between AI output and the AI itself. The question is, did the AI gain anything from this training? And the answer is, it did not, since the training used it's own answer with no other input. There's nothing in the water metaphor that draws this line.
Maybe a better metaphor is something involving drinking your own piss, but I don't feel the need to flesh that one out
So you’re saying LLMs are feeding us their piss instead of water
Well dang. That’s a problem ain’t it.
GPT-5 came and went, and we’re still here adding decimals to the model numbers hoping this fundamental fuckup will go away
Feels like everyone, including you and the guy you’re arguing with, and the researchers at openAI, knows this is a problem. Is it laziness? Lack of creativity? Are we seriously all out of ideas other than scaling compute?
When are we planning on figuring this one out boys. Who’s actually working on this today
Religions are an example of a system feeding back into itself and going off the rails. This is not an AI problem, this is the problem of any evolving system.
In humans this problem is solved by dying. If you get too stoooopid, well you get culled by your own stupidity. Luckily we run in a massively parallel fashion and those that aren't fatally dumb carry on.
This is also why human civilization fundamentally changed (not humans, our civilization) after wide adoption of the scientific method. Humanities growth in relation to our potential intelligence level was horrifically slow. It's really easy to say "hur hur, machine dumb" when we could have had rockets 10,000 years ago if we weren't dumb ourselves.
> those who need done a small set of narrowly defined tasks with existing clear guardrails: repetitive physical labor in a controlled environment, call center and customer service chat work, etc.
I have no idea how people can so confidently say that call center work is a “controlled environment” or “repetitive”. It’s almost by definition not repetitive or controlled. Customer support is what I go to when the controlled environment has failed
Let's repeat the same circle. Why is customer service fundamentally a more controlled environment than anything else the author deems "outside of an LLMs capabilities"?
came here to say exactly this. in fact, this is probably why we are not seeing a lot of AI application on customer service use case, and when we see one, it's almost always frustrating.
> If Jev is skipping generation entirely for a narrow structured task, of course it's faster
I think this is reasonable if people are actually using LLMs to solve this type of narrow structured task, which they are. The evidence is that every LLM provider has some method of forcing the output to conform to a json schema in their documentation.
Literally no person on earth can beat a computer in chess. Practically no person on earth can really teach a computer anything about chess. For some crazy reason, people keep playing
> Take Software engineering for example, I can't believe there is a class of software engineers who wake up everyday and tell themselves, "today is the day I am going to automate the rest of my job".
I think most people here get that this is the point?
The point beyond this one is that an AI proof doesn’t prevent humans from working on the problem, it destroys the current economic incentive to work on the problem. Perhaps we should rethink the current incentives. In order to make money as a chess player, you don’t need to beat AI, or ban AI from playing chess.
If mathematics took a similar approach (we don’t get paid for solving net-new problems, we get paid for enriching human understanding), then there’s no issue.
lol right. The nonchalance in referring to taxi/bus driver jobs.
Remember when we all said it's a good thing when the coal mining jobs are going away and that they should all just learn to code? Maybe a little more of that energy right now.
It’s not going to be ubiquitous? There hasn’t been a single frontier model where generation n costs less than generation n-1 to run. So the reasonable thing is to assume that GPT-7 will cost even more than GPT-6, and more and more of the frontier of knowledge will be locked behind a giant paywall. Participating in any field will mean ponying up to the oligarchs that own the infrastructure that runs the model.
I would love it if I could use it as a second monitor when working in a coffee shop or library. Unfortunately universal control was pretty solid at launch and then just completely left to die
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