Comment by pingou
6 days ago
I just got a bit triggered by the "hype" word. What if the hype was real? It is easy to say that nobody knows how all of this is going to work, and I would say it is a prudent thing to say, but there is value in making a bold prediction from the start instead of just updating your view to respond to change. In one case you are predicting stuff, in the other, just reacting.
But I absolutely agree that in hindsight we are often asking the wrong questions about each new technology.
I keep seeing on HN that AI is a hype, and many here are anti AI (which I get, as a programmer AI made my job less interesting, and I'm even worried about losing it), but where has AI underdelivered?
The hype is in what AI delivers (at least so far). I would never create a PR without an AI review. I will ask an AI to write code for me from time to time.
But it still has huge gaps in quality. And from time to time, it shows me that it doesn’t really understand things. You might point out that how is that any different from your mediocre engineer. But for most people skilled enough, you can easily know the difference when someone doesn’t really know something.
With AI, you discover this after reading several pages being dumped on you by people being “more productive” with AI.
Ok so the hype would be people saying AI can currently do something well and autonomously when it cannot (or not consistently enough), and it is easy to prove them wrong.
But I feel like people are more hyped about what the AI will be able to do soon rather than what it can do now.
I think AI does understand things (depending on your definition), how else could we communicate and ask it a question if it didn't? I mean we're quite far from Eliza here.
And yes, often their answer would be so wrong that we think it is impossible that AI understands anything, but this jagged intelligence doesn't prove, at least to me, that there isn't some understanding. At what point do we say that AI understands things? What if we can reduce 99% of those dumb failures, would we then say than AI understands?
>I think AI does understand things (depending on your definition), how else could we communicate and ask it a question if it didn't?
https://en.wikipedia.org/wiki/Chinese_room
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> and it is easy to prove them wrong
No, they just say you are using the wrong model or something.
If it's a coworker dumping reviews of crap code on you at work, the incentive is to blanket approve everything because otherwise you're just the grumpy old man who is resisting innovation. No matter that the code makes no sense at all and the tests aren't actually testing what they should test.
>where has AI underdelivered?
Other than the stock market (which seems decoupled from reality at the moment), where has AI delivered?
The only use case where I see anything resembling AI delivering on it's promises is software, and my personal experience with that is that everything that comes out of the teams using AI is destructively broken. (Where they used to be able to deliver software that worked, even if it wasn't ideal, now they reliably make things worse and their stuff doesn't work when used.)
I agree, especially the juxtaposition of "we have still have no idea how all of this is going to work when the dust settles" and "hype". If we don't know, then there is a chance it isn't a hype.
For example, now it may seem that the models are becoming mere infrastructure, and the value moves up to apps and data. But if the models of tomorrow become able to write the apps themselves, then the value moves back. I won't need to pay some to write me a wrapper for the LLM, if the LLM will be able to write the same wrapper, maybe even better because it will be customized for my needs. The app providers are currently profiting from the gap between "what a software company can do using the AI" and "what the AI can do unaided", but that gap is going to shrink, possibly to zero.