51–60 of 331 posts
AI hype-bros like to complain that real AI experts are too much concerned about debunking current AI then improving it - but the truth is that debunking bad AI IS improving AI. Science is a process of trial and error which only works by continuously questioning the current state.
https://www.lesswrong.com/posts/5uw26uDdFbFQgKzih/beware-gen...
I'm glad to read articles like this one, because I think it is important that we pour some water on the hype cycle If we want to get serious about using these new AI tools then we need to come out of the clouds and get real about their capabilities Are they impressive? Sure. Useful? Yes probably in a lot of cases But we cannot continue the hype this way, it doesn't serve anyone except the people who are financially i…
I don't understand what people mean when they say that AI is being hyped. AI is at the point where you can have a conversation with it about almost anything, and it will answer more intelligently than 90% of people. That's incredibly impressive, and normal people don't need to be sold on it. They're just naturally impressed by it.
Earlier quoted context omitted.
I’m so tired of hearing this be repeated, like the whole “LLMs are _just_ parrots” thing. It’s patently obvious to me that LLMs can reason and solve novel problems not in their training data. You can test this out in so many ways, and there’s so many examples out there. ______________ Edit for responders, instead of replying to each: We obviously have to define what we mean by "reasoning" and "solving novel problems"…
They can't create anything novel and it's patently obvious if you understand how they're implemented. But I'm just some anonymous guy on HN, so maybe this time I will just cite the opinion of the DeepMind CEO, who said in a recent interview with The Verge (available on YouTube) that LLMs based on transformers can't create anything truly novel.
Demis Hassabis On The Future of Work in the Age of AI (@ 2:30 mark)
I'm glad to read articles like this one, because I think it is important that we pour some water on the hype cycle If we want to get serious about using these new AI tools then we need to come out of the clouds and get real about their capabilities Are they impressive? Sure. Useful? Yes probably in a lot of cases But we cannot continue the hype this way, it doesn't serve anyone except the people who are financially i…
I’ll take critiques from someone who knows what a test train split is. The idea that a guy so removed from machine learning has something relevant to say about its capabilities really speaks to the state of AI fear
The key insight is that LLMs can 'reason' when they've seen similar solutions in training data, but this breaks down on truly novel problems. This isn't reasoning exactly, but close enough to be useful in many circumstances. Repeating solutions on demand can be handy, just like repeating facts on demand is handy. Marcus gets this right technically but focuses too much on emotional arguments rather than clear explanat…
I'm glad to read articles like this one, because I think it is important that we pour some water on the hype cycle If we want to get serious about using these new AI tools then we need to come out of the clouds and get real about their capabilities Are they impressive? Sure. Useful? Yes probably in a lot of cases But we cannot continue the hype this way, it doesn't serve anyone except the people who are financially i…
I don't understand what people mean when they say that AI is being hyped. AI is at the point where you can have a conversation with it about almost anything, and it will answer more intelligently than 90% of people. That's incredibly impressive, and normal people don't need to be sold on it. They're just naturally impressed by it.
The key insight is that LLMs can 'reason' when they've seen similar solutions in training data, but this breaks down on truly novel problems. This isn't reasoning exactly, but close enough to be useful in many circumstances. Repeating solutions on demand can be handy, just like repeating facts on demand is handy. Marcus gets this right technically but focuses too much on emotional arguments rather than clear explanat…
I’m so tired of hearing this be repeated, like the whole “LLMs are _just_ parrots” thing. It’s patently obvious to me that LLMs can reason and solve novel problems not in their training data. You can test this out in so many ways, and there’s so many examples out there. ______________ Edit for responders, instead of replying to each: We obviously have to define what we mean by "reasoning" and "solving novel problems"…
Earlier quoted context omitted.
How actually useful are they though? We've had more than a year now of saying these things 10X knowledge workers and creatives, so.... where is the output? Is there a new office suite I can try? 10 times as many mobile apps? A huge new library of ebooks? Is this actually in practice producing things beyond Ghibli memes and RETVRN nostalgia slop?
I think it largely depends on what you’re writing. I’ve had it reply to corporate emails which is good since I need to sound professional not human. If I’m coding it still needs a lot of baby sitting and sometimes I’m much faster than it.