Earlier quoted context omitted.
>but saves companies quite some money That's all that matters to companies.
Until they can't find seniors anymore.
AI is going to be in a different place in 5 or 10 years.
Artificial intelligence systems found to excel at imitation, but not innovation
21–30 of 126 posts
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#22Even their imitation is just superficial, at least for the prompts the average user is motivated to write. I might not be able to differentiate AI content from any human content, but I can differentiate it from high quality human content. Which is a bit sad, since AI will probably eliminate most lower end content creation jobs. This doesn't improve the state of the content industry for users, but saves companies quit…
> AI will probably eliminate most lower end content creation jobs. This doesn't improve the state of the content industry for users, but saves companies quite some money.
What does it say if your work can't be distinguished from AI clichés? Maybe it's what the industry needs.
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#23I'm shocked; shocked to learn that no innovation is going on at this AI establishment. Mimicry needs information, of which an AI has heaps; but, innovation needs will, of which it has none. Maybe some day, but not now.
> innovation needs will
feedback
Innovation needs feedback, otherwise all ML papers would not run evaluations. Humans come up with 100 stupid ideas that fail at eval before stumbling onto a good one.
Improving innovation is a matter of putting the AI inside a system that can provide feedback. Remember AlphaGo move 37? The model created feedback by self-play games, and beat all humans at Go - feedback made it really more creative than expert human players. It upturned centuries of strategy.
Feedback is also similar to the scientific method. We come up with theories and then test them out. That's how science advances, by validation, not by will. Humans are not magically more capable, we just have better feedback.
A few days ago there was a story "Earliest Carpenters: 476k-year-old log structure discovered in Zambia". It took so many years of feedback for humans to evolve from log cabins to LLMs. We had to discover or invent everything in the meantime, it's a slow, cultural process of feedback assimilation into language.
And now that same language experiential data is being learned by LLMs, and used contextually to solve problems. Most of our intelligence is either in language or feedback. Language is just our reservoir of past feedback. When AIs will generate their own experience and feedback, which will be targeted to their weak points, they will improve and even surpass humans. Learning from your own mistakes is better than learning from other people's mistakes which might be unrelated to your issues.
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#24"found to Excel"
on a positive note: at least HN didn't use an LLM on that headline
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#25Re: Artificial intelligence systems found to excel at imitation, but not innovation
#26Innovation is simply a result of trying to imitate, but adding errors. That's how humans do it. Add in some darwinism so that the best 'innovations' survive. Made a mistake in making food? Oh, that's a new recipe. Can't really remember how to tell the story? Well, that's a new story. Accidentally kicked a ball while trying to just walk? I just invented soccer. And so on.
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#27So, James Murphy is an AI?
"Yeah you wanted it smart But honestly, I'm not smart No, honestly, we're never smart We fake it, fake it all the time"
- LCD Soundsystem
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#28One can casually observe that LLMs quite excel at composition though: gluing together pieces of knowledge in ways no one did before (examples: a program that does X using language Y, a painting that mashes up two themes). Most knowledge workers' activities aren't innovative or imitational - similarly, we compose stuff, so LLMs are a fair competitor.
... and our judgments of composition favor recall over precision. Which is to say that as human judges we're good at finding sense in something generated if it's plausible. We'll take a proposition (eg in a composition) and construct a justification for it. "I can see how that makes sense". I am conflating plausible combination with high recall. Precision, in this sense, is that no proposition would be acceptable wit…
The very first python app I wrote was a statistical bard generator. I had python calculate word frequencies from a Shakespeare corpus and spit them back out with a probability distribution.
Honestly it read just as well ;) We’re simpler than we imagine.
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#29How could a statistical system trained on data display intelligence let alone innovation? It's just very good statistics at the end of the day. Artificial Perception is about as far as you can get with ml/dl tech if you point the sensors at the world of space-time. If you point it at words, as with LLM, you get statistics about words - that is, no actual understanding of what the words model in the minds of the original authors of those words. So utterly unreliable for any kind of mission critical or autonomous use.