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Generative AI is overrated, long live old-school AI

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Re: Generative AI is overrated, long live old-school AI

#121

Post by beepbooptheory »

kenjackson wrote: post #46
peter_retief wrote: post #15

"So has generative AI been overhyped? Not exactly. Having generative models capable of delivering value is an exciting development. For the first time, people can interact with AI systems that don’t just automate but create an activity of which only humans were previously capable." Good answer but I feel that most users/people do not understand the difference between generative and predictive machine learning and tha…

IMO, it has been underhyped. We're seeing things with LLMs that a decade ago I'd say was multiple decades out, if not more. We're just years into generative approaches. And I think we'll more combinations of methods used in the future. The goal of AI has never been to build an all knowing perfect system. It has also never been to replicate the way the human brain works. But its been to build an artificial system that…

Trying to imagine this stuff being even more hyped and I just don't think its possible. People around here are practically ready to sell their first born child to OpenAI/Microsoft at this point.

Re: Generative AI is overrated, long live old-school AI

#122

Post by superdisk »

sterlind wrote: post #63
version_five wrote: post #7

Seems like the person who wrote the blog works in "classical" deep learning. So do I, so here's the fairest take I can come up with: "AI" has for recent memory been a marketing term anyway. Deep learning and variations have had a good run at being what people mean when they refer to AI, probably overweighting towards big convolution based computer vision models. Now, "AI" in people's minds means generative models. Th…

do people actually use SVMs anymore? like, regression, sure - because it's a tool to measure how well a hypothesis (polynomial function) matches the data (points.) and CNNs are still foundational in computer vision. but the first and last time I heard of SVMs was in college, by professors who were weirdly dismissive of these newfangled deep neural networks, and enamored by the "kernel trick." but aren't SVMs basicall…

> but the first and last time I heard of SVMs was in college, by professors who were weirdly dismissive of these newfangled deep neural networks, and enamored by the "kernel trick."

LOL. Exact same experience in my college courses. Glad to know it's universal.

Re: Generative AI is overrated, long live old-school AI

#123

Post by 01100011 »

kmeisthax wrote: post #72

People calling neural-net classifiers "old-school" AI confused me. For a second I thought they were talking about the really old "expert systems" with everything being a pile of hard-coded rules.

It still feels like there's a place for these rule based systems(Prolog?) to at least place some constraints on the output of non-deterministic, generative AI. If nothing else, have a generative AI generate the ruleset so you have some explicit rules you can audit from time to time.

Re: Generative AI is overrated, long live old-school AI

#124

Post by rkhacker »

version_five wrote: post #7

Seems like the person who wrote the blog works in "classical" deep learning. So do I, so here's the fairest take I can come up with: "AI" has for recent memory been a marketing term anyway. Deep learning and variations have had a good run at being what people mean when they refer to AI, probably overweighting towards big convolution based computer vision models. Now, "AI" in people's minds means generative models. Th…

The Generative AI is the AI for the masses. While people were getting overhyped with all the possibilities and promises of AI and deep learning etc. it is for the first time that they can also tinker and get surprised by its results. People feel creative interacting with it.

Re: Generative AI is overrated, long live old-school AI

#125

Post by fulafel »

tough wrote: post #120
pstorm wrote: post #106

Earlier quoted context omitted.

That's a trivial example, sure. Think of saying "make this image more red, flip it vertically, then crop the bottom 25%, and finally output it with 80% compression as a jpg". That would take 15 minutes to figure out how to write that with imagick, or just have an LLM do it for you.

I had to try, seems reasonable, haven't tested the code As an AI language model, I do not have direct access to image editing software, but I can provide you with a shell script that could achieve the described image manipulation using ImageMagick, assuming it is installed on your system. Here's an example shell script that you could use as a starting point: bash Copy code #!/bin/bash # Set the input image filename i…

This has lots of lossy encode/decode cycles that will accumulate artifacts. Good anecdote.

Re: Generative AI is overrated, long live old-school AI

#126

Post by baq »

JohnFen wrote: post #49
version_five wrote: post #48

Earlier quoted context omitted.

This is just wrong. Also, even if a LLM could do that, so could a shell script, without the risks involved in using "AI" for it, or for now the ridiculous external dependence that would involve. I wonder if in 10 years people will be stuck debugging Rube-Goldberg machines composed of LLM api calls doing stuff that if-statements can do, probably cobbled together with actual if-statements

> doing stuff that if-statements can do, probably cobbled together with actual if-statements In other words, old-school expert systems.

With the limit of 25k words it might actually be reasonable to test out a prompt for an expert system… but I’d still leave reasoning to something else, for now. Z3, prolog or some forward chaining tool like clips, but have the LLM hallucinate some of the rules?

Re: Generative AI is overrated, long live old-school AI

#127

Post by xwdv »

echelon wrote: post #119
xwdv wrote: post #108

Earlier quoted context omitted.

AI proponents are missing the point. Anything you write to make an AI produce something is basically code. Docs are code. You don’t have to feed a developer code or docs, you can give them a high level idea and they’ll figure it out on their own if you want.

That code will eventually fall away. The big thing everyone in this single thread is missing is that AI is a metaheuristic. I wouldn't expect to use AI to run_script.py. That's easy. I'd expect it to look at the business signals and do the work of an intern. To look at metrics and adjust some parameters or notify some people. To quickly come up with and prototype novel ways to glue new things together. To solve brand…

To do the work of an intern an AI must go on Jira, read a ticket, then find the appropriate repositories where code needs to be modified, write tests for its modification, submit for code review, respond to feedback in code review, deploy its changes.

It’s not there yet.

Re: Generative AI is overrated, long live old-school AI

#128

Post by seydor »

nico wrote: post #102
seydor wrote: post #81

Earlier quoted context omitted.

It can be exact and self-consistent, you can teach the rules of mathematics . There are some things that are provably unprovable but thats a known fact.

You can still express contradiction in math. The rules don’t determine the interpretation. An LLM will pretty much always respect the rules of language, but it can use them to tell you completely fake stuff.

math is language

Re: Generative AI is overrated, long live old-school AI

#129

Post by baq »

GuB-42 wrote: post #43

Is there a fundamental difference? I mean, the only thing GPT does is predict the next word, which makes it not so different from a compression algorithm. And diffusion models (the image generating stuff) are essentially fancy denoisers. Depending on how you assemble the big building blocks, you get generation or you get prediction.

GPT-3.5 is not a Markov chain, this is trivially true. While ‘predicts the next word’ is true, the mechanism of it is of interest and that is most certainly not trivial.

Re: Generative AI is overrated, long live old-school AI

#130

Post by jedberg »

sharemywin wrote: post #117
arrow7000 wrote: post #95

Earlier quoted context omitted.

Maybe an adversarial approach was used in training these models in the first place?

It was they were' trained using reinforcement learning with human feedback to create the critic.

I hadn't thought about human feedback being an adversarial system, but I guess that makes sense, since it's basically a classifier saying "you got this wrong".
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