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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

#51

Post by gautamdivgi »

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…

Isn’t most of the mathematics of AI old, as in really old?

Regression, both linear and logistic are from the mid 1800s to early 1900s. Neural networks, at least the basics are from around 1950.

What has really changed is the engineering, the data volume and the number of fields we can apply the mathematics to. The math itself (or what is the basis of AI) is really old.

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

#52

Post by ChatGTP »

JohnFen wrote: post #42
aaroninsf wrote: post #35

Earlier quoted context omitted.

I am not so sure, there seems to be accumulating evidence that "finding the optimal solutions" means (requires) building a world model. Whether it's consistent with ground truth probably depends on what you mean by ground truth. Given the hypothesis that the optimal solution for deep learning presented with a given training set, is to represent (simulate) the formal systemic relationships that generated that set, by…

> there seems to be accumulating evidence that "finding the optimal solutions" means (requires) building a world model. Was this ever in doubt? This has been the case forever (even before "AI"), and I thought it was well-established. The fidelity of the model is the core problem. What "AI" is really providing is a shortcut that allows the creation of better models. But no model can ever be perfect, because the value…

But no model can ever be perfect, because the value of them is that they're an abstraction. As the old truism goes, a perfect map of a terrain would necessarily be indistinguishable from the actual terrain.

Not sure why but I find this incredibly insightful…

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

#53

Post by qorrect »

snapcaster wrote: post #19
DeathArrow wrote: post #12

>investors have become only interested in companies building generative AI, relegating those working on predictive models to “old school” AI. If that is the definition of old school AI, I wonder how symbolic AI should be named.

how about "useless with no successes of note" AI?

What ? We all use it everyday, it's just that as soon as the problem was solved with 'old AI', everyone forgot it was an AI problem.

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

#54

Post by [deleted] »

fnordpiglet wrote: post #18
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…

AI has been marketing term since the day it was coined. It means literally nothing, which means it can mean anything.

[deleted]

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

#55

Post by IanCal »

JohnFen wrote: post #47
nico wrote: post #40

Earlier quoted context omitted.

To me what’s exciting about Chat/GPT type of tech, is that they can be the “coordinators” of other models. Imagine asking an AI assistant to perform a certain industrial control task. The assistant, instead of executing the task “itself”, could figure out which model/system should perform the task and have it do it. Then even monitor the task and check it’s completion.

I'm not sure how the likes of ChatGPT could accomplish that even in theory, but I won't say it's not possible at some point in the future. Gpt itself, perhaps, someday.

You can just tell the models to and tell them what tools they have available and how to call out to them. Langchain supports this iirc.

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

#57

Post by kenjackson »

dimitrios1 wrote: post #17
whiplash451 wrote: post #9

Earlier quoted context omitted.

By stagnate, you mean beating humankind at the task, right? :)

It's funny to me we look at GPT4 scoring high on all these tests and think it's worth anything when educators and a lot of us here have been lamenting the standardized tests since Bush made it a preeminent feature of our country's education system. They are not a good measure of intelligence. They measure how well you can take a test.

Funny -- I literally had someone tell me this same thing this morning... but the exact same guy last week was arguing with me against the reduced importance of these same tests for college admissions. Last week he was arguing how critical these tests were for the college admissions process, but this morning the same tests are basically worthless.

Not saying you hold the same opinions -- but I wouldn't be surprised if people's take on these tests is more about what is convenient for their psyche than any actual principled position.

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

#58

Post by jasonjmcghee »

whiplash451 wrote: post #37
jasonjmcghee wrote: post #26

Earlier quoted context omitted.

The biggest issue with using them in this way is how alien the failure modes are. Interpretable models with transparent loss functions are easy to grok. How LLMs might fail on a classic task is (afaict right now) difficult to predict.

What is not transparent in the cross-entropy loss used in a large number of deep nets?

I think there was a breakdown in communication here.

If I train a classic deep net as a classifier and there are 5 possible classes, it will only ever output those 5 classes (unless there's a bug).

With ChatGPT, for example, it could theoretically decide to introduce a 6th class - what I would call an alien failure mode, even if you explicitly told it not to.

I think formally / provably constraining the output of LLM APIs will help mitigate these issues, rather than needing to use an embedding API / use the LLM as a featurizer and train another model on top of it.

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

#59

Post by nico »

version_five wrote: post #48
nico wrote: post #40

Earlier quoted context omitted.

To me what’s exciting about Chat/GPT type of tech, is that they can be the “coordinators” of other models. Imagine asking an AI assistant to perform a certain industrial control task. The assistant, instead of executing the task “itself”, could figure out which model/system should perform the task and have it do it. Then even monitor the task and check it’s completion.

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

Sure, maybe you can use a shell script, but now the AI assistant can write it based on your verbal/text description, and then the assistant can also run it for you after you’ve checked it.

What your are saying is: “why use the washing machine, if I my clothes are even cleaner when I wash them myself - I also spend less detergent and less water”.

You are free to keep doing your laundry by hand.

But I bet most people prefer the washing machine.

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

#60

Post by stormfather »

nico wrote: post #45
seydor wrote: post #16

I m not sure it's overrated, but the concerns are very real. We love the model because it speaks our language as if it's "one of us", but this may be deceiving, and the complete lack of model for truth is disturbing. Making silly poems is fun but the real uses are in medicine and biology, fields that are so complex that they are probably impenetrable to the human mind. Can Reinforcement learning alone create a model…

> model for the truth? Without sensing/experiencing the world, there is no truth. The only truth we can ever truly know, is the present moment. Even our memories of things that we “know” that happened, we perceive them in the now. Language doesn’t have a truth. You can make up anything you want with language. So the only “truth” you could teach an LLM, is your own description of it. But these LLMs are trained on thou…

I think for practical purposes you could hold that text from wikipedia or scientific papers if true, for example. The issue I think OP is referring to is if a LLM can refer back to these axiomatically true sources to ground and justify its outputs like a human would.
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