I think that 100% of the actually useful use cases for generative AI could be described in two words: “supervised autocomplete”.
Generative AI is overrated, long live old-school AI
141–150 of 192 posts
Re: Generative AI is overrated, long live old-school AI
#142Earlier quoted context omitted.
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.
Well in that case, maybe the debate is: do we want that? Why?
If you can trust the model is at least as accurate as wikipedia then it becomes a drop in replacement for every task you do that requires wikipedia.
There are a whole range of tasks that can’t be done today with an LLM because of the hallucination issues. You can’t rely on the information it gives you when writing a research paper, for example.
Re: Generative AI is overrated, long live old-school AI
#143I would add that there are logic deductive and constraint systems that are more classical and work in some areas. It is not about a single method but we should he aware that AI is a superset of what we see.
Re: Generative AI is overrated, long live old-school AI
#144Earlier quoted context omitted.
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.
Well in that case, maybe the debate is: do we want that? Why?
For starters because one of the first products people decided to use these models for is a search engine, and I don't think it is a stretch to argue that search engines should have a positive relationship, rather than indifference, towards facts and the truth.
Re: Generative AI is overrated, long live old-school AI
#145People 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.
Yeah, i think one potential way to use blackbox ai in newer systems is having guardrails that are validated as safe (but perhaps non-optimal) and ensuring that the ai takes action within that sample space. Obviously this is hard problem, but might open the doors for policies (in self-driving cars, for example) to be entirely ai driven.
Re: Generative AI is overrated, long live old-school AI
#146I think that 100% of the actually useful use cases for generative AI could be described in two words: “supervised autocomplete”.
That's not wrong, but an ideal autocompleter is a near-omniscient superintelligence. "The optimal approach to curing Alzheimer's is ______". "The proof of the Riemann hypothesis is as follows: ______". "The best way for me to improve my life is _______".
Re: Generative AI is overrated, long live old-school AI
#147There is much more to generative models than building out language models and image models.
Generative models are about characterising probability distributions. If you ever predict more than just the average of something using data, then you are doing generative modelling.
The difference between generative modelling and predictive modelling is similar to the difference between stochastic modelling and deterministic modelling in the traditional applied mathematical sciences. Both have their place. Neither is overrated.
Grab the best tool for the job.
Re: Generative AI is overrated, long live old-school AI
#148As stated by John McCarthy--"I invented [AI] because we had to do something when we were trying to get money for a summer study" (the Lighthill debate)--this article passes the AI sniff test, or "please remember us predictive AI folks when you go to dole out your money" as all that is solid melts into PR.
Re: Generative AI is overrated, long live old-school AI
#149Earlier quoted context omitted.
I think you're fighting an uphill battle because of what you picked to defend here - shell scripts are very easy to write, and I have a hard time imagining a future where someone tells an LLM, "Write me a shell script that runs run_control.py with the speed argument set to one hundred." to get, "./run_control.py --speed 100"
> shell scripts are very easy to write I've been a developer for a long-ass time, though I don't have super frequent occasion where I find it worthwhile to write a shell script. It comes up occasionally. In the past 2 weeks I've "written" 4 of them via ChatGPT for 1-off cases I'd have definitely found easier to just perform manually. It's been incredible how much easier it was to just get a working script from a desc…
I think one effect of LLMs and their limited context will be the end of DRY. I’ve already found myself getting gpt to write stuff for me that could have been part of or leveraged existing code with a little more thinking. But the barrier to just starting from scratch to do exactly what I want, right now, just got a whole lot lower.
Re: Generative AI is overrated, long live old-school AI
#150Earlier 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
> 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
Sounds like an extension of https://en.wikipedia.org/wiki/Wirth%27s_law. How many times have I done some simple arithmetic by typing it into my browser's bar and checking out the google calculator results? When a generation ago I would have plugged it into a calculator on my desk (or done it in my head, for that matter...). I would be entirely unsurprised to hear that in another generation we're using monstrously complicated "AI" systems to perform tasks that could be done way more simply/efficiently just because it's convenient.