Is deep blue really considered AI? I thought that was more of a brute force algo?
Good Old Fashioned AI is dead, long live New-Fangled AI
51–60 of 96 posts
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#52Alot of GOFAI was about symbolic reasoning which is back in fashion thanks to areas like Neurosymbolic AI and Graph Learning. One could argue that Generative AI like Stable Diffusion is incorporating some of these techniques. What is prompt engineering and textual inversion if not the manipulation of symbols? Add more recent interest in areas like Answer Set Programming and "what is old is new again". It's not like GOFAI dissapeared. Even technologies like Expert Systems still see use under a new name. Sometimes you don't need a heuristic approximation of the rules that you get from all ML approaches. You need exact representations or already know the rules and the challenge is inference.
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#53Earlier quoted context omitted.
GOFAI was never more than a rules engine. If-then statements. Agree with you about probabilistic AI being useful in low-stakes situations, at least at first.
Sorry, thats really wrong. I wouldn't call theorem provers just "if-then" statements. By that logic, everything, even large models, are if-then statements.
Technically, they are. There was a post on HN recently about how every model is equivalent to a decision tree.
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#54I think Hofstadter's book GEB is a whirlwind tour of cool ideas in GOFAI -- that concludes that it's all hopeless for AI because of the liar paradox.
Written in 1979.
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#55Earlier quoted context omitted.
Sorry, thats really wrong. I wouldn't call theorem provers just "if-then" statements. By that logic, everything, even large models, are if-then statements.
Technically, they are. There was a post on HN recently about how every model is equivalent to a decision tree.
I mean, if it can be specified by a computational process, that’s trivially true, right?
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#56"Finally, a vital question is, how will this affect today’s working artists? Here the answer is not so optimistic." I have a different take on this. I think this technology will allow more people, not less, to make money as a living (so, professionally) in a visual arts related industry. So I'm broadening the field to include not just "artists" but "commercial art" as well (designers, commercial illustrators, video/f…
> Whenever something becomes cheaper (in this case, labor for art), its consumption increases. So in the future, because producing commercial art is so much cheaper, it will be consumed a lot more. I have the opposite view. With lower barrier of entry it will get over-saturated, over-produced and consumers will suffer from content fatigue leading to less interest in AI generated media as a whole. An analogy is luxury…
How about website/frontend design as an analogy?
It'd be great if that was made easier so that more folks could participate/make a living. Then again, I think that every time that was made simpler (eg. Flash, Dreamweaver/export to html, JQuery, ...) has resulted in a slew of crap.
So: the lower the barrier to entry, the more actual skill/artistry becomes important for a high quality result.
Phrased differently: once the drudge work becomes mechanised, the concept of quality is lifted to a new level. This highlights aspects that used to be stuck in the mud of the drudge work, enabling a more profound understanding... by those with the necessary skills to do so.
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#57As always, they mis-spelled the acronym for "Machine Learning". There's nothing "Artificial" or "Intelligent" here but a mathematical algorithm operating on an algorithmically-encoded dataset. If anything, it's closer to an encryption algorithm where the keys can decrypt deterministic parts of the plantext from the cyphertext and soften the edges a bit.
Also very confusing, they misspelled "Bad" right at the outset. (Though I do find that can be a slightly useful signal about the sort of reasoning to be expected and how much attention to pay to it)
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#58The "new-fangled" AI, as the article calls it, is often useful when the stakes are low, and you can accept mistakes in outcomes. Examples of such applications are: trying to determine which of your friends occur in a photo, which movies a subscriber may be interested in, or which action could lead to victory in a computer game. Getting a rough translation of a newspaper entry, as mentioned in the article, is also a g…
The only barrier for higher stakes applications is going to be the frequency of errors. Flying an airplane or running a factory has a lot less margin for error, but humans don't do those things perfectly either (Chernobyl, Three Mile Island, Union Carbide-Bhopal disaster). It doesn't have to be perfect, just better than humans. And in fact, I'd argue that by having no deterministic outcomes prevents systemic failure,…
If you understand the problem well enough that you know that the frequency of errors is stable and won’t blow up on out-of-sample data, then it seems like you’ve fully modeled what’s happening? That’s not any easier than solving the problem because it is solving the problem.
If don’t have good reasons to be confident that the error rate is stable, then you’re just guessing that you solved the problem, because it seems to work.
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#59The "new-fangled" AI, as the article calls it, is often useful when the stakes are low, and you can accept mistakes in outcomes. Examples of such applications are: trying to determine which of your friends occur in a photo, which movies a subscriber may be interested in, or which action could lead to victory in a computer game. Getting a rough translation of a newspaper entry, as mentioned in the article, is also a g…
The only barrier for higher stakes applications is going to be the frequency of errors. Flying an airplane or running a factory has a lot less margin for error, but humans don't do those things perfectly either (Chernobyl, Three Mile Island, Union Carbide-Bhopal disaster). It doesn't have to be perfect, just better than humans. And in fact, I'd argue that by having no deterministic outcomes prevents systemic failure,…
>It doesn't have to be perfect, just better than humans.
I have a different opinion on this.
Humans don’t like uncertainty. We like to feel like our mental model of reality can predict future outcomes. When it doesn’t, we get very uneasy. It’s why we don’t like dealing with erratic humans.
Part of the problem with AI is it’s lack of interpretability. People aren’t going to want to interact with AI if they can’t intuit what it will do, even if you can show it’s statistically better. The performance barrier is going to be much higher than just a little better than humans. We don’t have that limitation when dealing with people because we can more easily infer their goals and actions.
Thinking that being a little better than humans is the threshold is a rational decision. But human trust is often irrational. The latter often drives politics which can regulate AI into a corner.
Re: Good Old Fashioned AI is dead, long live New-Fangled AI
#60Earlier quoted context omitted.
The only barrier for higher stakes applications is going to be the frequency of errors. Flying an airplane or running a factory has a lot less margin for error, but humans don't do those things perfectly either (Chernobyl, Three Mile Island, Union Carbide-Bhopal disaster). It doesn't have to be perfect, just better than humans. And in fact, I'd argue that by having no deterministic outcomes prevents systemic failure,…
> The only barrier for higher stakes applications is going to be the frequency of errors. Frequency and strength. My issue with e.g. image classifiers is that when they’re wrong, they’re catastrophically wrong — they don’t misidentify a housecat as a puma, they misidentify a cat as an ostrich.
Or, put in the language of risk, probability and severity