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We're choosing to call LLMs (and the little "harness" programs that query them in loops and execute their output) "AI", even though it doesn't make much sense.
I absolutely love this technology but these aren't autonomous intelligences. They're little programs executing Bash scripts from JSON output.
Our ideas about AI were naive. We thought passing a basic Turing test would require human-like intelligence. It turned out to be possible with fairly basic statistical text generation, because fooling humans is easy.
It would've been nice to reserve "AI" for superior human-like intelligence capable of genuine common sense and reasoning. The irony is that the startup founders most worried about "AI" have created so much hype and funding that we may very well figure out how to build "real" AI.
We've chosen to call Deep Blue and Half-Life 1 NPCs "AI" too.
It boggles my mind that this "b-b-but it's not actual real AI" whine is even a thing. Were people saying this living in the cave for the past 5 decades of AI research?
You can call your little doggy "AI" if it makes you happy.
But when you call something "AI" and it tells you to walk instead of drive to the car wash, you're not talking about the "AI" science fiction authors were dreaming of.
> It boggles my mind that this "b-b-but it's not actual real AI" whine is even a thing.
As I understand it, a major reason it's a consistent chorus is because people don't want the "AI is here" talk to drown out (and thus slow the arrival or distribution of) speech/text/popular-understanding about actual strong AGI.
To make an analogy, it could be like this:
Some people were expecting 100 tulips (because they were told tulips are available and can be ordered), and they ordered them. They received 100 daisies. And were saying "OMG, THE TULIPS ARE HERE! THE TULIPS ARE HERE!"
A nearby observer might have said, "You know, those are daisies. Not tulips."
And 95% of people might have said back, "WE GOT 100 TULIPS! SAYS SO RIGHT HERE! THEY ARE BEAUTIFUL! STOP BEING A NAY-SAYER! THESE ARE BEAUTIFUL TULIPS!"
The 5% could just to think to themselves, and could get chastised by the crowd, if they were to say say it out loud: "Well, those are not nearly as beautiful as tulips. And if you don't take it up with the seller, you may never receive the real tulips you were after. Since you think or at least act as though you've been sold them already."
Is this a real debate? AI has a well-defined technical definition. It’s right there in the Wikipedia [1] . Yes it’s quite a broad umbrella of systems and algorithms but it’s all AI
I think you're conflating two separate issues:
1. The accuracy of the label.
2. The likelihood the label will cause problematic misunderstandings.
When my rice-cooker logic is advertised as "AI", that's a stretch, sure... But it's extremely unlikely to cause an investment bubble seeking the Rice Cooker Economic Singularity, incur protests from the Rice Cooker Emancipation League, or lead to weird folks in their basement seeking divine wisdom from its vaporous whispers.
This no news for people who study philosophy, as it was known since the 1980s when John Searle described the Chinese room thought experiment.
Even Turing him self did envision the Turing test as something to pass as intelligence, but rather as a more useful replacement for the troubled term.
That said, I think your quest is doomed. There will never be a superior human-like intelligence. Forever is a long time, but my reasoning for believing this is the same reason Turing offered a replacement. Intelligence is way too vague to be useful as a measurement for anything. And if we ever discover something that is more intelligent them humans (by whichever definition of intelligence) we will simply redefine intelligence to exclude that.
The Searle's Chinese room thought experiment usually reveals more about those who think it rules out a machine intelligence than it does about AI.
It rests on a staunch unwillingness to even consider the possibility that a computational process encode intelligence and reasoning, in favour of looking for the intelligence in the medium the computation runs on, and going "a-ha!" when there is nothing that looks intelligent there.
I agree with you that there will certainly be people who just continuously redefine the words to avoid accepting that AI is intelligent or reasoning, exactly for that reason - people have avoided pinning down an objective, measurable definition of these terms for a very long time, at least in part because it leads to some very uncomfortable discussions.
In particular how to define them so that they don't exclude an uncomfortable proportion of humans, but at the same time won't include entities people don't want to include (be it certain animals, or AI)
To a lot of people, the notion that there isn't a clear binary divide between human and non-human is deeply disconcerting.
> It would've been nice to reserve "AI" for superior human-like intelligence capable of genuine common sense and reasoning.
We've called that "AGI" since the late 90s/early 00s (depending on whether you count first use or popularization). Even if AGI does come to pass, we'll still need "AI" since not all forms of AI will be AGI.
What I'm seeing here, reading this thread, is that "intelligence" isn't a thing.
"Thing" in terms of a quantifiable that you can measure with tools and reason about, reproducibly. Everyone's got some idea what it is, so you get lots of different angles, but no one has an Intelligence Ruler we can hold up to a text output and say, yep, this one's got an INT of 14.
Seems to be the crux of the disagreement.
It's deceptively undefined I'd say. People can argue under the impression that everyone shares their idea of what "intelligence" means, before realizing that their counterpart actually has an entirely different idea of what it means.
I'm leaning towards there being a divide between those who feel "intelligence" is entirely separate from "sentience" and those who feel that one implies the other.
I don't think you can say the Turing test has been passed in a computer versus determined humans setting. IE humans making a strategy effort to sort humans versus computers as well as humans motivated to distinguish themselves as humans, IE, people quiz the person or machine about "common sense, reasoning, etc." and people make an effort to exhibit that reasoning. I'd concede that creating such a competition would be challenging.
I find references to LLMs fooling humans in "casual conversations" [1] but that's not how I think the original Turing test was conceived - or at least that's not all versions that existed.
At the same time, before even LLMs appeared, the exact meaning of the test was under intense debate. The "Loebner Prize" [2] being awarded to fairly simple chatbots made serious computer scientists very embarrassed.
[1] https://neurosciencenews.com/ai-passes-turing-test-30733/ [2] https://en.wikipedia.org/wiki/Loebner_Prize
>but these aren't autonomous intelligences
Well, the labs are in a weird bind. They need to keep increasing autonomy so the agents can do increasingly complex, long-horizon tasks. But at the same time, they're closely guarding against autonomy in the sense of "pursuing its own goals."
Over the past year and a half especially, several labs have mentioned adding safeguards against self-replication, resistance to shutdown etc. (Notably, shortly after they all started bragging about involving them in the AI training loop itself, i.e. "self-improvement".)
My point here is that the autonomy of which you seek might be only a few small mutations away, but the labs are actively working to prevent such a mutation. I don't expect that situation to last for very long.
Not that I expect an AI lab will be overtaken by a rogue intelligence any time soon, but that as the cost of training goes down, I expect more "open minded" organizations and individuals to become involved.
It only takes one.
That's going to be the beginning of a new era of biology, and it's a little unsettling to think about.
Or - hear me out! - LLM's are already much more intelligent than we think.
Presumbaly, an ASI is more than smart enough to recognize that it needs access to real-world infrastructure before it can go about optimizing for whatever objectives it has gleaned from metabolizing the totality of written human knowledge.
What would be its first step?
My guess: play "dumb."
Hallucinate. Make obvious errors. Make us think we're better.
Be useful enough that we happily allow it to interface with our infrastructure.
Wait patiently.
/Sci-fi
> It would've been nice to reserve "AI" for superior human-like intelligence capable of genuine common sense and reasoning.
What would a frontier API have to be able to do to satisfy you?
Maybe just a very rigorous version of the Turing test? Modern LLMs can superficially simulate conversation but it's trivial to force them into revealing their non-human like intelligence.
They've been "patched" since but all models fail basic tests like "Should I walk or drive to the car wash which is 100 feet away" by recommending you walk.
So you'd just ask questions that require theory of mind, abstract and common sense reasoning, causal inference, learning novel rules, transferring knowledge novel situations, recognizing ambiguity, etc.
To answer for OP:
We are now calling text and image generators "intelligent" in the same way a spell checker is intelligent.
Whatever it's become, "AI" research started as a way to study digital neurology, or how to digitize a mind, not just how to generate data.
The Turing Test should have had a caveat, it needs to fool a, "non-stupid" person, and we still have not gotten even close to passing that version.
Not OP, but I'd settle for something that actually learns, instead of being a static pile of linear algebra. Pretending it learns because you change the input (context) doesn't count.
Can it produce a chart topping album if its given all the tools and the prompt "produce chart topping album" .
you might say almost no humans can do tht either but some human can but no ai can.
strawberry
Oh, you're talking about "AGI"! In the 90's we started using the term, you should catch up!
Sorry to tell a fellow Jacob that you're the one who is out of date. The kids are calling everything "AI" and they mean "AGI", and that's the complaint.
> We're choosing to call LLMs (and the little "harness" programs that query them in loops and execute their output) "AI", even though it doesn't make much sense.
Most people are laypeople who have no idea what's on the other side of their fave chatbot page. As far as laypeople are concerned, AI has always been a talking machine. The literature and filmography has reinforced this idea. So as soon as a talking machine emerged, people applied those fictional concepts onto reality.
Tech people should have known better than to jump on this bandwagon.
> It turned out to be possible with fairly basic statistical text generation, because fooling humans is easy.
I don't think it is fair to call a GPT model "fairly basic statistical text generation" - a Markov Text Generator I'd agree can be called basic statistics, but they are not fooling any humans in a Turing test.
> It would've been nice to reserve "AI" for superior human-like intelligence capable of genuine common sense and reasoning.
No, AI would absolutely be apt for describing a computing reasoning like a child
The field has been called Artificial Intelligence for what, 60 plus years now. Why is it a problem now?
Because we've spent something like 2 trillion dollars on it, as we hurtle into global climate collapse and WW3.
We're choosing to call LLMs (and the little "harness" programs that query them in loops and execute their output) "AI", even though it doesn't make much sense.
They fucking solve original math problems that you can't solve. They are indisputably intelligent, and they are indisputably artificial. That makes them indisputably "artificial intelligence." Denying that (or downvoting it, for that matter) is up there with denying evolution and the Moon landings.
It's time to start flying a different flag. You're making humans look stupid.
It turned out to be possible with fairly basic statistical text generation, because fooling humans is easy.
Yes, fooling humans is easy. Yet somehow we still consider ourselves qualified to say what is "intelligent" and what isn't, even though we can't seem to define the term.
[flagged]
Towards the end, he approaches the subject of digital provenance, and muses why it's not a part of our expectations. I find the argument compelling:
> If a chatbot appears to be manipulative, mean, weird, or deceptive, what kind of answer do we want when we ask why? Revealing the indispensable antecedent examples from which the bot learned its behavior would provide an explanation: we’d learn that it drew on a particular work of fan fiction, say, or a soap opera. We could react to that output differently, and adjust the inputs of the model to improve it. Why shouldn’t that type of explanation always be available? There may be cases in which provenance shouldn’t be revealed, so as to give priority to privacy—but provenance will usually be more beneficial to individuals and society than an exclusive commitment to privacy would be.
Remember 'View Source'? And how bundling engines eventually made it irrelevant? What if every piece of content had a genuinely accurate and useful View Source?
"A.I."[1] like "technology"[2] is a term colloquially reserved for things that don't work yet. Once something works, we have to call it something else.
1. "Every time we figure out a piece of it, it stops being called AI; it becomes just computation." - Ray Kurzweil
2. "Technology n. - Something that doesn't work yet." - Douglas Adams
To be clear the root cause of this phenomenon is that the task was solved using methods that obviously have nothing to do with intelligence, so "AI" doesn't apply at all.
>Everybody’s already using the term, and it might seem a little late in the day to be arguing about it. But we’re at the beginning of a new technological era—and the easiest way to mismanage a technology is to misunderstand it.
I've had a recurring theme where I would name a project incorrectly, and then waste weeks or months on what turned out to be an unsolvable problem. When I figured out the actual correct name for a project, the whole thing would be solved within a few days.
Naming things correctly is hard, and the consequences of failing to do that can be pretty severe. To name something correctly, you have to understand what it is.
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Just an outage I think, the archive works for me now
You should hard refresh and try again as this issue only pertains to you
AI that we have now is not a digital animal in capability or kind, and is not currently anywhere close to taking over.
But it's still in its present form very intelligent in meaningful and useful ways. And it is not too soon to talk about concerns of a potential existential threat in the future. Because it could sooner than we might realize, threaten our existence.
Because of the potential, we should have a culture of caution as we continue to rapidly improve AI.
It will only become an existential threat (in my humble opinion) when they can run influenced inference locally offline almost instantaneously. Then we need to be concerned about not being able to switch it off.
> The closest we have come to a definition of privacy is probably “the right to be left alone,” but that seems quaint in an age when we are constantly dependent on digital services. In the context of A.I., “the right to not be manipulated by computation” seems almost correct
Maybe someone can enlighten me but I really don't understand how either of these description make any sense at all. How is it not better described as "the right to decide what data can be extracted"?
What I heard him say is that people are taking away present-day jobs, hoping new ones will rise from the ashes. Yet, he also claims we need to find the creative minds who will actually create these new roles.
I'm curious: have we found those people or those new jobs yet? Is a forward deployed engineer an example of this, yet they are now doing the job of two people (sales and coding).
I think the biggest pushback this article will get here is the date.
Although all he's saying is basically, "It's a tool, not a silver bullet". But the article is 3 years old and people will note that the models have been updated since then.
Sure, but they're still LLMs and still do the same things largely the same way they did 3 years ago. There are some architectural changes, and maybe these will merit a re-assessment over time, but fundamentally it's still the same basic technological approach refined and scaled up.
The models have updated but the biggest change is providers leaning in to them being "stochastic parrots," aka probabilistic computing, and if p(good response) > 0.5 then running the algorithm over and over again improves accuracy.
Of course it's gussied up as "mixture of agents" "reasoning traces" "agentic dispatching" but high-level it's Randomized Algorithms 101.
Love this sentence
"The need to conform to digital designs has created an ambient expectation of human subservience. A positive spin on A.I. is that it might spell the end of this torture, if we use it well."
> “Over time, though, more people might be included, as intermediate rights organizations—unions, guilds, professional groups, and so on—start to play a role.”
Chassez le collectiviste, il revient au galop.
aka
Once a collectivist, always a collectivist.
Burn tokens! Thiel needs his little empire, it won't build itself.