[BoiledCabbage]

> That's what ultimately depresses me about AI. It's still just a parlor trick. We haven't actually taught computers to think, to reason, to be innovative.

And what do you feel when we make these parlor tricks more capable than us at the majority of tasks?

And what do you feel when we understand it well enough to realize we're the same type of parlor tricks?

To me it seems like you're most interested in a magic 'aha' moment and will miss or not be prepared for how the road in front of us likely unfolds.

[keiferski]

And what do you feel when we understand it well enough to realize we’re the same type of parlor tricks?

That’s called positivism and it has a lot of philosophical issues. I wouldn’t be so quick to assume that sensory appearance is equivalent to reality.

https://en.wikipedia.org/wiki/Positivism

[bondarchuk]

Sensory appearance not being equivalent to reality does not have any relevance to the question of AI and humans ultimately being the same kind of information-processing system. Just handwaving "that's X philosophical position and it has problems" does not strike me as a good argument either unless you manage to explain how these problems pertain to the question at hand.

[keiferski]

Unless AI becomes indistinguishable from human beings on a cellular level, yes, it’s entirely relevant and is the single most relevant thing. A lot of people seem to think that if an AI can simulate the appearance of a human being, that makes them equivalent to one. It might introduce some problems WRT to determining if an entity is human or not, but this doesn’t somehow prove they humans are just a “parlor trick.”

This is a positivistic argument and as I pointed out, positivism has a lot of issues. The best counter argument IMO being that it’s needlessly reductive. This is all covered pretty clearly in the link.

[ben_w]

> Unless AI becomes indistinguishable from human beings on a cellular level, yes, it’s entirely relevant and is the single most relevant thing.

I disagree.

Thought experiment: design a circuit which has as many inputs and outputs as a biological neurone, such that it always maps inputs to outputs in the same way (including the observation that this isn't a static map but one which changes over time), then connect them as neurons are in one of us.

While clearly nothing like an natural brain on a cellular level, I believe this is a sufficient similarity to be "the same parlour tricks".

The question then is: how close does the design actually need to be, while not losing anything of importance?

Perceptrons were only ever a toy model, so they may well be insufficient; but on the other hand, for a sense of scale, GPT-3 is about the complexity of a rodent brain rather than a human brain — and that suggests that humans could learn to be simultaneous experts in many dozens of fields and languages with a mere tenth of a percentage point of our brains if only we lived long enough to read the entire internet.

Which matters most — neurons, connective structure, learning environment, or something else — is, I think, still an open question. But even between all the differences, AI collectively are general purpose enough to at least suspect these things have got a lot of similarities where it matters.

[bondarchuk]

>A lot of people seem to think that if an AI can simulate the appearance of a human being, that makes them equivalent to one.

That is not what BoiledCabbage was saying. He was saying: "And what do you feel when we understand it well enough to realize we're the same type of parlor tricks?"

>This is a positivistic argument and as I pointed out, positivism has a lot of issues. The best counter argument IMO being that it’s needlessly reductive. This is all covered pretty clearly in the link.

You're not really making any specific claim about what is wrong with BoiledCabbage's speculation, and why this specific thing is wrong. "That's wrong because positivism, it's all in this 5k word wikipedia article!" just doesn't prove anything.

[keiferski]

If you haven’t done the reading, I can’t explain it to you in a HN comment. I’m not trying to be snarky about it, but I genuinely don’t know what else to tell you. This is a pretty foundational ideal in the philosophy of science.

What’s wrong with the speculation is that it’s a positivistic argument that is needlessly reductive. It’s reductive because it assumes that appearing human-like is equivalent to being human.

The fact that we can understand how “AI” works as a parlor trick yet appears human-like in no way implies that human beings are nothing more than the same parlor trick processes. To argue that it does is to make a positivistic argument that doesn't take in account a whole host of other things. As noted in the Criticism section of the article (which is hardly 5,000 words) there are many issues with this approach.

[bondarchuk]

>It’s reductive because it assumes that appearing human-like is equivalent to being human.

I don't read that assumption into BoiledCabbage's statement at all: "[..] when we understand it well enough to realize we're the same type of parlor tricks?" This clearly implies a (hypothetical) deeper understanding of processes in the brain and their specific qualities, rather than (as you seem to be implying) a mere comparison of the outputs.

Edit: anyway, the criticism section opens like this:

>Historically, positivism has been criticized for its reductionism, i.e., for contending that all "processes are reducible to physiological, physical or chemical events," "social processes are reducible to relationships between and actions of individuals," and that "biological organisms are reducible to physical systems."

This (at least the 1st and 3rd quoted item, while I think the 2nd one is just out of scope) is exemplary of the kind of things that are obviously true for anyone but a subset of philosophers clinging to magical and unprovable beliefs about the human mind. I asked you to elaborate your argument precisely because if it all boils down to simply rejecting physicalism (in philosophy of mind terms) there's nothing new to argue about. The recurring discussion about "AI can never be like humans" is only interesting when the participants do a little bit more than just staking out their own position in idealism vs dualism vs physicalism terms and regurgitating all the known debates between these camps.

[__loam]

That statement also has no basis in neuroscience.

[jmopp]

Computers are already better than humans at a wide variety of tasks. Text generation just happens to now be one of those tasks. But if you look at the prompt -> output -> prompt feedback loop, it's clear that the human submitting the prompts is still doing all the thinking. We're not yet at the point where the AI can prompt itself and improve its output in a logical manner.

[ben_w]

> We're not yet at the point where the AI can prompt itself and improve its output in a logical manner.

Self-play is widely used to train game AI, and is the "A" in "GAN"; is there any point doing it on an LLM? Especially on the ones being sold as services where people get upset if they change over time?

[tessellated]

You really should take a look at Code Interpretor:

https://www.latent.space/p/code-interpreter#details

[emodendroket]

> And what do you feel when we make these parlor tricks more capable than us at the majority of tasks?

This seems like the logical fallacy of "begging the question" since it is far from apparent to me that they are "more capable than us at the majority of tasks."

[ben_w]

It's certainly difficult to enumerate all the things we humans actually do.

There's a lot of stuff we consider to be "common sense", sometimes those things are used to criticise AI and sometimes they're used to criticise other humans for not knowing them, but that is a category that we don't even think about until we notice the absence.

For the things not considered common sense, like playing chess (beats all humans) or speaking/reading foreign languages (more than I can name to a higher standard than my second language), to creating art (even if it regularly makes the common sense mistake of getting the number of fingers and limbs wrong it's still better and not just faster than most humans), to arithmetic (a Raspberry Pi Zero can do it faster than all humans combined), to symbolic maths, to flying planes…

A dev conference I was at recently had someone demonstrate how they hooked up their whatsapp voice calls to speech recognition, speech synthesis trained on their own voice, and an LLM, and the criticism of the people who got the AI replies was not "you're using an AI" (he had to actively demonstrate his use of AI to conversation partners who didn't believe him) but "you can't have listed to my message, you replied too quickly to have even played it all back."

[oldandtired]

It is impossible to enumerate all the things that we humans do. However, we can enumerate all the things that we create can do. Every system we create has its limitation due to the limitations that we create in them. All systems we create cannot exceed those limitations.

We make machines that are stronger, faster, and can have much finer motor control than we have as individual abilities. No machine we have created has the dexterity that we have.

Every computational system can be analysed in fine detail to determine the limits that we have built into them. It may take an enormous amount of time and effort to do so, but we can do it. No computational system that we have built is able to exceed the limited programming we place in it.

There is an enormous amount of hype that goes on about the current generation (and future generations) of these systems, but all of them are in the abilities that we have programmed into them. They are in all essentials completely stupid (in the worst possible way - non-sentient, non-intelligent).

Every logic error that we have made in building these systems is hidden in that code. One day, those errors will come back and bite us, but there is nothing intelligent or sentient in these systems. It is our errors, for which we are responsible, that will cause those problems.

We can use them as adjuncts to our sentience and intelligence - but all they are are tools, never anything more.

However, if we cede control to these systems, we are ceding control to something that is no better than fire (a good servant - a horrendous master). After forty years, I have seen far too often, hype by humans convince other humans to cede control to the systems that humans have made and the result has been various levels of chaos.

If anything, what we need to be careful of is how humans use these systems against other humans. This is the perennial problem that we face as we build new technology.

[ben_w]

Mostly I agree with you, but

> However, we can enumerate all the things that we create can do.

Not really, no. Even before AI, "Turing Complete" makes things extremely hard to enumerate; see Busy Beaver numbers for how small a system can be and still outside our ability to fully comprehend — needing to use up-arrow notation because exponentials aren't big enough is always good for a laugh.

[oldandtired]

With your example of "Turing Complete", we know what cannot be done and in this way, we have enumerated the things that can be done, if you like. You appreciate the humour required for the up-arrow notation - a very human quality.

You example of the Busy Beaver numbers, which was a recent interesting read, is a good example of what I was trying to point out. We have a definition and even if we cannot enumerate each number, we discuss and think about these in a rational way. At the moment, I am quite interested in Computer Algebra Systems (of which there are a variety) and I find it interesting just how limited these systems are and just how difficult it is to program into them the capabilities that humans use to solves various problems. The various discussions have been quite enlightening.

Mathematics is an interesting subject and I think shows up the intractability of ever getting that highly feared singularity.

All artificial computing systems are limited in ways we are not. Your "Turing Machine" example is one such case. The Halting Problem being a class example.

I think that far too often, we fail to recognise that what we create is not that great. We often stand in awe of the things we make without comprehending that these things are a very poor reflection of what is around us and what we ourselves are.

Every time some hype comes about these artificial stupidity systems, I look at my youngest granddaughter and see in her, capabilities that far exceed anything that we have created. Even my old buck of a goat demonstrates capabilities far, far in excess of anything we have created in all of our computational systems.

As I have said elsewhere here, we have to be careful that we do not cede control of our lives to systems that we think are more than they really are - systems that are limited, fragile and prone to failure.

[ben_w]

> All artificial computing systems are limited in ways we are not. Your "Turing Machine" example is one such case. The Halting Problem being a class example.

You appear to be asserting that humans can tell if a loop will end, when that loop is defined so that if it does it doesn't and if it doesn't it does.

> Even my old buck of a goat demonstrates capabilities far, far in excess of anything we have created in all of our computational systems.

How so?

Not saying this is necessarily false — GPT-3 is about as complex as the brain of a rodent, so it wouldn't exactly be surprising even though the LLM only does text and completely different AI do other things — but still, what exactly do goats do that's "far in excess"?

[adastra22]

AI systems are vastly better than humans at a wide variety of tasks. Better at handwriting recognition, better at scheduling, better at playing games, better at speech recognition and transcription, etc.

[cypress66]

I am skeptical on many of those. Speech recognition is not even close to human level. Whisper, and whatever Google uses will make a lot of mistakes on audio files that are trivial to any native speaker.

[adastra22]

In actual tests it is beyond human level. Humans actually mishear about 1 in 20 words during transcription tests; whisper does better.

[emodendroket]

But we don’t solely rely on how well we hear since we have knowledge that allows us to correct for poor hearing based on what is being said rather than forging ahead with a nonsense transcription. Machine transcription is definitely faster and cheaper but the end product isn’t “better,” and anyone who has read it can attest to that.

[ben_w]

> But we don’t solely rely on how well we hear since we have knowledge that allows us to correct for poor hearing based on what is being said rather than forging ahead with a nonsense transcription.

Good voice transcription AI already do that too; that's why they work best if they know which language they're operating in, as that means they can use the language to create a model of the most likely words.

I think the most recent WWDC from Apple even has a video about adding custom vocabulary for their speech engine to pick up on that covered some details in this exact topic, though I can't search right now.

[cypress66]

Well, those "actual tests" clearly don't reflect reality. This is obvious if you actually use whisper.

[oldandtired]

The question to ask is why?

The answer is that we have programmed these systems to do what we require. They cannot exceed but they fail becasue of errors that we have placed in these systems.

All of the tasks that you have mentioned have been programmed that way. It has taken human ingenuity to work out how to do this programming. The end result is a machine (non-sentient, non-intelligent) that is doing what we require.

If you look at game playing, a system was created to play Go and won and yet that same system fails to win against humans under many circumstances. The literature is there, yet not publicised for all the world to see. A result of keeping the hype in play.

If you look at speech recognition, these systems still fail when we humans work against them and yet, we humans still recognise what the machines fail at.

Just keep in mind that a tractor can move a greater amount of material than a human can, but it is still only a tool. A plane can travel faster and fly higher that a human can, but it is still only a tool.

We use these systems to augment our abilities and yet they are all limited in so many ways that we are not.

The upshot is that we can do amazing things with the things we create, but none of those things exist without us and all those things fail without us.

[ben_w]

> All of the tasks that you have mentioned have been programmed that way. It has taken human ingenuity to work out how to do this programming.

The successful Go AI were programmed to learn; we still can't program a decent Go AI with rules humans come up with.

> The literature is there

Do you have a link? Two Minute Papers just had a video about an AI systematic finding ways to confound other AI, but I thought we'd passed the point where the best Go AI could be so manipulated by humans…

[oldandtired]

Your example of the Go AI being programmed to learn is not all that accurate for what has been achieved here. I didn't keep the link for the discussion on the confounding of the Go AI system. What the discussion covered though was that there were simple Go configurations that the GO AI failed abysmally on when playing a human - it didn't learn here.

I have spent forty years dealing with all sorts of computer systems - designing, building, maintaining, repairing, redesigning and rebuilding. One thing I have learnt over that time is that none of the systems ever built has been error free in terms of the logic entailed within them. All to often, I have seen systems that were used to make decisions with and those using them assuming that the outputs were correct or reasonable. Yet on investigation, the logic entailed in them was completely rubbish.

We make assumptions and often we do not carefully check that those assumptions are actually real. I don't trust anything I write until I have gone over it with a fine tooth comb and then I will try to document all my assumptions and this usually shows up various logic errors or conditions that I didn't think about. I don't see this happening much out in the real world.

[ben_w]

> Your example of the Go AI being programmed to learn is not all that accurate for what has been achieved here.

What do you mean?

AlphaZero was trained entirely on self-play, and is a generic reinforcement learning algorithm. All it starts with are the rules (Chess, Go, Shogi) and a few million games later it beats — so far as I can see from a quick Google — all the humans, and most matches against AlphaGo Zero which learned the same way and which in turn beat AlphaGo Lee in every match, and that (unlike the aforementioned) was trained on examples of human matches in addition to self-play… but still learning from those examples as there's no known useful[0] set of rules that even says if a Go game is over let alone which moves are good.

There are AI which can find and exploit its weaknesses, but I've not seen anyone else suggest humans can defeat it.

> I didn't keep the link for the discussion on the confounding of the Go AI system. What the discussion covered though was that there were simple Go configurations that the GO AI failed abysmally on when playing a human - it didn't learn here.

Do you remember the name of the AI?

A bit of rummaging got me KataGo, but the humans had to use another AI to discover the weaknesses of KataGo rather than figuring it out for themselves.

And yes, KataGo absolutely does learn. The fact you can trivially stop the learning process is a feature not a bug for AI, precisely because it means any safety testing of the sort you're calling for is actually possible (albeit rather different than formal logic).

[0] pathological cases are easy — "board empty == not finished" — but not helpful.

[tsunamifury]

He will go on saying it’s a trick. It’s a form of denial I’m seeing everywhere now when faced with something so genuinely terrifying or identity challenging you can’t process it.

[emodendroket]

Perhaps I can say you're motivated by an Oedipus complex and we can keep the chain going of ad hominem with a thin psychobabble veneer to make it appear serious.