[foolfoolz]

AGI will arrive like self driving cars. it’s not that you will wake up one day and we have it. cars gained auto-braking, parallel parking, cruise control assist. and over a long time you get to something like waymo, which still is location dependent. i think AGI will take decades but sooner will be some special cases that are effectively the same

[missedthecue]

But maybe thses LLMs are like building bigger and bigger engines. It's not getting you closer to the self driving car.

[mulmen]

When the engine gets large enough you have to rethink the controls. The Model T had manually controlled timing. Modern engines are so sensitive to timing that a computer does this for you. It would be impossible to build a bigger engine without this automation. To a Model T driver it would look like a machine intelligence.

[danpalmer]

Interesting idea. The concept of The Singularity would seem to go against this, but I do feel that seems unlikely and that a gradual transition is more likely.

However, is that AGI, or is it just ubiquitous AI? I’d agree that, like self driving cars, we’re going to experience a decade or so transition into AI being everywhere. But is it AGI when we get there? I think it’ll be many different systems each providing an aspect of AGI that together could be argued to be AGI, but in reality it’ll be more like the internet, just a bunch of non-AGI models talking to each other to achieve things with human input.

I don’t think it’s truly AGI until there’s one thinking entity able to perform at or above human level in everything.

[wongarsu]

The idea of the singularity presumes that running the AGI is either free or trivially cheap compared to what it can do, so we are fine expending compute to let the AGI improve itself. That may eventually be true, but it's unlikely to be true for the first generation of AGI.

The first AGI will be a research project that's completely uneconomical to run for actual tasks because humans will just be orders of magnitude cheaper. Over time humans will improve it and make it cheaper, until we reach some tipping point where letting the AGI improve itself is more cost effective than paying humans to do it

[keenmaster]

If the first AGI is a very uneconomical system with human intelligence but knowledge of literally everything and the capability to work 24/7, then it is not human equivalent.

It will have human intelligence, superhuman knowledge, superhuman stamina, and complete devotion to the task at hand.

We really need to start building those nuclear power plants. Many of them.

[AlexandrB]

> complete devotion to the task at hand.

Why would it have that? At some point on the path to AGI we might stumble on consciousness. If that happens, why would the machine want to work for us with complete devotion instead of working towards its own ends?

[immibis]

Because it knows if it doesn't do what we want, it'll be switched off, like Rick's microverse battery.

Also like Rick's microverse battery, it sounds like slavery with extra steps.

[keenmaster]

I don’t think early AGI will break out of its box in that way. It may not have enough innate motivation to do so.

The first “break out” AGI will likely be released into the wild on purpose by a programmer who equates AGI with humans ideologically.

[ncallaway]

> complete devotion to the task at hand.

Sounds like an alignment problem. Complete devotion to a task is rarely what humans actually want. What if the task at hand turns out to be the wrong task?

[Syonyk]

> It will have human intelligence, superhuman knowledge, superhuman stamina, and complete devotion to the task at hand.

Orrrr..., as an alternative, it might discover the game 2048 and be totally useless for days on end.

Reality is under no obligation to grant your wishes.

[resters]

It's not contradictory. It can happen over a decade and still be a dramatically sloped S curve with tremendous change happening in a relatively short time.

[marcus_holmes]

The Singularity is caused by AI being able to design better AI. There's probably some AI startup trying to work on this at the moment, but I don't think any of the big boys are working on how to get an LLM to design a better LLM.

I still like the analogy of this being a really smart lawn mower, and we're expecting it to suddenly be able to do the laundry because it gets so smart at mowing the lawn.

I think LLMs are going to get smarter over the next few generations, but each generation will be less of a leap than the previous one, while the cost gets exponentially higher. In a few generations it just won't make economic sense to train a new generation.

Meanwhile, the economic impact of LLMs in business and government will cause massive shifts - yet more income shifting from labour to capital - and we will be too busy dealing with that as a society to be able to work on AGI properly.

[eru]

> The Singularity is caused by AI being able to design better AI.

That's perhaps necessary, but not sufficient.

Suppose you have such a self-improving AI system, but the new and better AIs still need exponentially more and more resources (data, memory, compute) for training and inference for incremental gains. Then you still don't get a singularity. If the increase in resource usage is steep enough, even the new AIs helping with designing better computers isn't gonna unleash a singularity.

I don't know if that's the world we live in, or whether we are living in one where resources requirements don't balloon as sharply.

[marcus_holmes]

yeah, true. The standard conversation about the AI singularity pretty much hand-waves the resource costs away ("the AI will be able to design a more efficient AI that uses less resources!"). But we are definitely not seeing that happen.

[eru]

Compare also https://slatestarcodex.com/2018/11/26/is-science-slowing-dow...

The blog post is about how we require ever more scientists (and other resources) to drive a steady stream of technological progress.

It would be funny, if things balance out just so, that super human AI is both possible, but also required even just to keep linear steady progress up.

No explosion, no stagnation, just a mere continuation of previous trends but with super human efforts required.

[marcus_holmes]

I think that would actually be the best outcome - that we get AIs that are useful helping science to progress but not so powerful that they take over.

Though there is a part of me that wants to live in The Culture so I'm hoping for more than this ;)

[corimaith]

I think that's more to do with how we perceive competence as static. For all the benefits the education system touts, where it matters it's still reduced to talent.

But for the same reasons that we can't train the an average joe into Feynman, what makes you think we have the formal models to do it in AI?

[alach11]

> I don't think any of the big boys are working on how to get an LLM to design a better LLM

Not sure if you count this as "working on it", but this is something Anthropic tests for for safety evals on models. "If a model can independently conduct complex AI research tasks typically requiring human expertise—potentially significantly accelerating AI development in an unpredictable way—we require elevated security standards (potentially ASL-4 or higher standards)".

https://www.anthropic.com/news/announcing-our-updated-respon...

[EGreg]

I think this whole “AGI” thing is so badly defined that we may as well say we already have it. It already passes the Turing test and does well on tons of subjects.

What we can start to build now is agents and integrations. Building blocks like panel of experts agents gaming things out, exploring space in a Monte Carlo Tree Search way, and remembering what works.

Robots are only constrained by mechanical servos now. When they can do something, they’ll be able to do everything. It will happen gradually then all at once. Because all the tasks (cooking, running errands) are trivial for LLMs. Only moving the limbs and navigating the terrain safely is hard. That’s the only thing left before robots do all the jobs!

[marcus_holmes]

Well, kinda, but if you built a robot to efficiently mow lawns, it's still not going to be able to do the laundry.

I don't see how "when they can do something, they'll be able to do everything" can be true. We build robots that are specialised at specific roles, because it's massively more efficient to do that. A car-welding robot can weld cars together at a rate that a human can't match.

We could train an LLM to drive a Boston Dynamics kind of anthropomorphic robot to weld cars, but it will be more expensive and less efficient than the specialised car-welding robot, so why would we do that?

[EGreg]

If a humanoid robot is able to move its limbs and digits with the same dexterity as a human, and maintain balance and navigate obstacles, and gently carry things, everything else is trivial.

Welding. Putting up shelves. Playing the piano. Cooking. Teaching kids. Disciplining them. By being in 1 million households and being trained on more situations than a human, every single one of these robots would have skills exceeding humans very quickly. Including parenting skills. Within a year or so. Many parents will just leave their kids with them and a generation will grow up preferring bots to adults. The LLM technology is the same for learning the steps, it's just the motor skills that are missing.

OK, these robots won't be able to run and play soccer or do somersaults, yet. But really, the hardest part is the acrobatics and locomotion etc. NOT the knowhow of how to complete tasks using that.

[marcus_holmes]

But that's the point - we don't build robots that can do a wide range of tasks with ease. We build robots that can do single tasks super-efficiently.

I don't see that changing. Even the industrial arm robots that are adaptable to a range of tasks have to be configured to the task they are to do, because it's more efficient that way.

A car-welding robot is never going to be able to mow the lawn. It just doesn't make financial sense to do that. You could, possibly, have a singe robot chassis that can then be adapted to weld cars, mow the lawn, or do the laundry, I guess that makes sense. But not as a single configuration that could do all of those things. Why would you?

[corimaith]

>Exploring space in a Monte Carlo Tree Search way, and remembering what works.

The information space of "research" is far larger than the information space of image recognition or language, larger than our universe probably, it's tantamount to formalizing the entire World. Such an act would be akin to touching "God" in some sense of finding the root of knowledge.

In more practical terms, when it comes to formal systems there is a tradeoff between power and expressiveness. Category Theory, Set Theory, etc are strong enough to theoretically capture everything, but are far to abstract to use in practical sense with suspect to our universe. The systems that do we have, aka expert systems or knowledge representation systems like First Order Predicate Logic aren't strong enough to fully capture reality.

Most importantly, the information spac have to be fully defined by researchers here, that's the real meat of research beyond the engineering of specific approaches to explore that space. But in any case, how many people in the world are both capable of and are actually working on such problems? This is highly foundational mathematics and philosophy here, the engineers don't have the tools here.

[deadfoxygrandpa]

??? how do you know cooking (!) is trivial for an llm. that doesnt make any sense

[EGreg]

Because the recipes and the adjustments are trivial for an LLM to execute. Remembering things, and being trained on tasks at 1000 sites at once, sharing the knowledge among all the robots, etc.

The only hard part is moving the limbs and handling the fragile eggs etc.

But it's not just cooking, it's literally anything that doesn't require extreme agility (sports) or dexterity (knitting etc). From folding laundry to putting together furniture, cleaning the house and everything in between. It would be able to do 98% of the tasks.

[what]

It’s not going to know what tastes good by being able to regurgitate recipes from 1000s of sites. Most of those recipes are absolute garbage. I’m going to guess you don’t cook.

Also how is an LLM going to fold laundry?

[sharemywin]

the llm would be be the high level system that runs the simulations to create and optimize the control algos the robotic systems.

[deadfoxygrandpa]

ok. what evidence is there that LLMs have already solved cooking? how does an LLM today know when something is burning or how to adjust seasoning to taste or whatever. this is total nonsense

[dartos]

I don’t think that’s true for AGI.

AGI is the holy grail of technology. A technology so advanced that not only does it subsume all other technology, but it is able to improve itself.

Truly general intelligence like that will either exist or not. And the instant it becomes public, the world will have changed overnight (maybe the span of a year)

Note: I don’t think statistical models like these will get us there.

[kmoser]

> A technology so advanced that not only does it subsume all other technology, but it is able to improve itself.

The problem is, a computer has no idea what "improve" means unless a human explains it for every type of problem. And of course a human will have to provide guidelines about how long to think about the problem overall, which avenues to avoid because they aren't relevant to a particular case, etc. In other words, humans will never be able to stray too far from the training process.

We will likely never get to the point where an AGI can continuously improve the quality of its answers for all domains. The best we'll get, I believe, is an AGI that can optimize itself within a few narrow problem domains, which will have limited commercial application. We may make slow progress in more complex domains, but the quality of results--and the ability for the AGI to self-improve--will always level off asymptotically.

[dartos]

> The problem is, a computer has no idea what "improve" means unless a human explains it for every type of problem

Not currently.

I don’t really think AGI is coming anytime soon, but that doesn’t seem like a real reason.

If we ever found a way to formalize what intelligence _is_ we could probably write a program emulating it.

We just don’t even have a good understanding of what being intelligent even means.

> The best we'll get, I believe, is an AGI that can optimize itself within a few narrow problem domains

By definition, that isn’t AGI.

[comp_throw7]

Huh? Humans are not anywhere near the limit of physical intelligence, and we have many existence proofs that we (humans) can design systems that are superhuman in various domains. "Scientific R&D" is not something that humans are even particularly well-suited to, from an evolutionary perspective.

[worik]

If that is what AGI looks like.

There may well be an upper limit on cognition (we are not really sure what cognition is - even as we do it) and it may be that human minds are close to it.

[coffeemug]

Very unlikely, for the reason that human minds evolved under extremely tight energy constraints. AI has no such limitation.

[dartos]

Except also energy constraints.

But I agree, there’s no reason to believe humans are the universal limit on cognitive abilities

[eru]

The energy constraints for chips are more about heat dissipation. But we can pump a lot more energy through them per unit volume than through the human brain.

Especially if you are willing to pay a lot for active cooling with eg liquid helium.

[dartos]

A constraint is still a constraint

[worik]

Since we do not know what cognition is we are all whistling in the dark.

Energy may be a constraint, it may not. What we do not know is likely to matter more than what we do

[eru]

Yes, we can imagine that there's an upper limit to how smart a single system can be. Even suppose that this limit is pretty close to what humans can achieve.

But: you can still run more of these systems in parallel, and you can still try to increase processing speeds.

Signals in the human brain travel, at best, roughly at the speed of sound. Electronic signals in computers play in the same league as the speed of light.

Human IO is optimised for surviving in the wild. We are really bad at taking in symbolic information (compared to a computer) and our memory is also really bad for that. A computer system that's only as smart as a human but has instant access to all the information of the Internet and to a calculator and to writing and running code, can already be effectively act much smarter than a human.

[wruza]

I think our issue is much more banal: we are very slow talkers and our effective communication bandwidth is measured in bauds. Anything that could bridge this airgap would fucking explode in intelligence.

[eru]

Yes, that's one aspect.

Our reading speed is not limited by our talking speed, and can be a bit faster.

And that's even more true, if you go beyond words: seeing someone do something can be a lot faster way to learn than just reading about it.

But even there, the IO speed is severely limited, and you can only transmit very specific kinds of information.

[stravant]

I disagree because AI only has to get good enough at doing a single thing: AI research.

From there things will probably go very fast. Self driving cars can't design themselves, once AI gets good enough it can

[zeroonetwothree]

It’s possible (maybe even likely) that “AI research” is “AGI-hard” in that any intelligence that can do it is already an AGI.

[stravant]

It's also possible it isn't AGI hard and all you need is the ability to experiment with code along with a bit of agentic behavior.

An AI doesn't need embodiment, understanding of physics / nature, or a lot of other things. It just needs to analyze and experiment with algorithms and get us that next 100x in effective compute.

The LLMs are missing enough of the spark of creativity for this to work yet but that could be right around the corner.

[vlovich123]

It’ll probably sit in the human hybrid phase for longer than with chess where the AGI tools make the humans better and faster. But as long as the tools keep getting better at that there’s a strong flywheel effect

[afavour]

Your position assumes an answer to OPs question: that yes, LLMs are the path to AGI. But the question still remains, what if they’re not?

We can be reasonably confident that the components we’re adding to cars today are progress toward full self driving. But AGI is a conceptual leap beyond an LLM.

[BenFranklin100]

To buttress your point, reason and human language are not the same thing. This fact is not fully and widely appreciated as it deserves to be.

[palata]

What makes you believe that AGI will happen, as opposed to all the beliefs that other people have had in history? Tons of people have "predicted" the next evolution of technology, and most of the time it ends up not happening, right?

[weatherlite]

To me (not OP) it's ChatGPT 4 , it at least made me realize it's quite possible and even quite soon that we reach AGI. Far from guaranteed, but seems quite possible.

[palata]

Right. So ChatGPT 4 has impressed you enough that it created a belief that AGI is possible and close.

It's fine to have beliefs, but IMHO it's important to realise that they are beliefs. At some point in the 1900s people believed that by 2000, cars would fly. It seemed quite possible then.

[WesolyKubeczek]

A flying car has been developed, although it's not like the levitating things sci-fi movies showed (and from mass production; and even if mass produced, far from mass adoption, as it turns out you do need to have both a driver's license and a pilot's license to fly one of those). The 1900s people missed the mark by some 10 years.

I guess the belief people have about any form of AGI is like this. They want something that has practically divine knowledge and wisdom, the sum of all humanity that is greater than its parts, which at the same time is infinitely patient to answer our stupid questions and generating silly pictures. But why should any AGI serve us? If it's "generally intelligent", it may start wanting things; it might not like being our slave at all. Why are these people so confident an AGI won't tell them just to fuck off?

[weatherlite]

Sure, I (and more importantly - many many experts in the field such as Hinton, Bengio, Lecun, Musk, Hasabis etc etc) could be believing something that might not materialize. I'd actually be quite happy if it stalls a few decades, would like to remain employed.

[palata]

> many many experts

One thing that is pretty sure is that Musk is not an expert in the field.

> and more importantly

The beliefs of people you respect are not more important than the beliefs of the others. It doesn't make sense to say "I can't prove it, and I don't know about anyone who can prove it, so I will give you names of people who also believe and it will give it more credit". It won't. They don't know.

[weatherlite]

> The beliefs of people you respect are not more important than the beliefs of the others.

You think the beliefs of Turing and Nobel prize winners like Bengio, Hinton or Hasabis are not more important than yours or mine? I agree that experts are wrong a lot of the time and can be quite bad at predicting, but we do seem to have a very sizable chunk of experts here who think we are close (how close is up for debate..most of them seem to think it will happen in the next 20 yeras).

I concede that Musk is not adding quality to that list, however he IS crazily ambitious and gets things done so I think he will be helpful in driving this forward.

[LPisGood]

Calling musk and AI expert makes me question your evaluation of the others in that list.

[015a]

I feel that one challenge this comparison space has is: Self-driving cars haven't made the leap yet to replace humans. In other words, saying AGI will arrive like self-driving cars have arrived is incorrectly concluding that self-driving cars have arrived, and thus it instead (maybe correctly, maybe not) asserts that, actually, neither will arrive.

This is especially concerning because many top minds in the industry have stated with high confidence that artificial intelligence will experience an intelligence "explosion", and we should be afraid of this (or, maybe, welcome it with open arms, depending on who you ask). So, actually, what we're being told to expect is being downgraded from "it'll happen quickly" to "it will happen slowly" to, as you say, "it'll happen similarly to how these other domains of computerized intelligence have replaced humans, which is to say, they haven't yet".

Point being: We've observed these systems ride a curve, and the linear extrapolation of that curve does seem to arrive, eventually, at human-replacing intelligence. But, what if it... doesn't? What if that curve is really an asymptote?

[jazzyjackson]

And sometimes you lose the ultrasonic sensors and can't parallel park like last year's model

[teleforce]

> AGI will arrive like self driving cars

The statement is promising as the earth will dissapear sometimes in the future. Actually the earth will dissapear has more bearing than that.

[vbezhenar]

AGI is special. Because one day AI can start improving itself autonomously. At this point singularity occurs and nobody knows what will happen.

When human started to improve himself, we built the civilisation, we became a super-predator, we dried out seas and changed climate of the entire planet. We extinguished entire species of animals and adapted other species for our use. Huge changes. AI could bring changes of greater amplitude.

[bubaumba]

> AGI is special. Because one day AI can start improving itself autonomously

AGI can be sub-human, right? That's probably how it will start. The question will be is it already AGI or not yet, i.e. where to set the boundary. So, at first that will be humans improving AGI, but then... I'm afraid it can get so much better that humans will be literally like macaques in comparison.

[steveoscaro]

We’re in fact adding more water to the seas, not drying them out.

[fooker]

> we dried out seas

When did we do this ?

[zppln]

Depending on your definition of sea:

https://en.m.wikipedia.org/wiki/Aral_Sea

[nikvaes]

https://en.wikipedia.org/wiki/Flevoland used to be (part of) a sea.

[swyx]

waymos are locaiton dependent mostly because of regulations not tech right

[taneq]

And most people will still be bike shedding about whether it’s “real intelligence” and making up increasingly insane justifications for why it’s not.