It's also "out-brute forcing them." It just never gets tired. If a mathematician picks a research direction and spends a whole week on it and it doesn't pan out, they will likely be annoyed, need a break for a while, etc. This thing just does not ever get tired or discouraged or care; it's just onto the next thing until something ends up working.
AI has sitzfleisch
https://en.wikipedia.org/wiki/J._Robert_Oppenheimer#:~:text=...
My browser doesn't do the fancy URL text selection...
sitzfleisch: the ability to endure or carry on with an activity
Something Oppenheimer did not have, apparently.
loaned from German, where it's originally a way to say buttocks, literally "sitting flesh". If you have more Sitzfleisch you can sit for longer. Both in the literal sense (a bigger butt makes sitting more comfortable) and in the figurative sense (having the mental ability to sit for longer, get more desk work done)
I think there is an IT bit of humor from about 1 decade+ back where the people who's proposals won out in meeting were the ones that could keep from needing to go to the bathroom longer.
Fascinating crossover from literal to figurative that you find so often when you trace language back far enough.
Don’t worry, the link provided by the GP did nothing to explain what was meant anyway.
This is fantastic. Now I have a sophisticated-sounding german word for my attention deficit.
There's also a less flattering reading of the word, where Sitzfleisch means having a "flat ass" (from sitting too much, e. g. Sitzfleischparade describing a group of flat-arsed people, or something like Sitzfleischmaxxer, and so on).
Ass-maxxing.
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in Gujarati its "Gand vagar no loto". ( Utensil with Round Ass ). I guess every language as its equivalent.
This was such an interesting thing to learn
We Americans call it grit.
The connotation of grit to me feels different. Grit is pushing through adversity, rather than just tedium.
Maybe.
Grit can be the courage to endure adversity.
It can also be the resolve to endure tedium.
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Wow, what a great comparison. LLMs are great at reasoning but absolute dogshit at simple arithmetic. If there's a raw calculation involved I always tell it to use python to add it all up.
The abacus seems to date back around 4500 years.
If your goal is to implement an absurd comment you can use this one next time: instruct your LLM to implement Conway’s Game of Life to implement an abacus.
Because, you know, humans are notoriously poor at implementing the x86-64 instruction set in their minds. This is why God had to create Guido van Rossum.
Arguably Mathematica would be a better fit, but there are those who frequent this corner of the Internet who rather not have to read anything that might cause them to think about Stephen Wolfram.
So I won’t mention it.
Ever heard of string theory.
People go whole lives without being able to make it pan out.
String theory is a great example of a dead end kept alive by ego and sunk cost fallacy. An AI would have declared it dead and moved on 10 years earlier.
When people make these comments about string theory, are they at the forefront of quantum physics theory and have spent years on modern string theory? Or did they just watch a YouTube video and then keep parroting this?
You could reductio ad-absurdum this logic quite broadly. We all form beliefs about the world and its aspects, and almost always through fallible sources. Should one be confident about ones of questionable provenance? I say no. But forming beliefs from the information we have is a useful skill.
Nothing wrong with learning and being influenced. However, many posters on HN are very confident that string theory is a dead end. It makes me question if they’ve done cutting edge string theory or it is just some random software engineers who watched Sabina on YouTube.
The degree of confidence matters here.
In the age of infinite bullshit generators, the even more useful skill is being able to say "I don't know." Or "I'm not qualified to have a useful opinion on this so I'm just not going to say anything." I could write a bunch of stuff about my personal opinions on string theory and waste everyone's time, or I could just shut up and not be a human stoichastic parrot.
I watch three YouTube videos.
The Lambda-CDM model seems to be a dead end, but instead of recognising that, picking themselves up, and moving on, the Lambda-CDM Model Industrial Complex simply papered over the gaping holes with magical thinking.
Sciencism.
This isn't a great argument. Researchers who do not think string theory is good are not going to spend years on it. There are plenty of experts that dismiss string theory. I have no skin in the game, and don't care either way, fwiw.
I agree but I think it’s a little hopeful to believe AI will save string theory
I also just keep parroting that the Earth is not flat and a bunch of other things I've been told and then never questioned, since it seems to make sense.
When the flath-earth craze started I've been trying to at least get that bit actually personally verified. Haven't managed to do it to this day, though. So I'll just keep parroting various things without properly understanding them.
C'est la vie.
> When the flat-earth craze started I've been trying to at least get that bit actually personally verified. Haven't managed to do it to this day, though.
How do I say this in the most gentle way I can...?
Your brain is broke. No, seriously. If you can help it, try not to argue with anyone about anything, ever. You have a demonstrated inability to think clearly.
Your drive to verify must be very low then. There are hundreds of small logic reasonings or even experiments with which you can easily prove that a flat earth model is at least very complicated or even impossible.
Explaining Moon phases gets very complicated in any flat earth model. With binoculars you can see the shadows of craters on the moon's terminator. Or the phases of Venus whereas Mars doesn't have any.
Timezones are ridiculously hard to explain on a flat earth.
A proper theory must explain all of them and no flat earth model can do that. A round Earth OTOH easily does.
Or the just read Woit, uh, 20 years ago now, “not even wrong”.
Sabine has been at the forefront and has the goods: https://youtu.be/1mgxuVVUz40
And for the inevitable critics of Sabine...maybe Leonard Susskind is good enough for you: https://youtu.be/2p_Hlm6aCok
The error with this approach is that every single physics theory gets exactly the same criticisms.
You can take any of the theories that Hossenfelder would spend time on instead of the ones she does not like, and you would find (basically) a similar percentage of physicists saying it's a mistake to continue in this direction.
In other terms: for each physics theory, on 100 physicists, you have 5 physicists saying it is a mistake to continue working on it (number made up for illustration, and there is probably some variations, but you get the gist). You took one theory and found few physicists saying it is a mistake to continue working on it. You conclude, incorrectly, that it means this theory is fundamentally differently treated as any other theories.
(on top of that, it is unfortunate that Hossenfelder later screw up her image by doing way too much mistakes that someone reliable would not do)
> It's also "out-brute forcing them." It just never gets tired. If a mathematician picks a research direction and spends a whole week on it and it doesn't pan out, they will likely be annoyed, need a break for a while, etc. This thing just does not ever get tired or discouraged or care; it's just onto the next thing until something ends up working.
> String theory is a great example of a dead end kept alive by ego and sunk cost fallacy. An AI would have declared it dead and moved on 10 years earlier.
Not only are LLMs perfect machines with all the intelligence of humanity without any of our problems, they are also everything else. I wait to get my hands on one of those LLMs people on hn seem to be using. I want to believe too. Let me into the religion of the perfect thinking machine gods.
Ok Sabina, everyone is string theory is all just a bunch of egotistical morons.
No, not morons, but people who have built a career on string theory. At this point, even if they regret their decisions, it’s too late to turn back now.
I don't think it's a good argument. String theory is just "one application" of advanced mathematical physics. It's like saying that software developers specialised in ReactJS would lose their career if ReactJS is suddenly abandoned.
Not a fair comparison because one is exposed to real life market forces vs. academic inertia.
ReactJS devs will retrain when the market dies. Professors still publishing theories/experiments costing large amounts of public monies better spent elsewhere.
As opposed to having built a career complaining about string theory on youtube?
And that's the reason she's wrong?
You were the one introducing the argument "they are getting advantages out of it so we should be careful to not take what they say as an impartial view". Same can be told of Hossenfelder (personally, I would say that Hossenfelder has shown more clues that indeed she is not very reliable and would prefer caricatural sensationalistic descriptions, which is not what the typical string theory physicist does).
No, my point was only to refute the idea that people need to be egotistical or moronic (the only two options) to cling to an idea past its expiry date. People could also be “pot-committed” career-wise. Or they could have myriad other reasons (identity, sunk-cost fallacy, etc).
Nowhere did I suggest that “the reason for discrediting string theorists is that they have financial stakes in the idea.” Please try to be more charitable than that.
You said
> No, not morons, but people who have built a career on string theory. At this point, even if they regret their decisions, it’s too late to turn back now.
This is not presented as "yet another option that may or may not be the reality", this is presented as your conclusion of why we observe what we observe.
Maybe it is not what you are thinking, but you cannot blame people for interpreting your message the way you have written it.
I agree with you that there are several options, one of the most probable, that you did not mention, is that the situation of the string theory is just "normal" and some idiots are not able to understand that.
Spending your life's work on a theory that is widely agreed to be untestable is certainly a form of ego, or at least is more philosophy than science.
The "untestable" meme is just a thought terminating cliche. It's as if you believe no researchers ever considered the brilliant insight that the framework is difficult to test. History is littered with plenty of examples of a novel discovery, understanding, or technology yielding new opportunities for experimental design.
It's also a glib dismissal of the unexpected mathematical elegance of string theory that makes it so compelling. Worse, it completely ignores the material contributions to applied physics that string theory has made possible which is obviously worth "spending your life's work on" - as if people need to justify the value of their life's work to disinterested onlookers lest they be demeaned.
This is a pretty silly belief to hold about science. Plenty of strong, well held standards of the modern era were considered ridiculous fringe beliefs a century ago.
They were testable, no?
Not taking either side here - but surely a lot of cosmological phenomena couldn't be testable/verifiable at the time they were theorized either?
(thinking of black holes for example - they were theorized way before we had observations. And presumably a lot of particle physics can similarly be theorized before we built the technology to experimentally verify them)
Black holes were theorized and you could design experiments that, given the proper instruments, would allow them to be detected. Relativity was similar (famously, the curvature of spacetime was demonstrated during a solar eclipse by being able to see stars that should have been behind the sun).
String theory has nothing even theorized that would allow us to prove it.
Sometimes theories need engineering to catch up to become testable.
Well, we can test it, but you'll need to give me a ton of money in order for me to test it.
even if its not particularly relevant to the physical world around us, it still explored cool math
Also out-speeding them, and that was before high speed inference.
Out-ralphing them, you might say!
https://ghuntley.com/ralph/
AGI ≈ artificial stupidity × infinite persistence
> It's also "out-brute forcing them."
That is also approximately what people have always done to succeed.
Mathematicians routinely spend years on a problem without getting anywhere.
It helps though if you have many problems to work on
The key here is that it’s depending on the human inability to connect the sum of relevant knowledge, but said knowledge comes from humans.
Theres going to be this field day of low-hanging fruit that ML can round up, but after that I suspect it will be in fits and starts as a “connection maker” rather than some proof producer.
I think we're underestimating just how much low hanging fruit there is. I've been trying to apply this LLM research process to physics (QM and solid state) and there is so much missing in Physlib and the rest of the Lean ecosystem that most of my work has been trying to formalize the theories and validating them against the specification problem (and mostly failing badly).
It's not only going to be "connection maker". If and when robotics advance to a point where the LLMs are embodied, they can run experiments in the physical world and find new knowledge.
Being embodied is not the important barrier to running experiments. It's having access to a body of resources (i.e. funding and infrastructure).
For some research funding is mostly the salaries of the people doing the research.
What research works that way?
large parts of Computer science, mathematics, theoretical physics, economics, some humanities research and I'm probably missing a ton.
So applied math, math, applied math, applied math, and maybe some others.
That makes sense, although I'd argue that at least in the realm of HEP theoretical physics has extraordinarily expensive kit compared to what scientists make. See: The LHC.
Reducing all these fields to mathematics is incredibly reductive. I don't think it's in good faith.
I think it's telling that "Researchers cost more than any other aspect of research" seems to involve primarily math as inputs and outputs. Like I said the obvious outlier is theoretical physics because that tends to involve significant resources both to explore (supercomputers) and verify (colliders, telescopes, interferometers, etc). Most people involved in research in any number of fields do not find that their collective salaries are the majority of the cost required; math is an outlier in many cases.
yeah but LLMs might be even cheaper than grad students
Robots in labs already exist, but mercifully they're not hooked up to anything as unpredictable as an LLM. Robots tend to work best as specialists doing high-throughput, extremely repetitive tasks which nonetheless require a degree of precision. Giving a robot a "human" body makes very little sense if we're talking about the needs and productivity of a non-human; humanoid robots are marketing for humans.
Humanoid robots are obviously more than marketing. The entirety of human civilization is human shaped. Making robots that are human shaped is easier and more efficient than redesigning and rebuilding everything that exists.
> The entirety of human civilization is human shaped.
That's the marketing pitch.
A plumbing robot doesn't need to be humanoid, an octopus shape may well be better for all the awkward corners. A robot police officer could be the municipality itself for sensory nodes (essentially the sales pitch of Flock etc.), plus some drones or robot dogs to perform arrests*.
The robot vacuum cleaners and lawnmowers we already have are nothing like a human. A robot taxi driver can be just the car. Robot dogs are already used for maintenance and security sweeps.
If you've got wheelchair access, you've got wheeled robot access. If you've got guide dog access, you've got access for Boston Dynamics' Spot.
* this may be a bad idea with current robotics, but I aver it's not improved by making those robotics humanoid.
You are not understanding what humanoid robots are about. Those are specialist robots you are describing. The promise is of course one robot that can do the plumbing, clean your house, do the dishes, build a house, and basically every physical job a human can do. It's extreme lly likely that at least a somewhat humanoid shape is required for that.
My octopus will outperform your humanoid by doing the dishes, fixing the plumbing, and preparing a Caesar salad, all at the same time!
Ah, but my "five guys" will outperform your one octopus!
Yeah. Can't wait to see three or four armed robots. Or five or six!
How do you train a robot to use three hands effectively when we only have two? Then again, why is the robot limited to being one robot? If two humanoid robots are in the same area, they don't have to be distinctly controlled. If they're both controlled by the same AI, a third arm on one body is the same as that arm being attached to another body.
Humans are really bad at everything we do compared to the specialized creatures in nature, it’s just that we can do many things that sets us apart. A humanoid robot is incredibly dumb for that reason. At least add a set of arms and legs and 360 vision. And obviously dislocated joints than can move freely and hands should have two thumbs and more fingers.
It’s not hard to come up with a bunch of improvements for humans, it’s just that making robots in our image is a lot more trivial because you only have to solve for those same averages attributes that we have.
Things you need to take into account that you've almost certainly glossed over:
Safety. Human-robot interactions are generally dangerous and avoided, unless the robot is specifically designed to interact with people. In those cases you often sacrifice speed, strength, and flexibility for safety and softness. Having someone come in with a specialized plumbing robot makes sense, you owning one probably doesn't, and you owning a generalize android capable of plumbing makes less sense still.
Cost. The more compact, complex, and interactive your robot is the more it costs. Make a strong, compact, complex robot safe for interactions with people in the wild is non-trivial and adds costs. The software required to do all of this is hypothetical, but obviously also costly.
Need. I understand the dream of a robot to do whatever you want is very much part of our culture, but when you consider the downsides do you really need it? I don't need a plumber living in my house any more than I need a carpenter or a landscaper to live on premises. At most these are services I would need occasionally or on a schedule. I also doubt my need for them will overlap much, unless we're talking about building a new dwelling.
So why do I need a generalist in my life that's going to cost more than you can imagine, when the means to hire existing human generalists is cheap, quick, and frankly less likely to accidentally punch a hole in you.
> Making robots that are human shaped is easier and more efficient than redesigning and rebuilding everything that exists.
In the last 100-200 years, that has been proven wrong at every single step.
Generalist humanoid robots that are able to operate in unstructured environments weren't an option (they still aren't an option for the majority of operations). The humanity had no ways of building them.
Anyway, it's true that replacing an automated production line with a crowd of generalist robots doesn't make sense. Generalist humanoid robots are intended to replace the remaining human workers.
Historically this has never been correct. Turns out you get more efficient systems when designing them without how a human would accomplish a task in mind.
Counterpoint: cars. It takes sustained effort to prevent civilization from being modified to accommodate new technology, e.g. Stop Kindermoord.
Outside of sci-fi, marketing proposals, and niches like "Elder care in Japan" there are very few humanoid robots. By contrast non-humanoid robots have been mass produced and used in industry for decades. Arms. Carts. Trollies.
No people. If you want something with fine motor control and dexterity, it's easier to make that the robot and then have another robot bring the workpiece to the arm than it is to build a single robot that can walk around and do it. There are compromises in human features because we're generalists.
>elder care is niche
The 2030s have some bad news for us...
https://www.youtube.com/watch?v=n-gYFcVx-8Y
Counterpoint: something has happened in frontier models, and yes they now get discouraged and will sometimes prefer to not continue working on a problem unless you tell them to anyway.
I don't know how or why this would be trained on behavior, but no, it isn't true anymore that models don't say things like, "Ugh," or "this is going to take hours and maybe we should stop here."
I think it's to combat runaway token usage.
> If a mathematician picks a research direction and spends a whole week on it and it doesn't pan out, they will likely be annoyed, need a break for a while, etc.
Your timelines are a bit unambitious. There's nobody expecting to make significant progress with a week of work.
> There's nobody expecting to make significant progress with a week of work.
You underestimate my ADHD.
Source: I am mathematician.
Hell, I underestimate my own ADHD.
Source: the post-it notes, ALL OF THEM.
They were just illustrating their point, I wouldn't take that literally.
We're just going to slowly deconstruct every element that could be a factor of intelligence.
It's not out-thinking, it's just out-remembering
It's not out-thinking, it's just out-working
It's not out-thinking, it's just able to consider more things simultaneously
It's not creative, it's just randomly generating things and then selecting viable ones
A new technology being able to do something better than humans does not mean it’s intelligent though. A calculation program is not intelligent just because it can remember more digits than me, work more than me
That's insightful. AI is teaching us things about our own intelligence by simply evolving under our eyes.
If you make that list comprehensive, there's probably a Nobel prize in it for you.
But the difference really does matter and is not just a case of "whittling down" what intelligence really is.
We have known for a very long time that computers and machines are much faster than humans, more accurate, are scalable in certain ways that humans aren't, and they don't tire. I think most people who are not in the "AI cult" would agree that LLMs and modern generative AI are really just an extension of those faster/more accurate/more scalable and never tiring traits. But there does seem to be (and I'm sure folks much smarter than I have quantified this or described it better than I can) a fundamental difference in how humans think, especially as it applies to what true "understanding" really entails, and for the ability to think up truly novel and unique things that are not just a rejiggering/recombination of training data. I believe those skills really are at the heart of human cognition, and as impressive as LLMs are in replicating what this looks like, there are plenty of "LLM failure modes" where it's clear that LLMs lack a true understanding of concepts or the ability to generate useful, completely novel ideas.
There's definitely a lot missing from the current state of the art in machine learning that all brains manage to beat, and we can observe this just because an animal that needs as many examples as an AI to learn motor functions would starve to death before learning to eat.
However I can only guess that this is important, I'm not absolutely certain. They're at risk of being an economic disruptor just by being extremely stupid (by how much they need to study) faster than us to the same ratio we jog faster than continental drift.
Nobody knows what true "understanding" really entails, or what are "truly novel and unique things that are not just a rejiggering/recombination of training data". For the latter, you'd at least have to find an example in history of someone who came up with some idea that has been widely considered "truly novel" by experts, who didn't have any education or training, so no "rejiggering/recombination".
It's almost as if we're building something that... mimics intelligence.
Can you mimic intelligence?
You just did.
Boooom! Headshot!
>that could be a factor of intelligence
Could is carrying a lot of weight here.
Because, what's really happening is we're saying "Oh these things are what defines intelligence" then implementing them and /discovering/ "oh wait, there's more to this than we knew".
We've known, for decades, for example that an IQ test is not a measure of Intelligence, even though people still refer to it as though it is. A computer passing an IQ test, therefore, would have been thought of as possessing intelligence way back when, but would not now.
Oh, on the point of "creativity" - is a RNG "creative"? It creates a value unbounded by human intervention (in theory, yes Pseudo RNGs have limitations) - therefore it must be creative... right?
In other words: Thousand monkeys with a thousand typewriters...
https://news.ycombinator.com/item?id=48231974
Take something like
If a thousand monkeys typed at a character per second, on a keyboard with the 23 relevant characters, it would take roughly 10^136 years for them to come up with this counterexample. Though, to be fair to monkey scenario, there's a large family of them known now, so it's not quite this bad: suppose there are a trillion permutations and similar examples that fit in this string. Then we are down to 10^124 years.If LLMs are monkeys, somehow trained LLM weights allow them to model and prune massive numbers of universes in parallel.
Just FTR - 1 character per second is glacially slow - it's 12 wpm - fine for (slow) transcription, but the monkey typing exercise doesn't require them to know what they are typing out
How fast do your monkeys type?