https://en.wikipedia.org/wiki/J._Robert_Oppenheimer#:~:text=...
sitzfleisch: the ability to endure or carry on with an activity
Something Oppenheimer did not have, apparently.
Grit can be the courage to endure adversity.
It can also be the resolve to endure tedium.
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.
People go whole lives without being able to make it pan out.
The degree of confidence matters here.
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.
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.
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.
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.
And for the inevitable critics of Sabine...maybe Leonard Susskind is good enough for you: https://youtu.be/2p_Hlm6aCok
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)
> 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.
ReactJS devs will retrain when the market dies. Professors still publishing theories/experiments costing large amounts of public monies better spent elsewhere.
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.
> 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.
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.
(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)
String theory has nothing even theorized that would allow us to prove it.
Out-ralphing them, you might say!
AGI ≈ artificial stupidity × infinite persistence
That is also approximately what people have always done to succeed.
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.
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.
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.
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.
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.
Vision is hard regardless of the angle, but scaling it from a normal camera to 360° doesn't add much cost or difficulty once you've done the hard part of turning pixels into a suitable latent space.
> Look at octopi with their insane nervous system required to support their tentacle.
500 million neurons across the whole animal, brain included. We'll only know the synapse count when someone does a full connectome scan of one, but based on the vague estimates I see with a quick search, their whole mind is less complex than a SotA LLM today.
> The one who wins is the one who builds a robot that can do the most, while being the cheapest.
This is a reason for specialists, not generalists.
A literal Swiss army knife is a perfectly reasonable thing to own, but you don't want to hire a builder who only has that and nothing else, not even if it's the silly model: https://www.vintageknives.nl/p/wenger-giant-swiss-army-knife...
The best container ship is a terrible pleasure yacht, and vice versa. You use container ships pretty much constantly, even though you (almost certainly) don't own one, by the power of indirection. You can rent a pleasure yacht as desired without owning own.
In both cases, the cheap option is to use the right tool for the right job, rather than to take a holiday on the Hanoi Express and get your next international shipment delivered by this: https://www.boattrader.com/boat/1996-hatteras-82-convertible...
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.
In the last 100-200 years, that has been proven wrong at every single step.
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.
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.
The 2030s have some bad news for us...
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."
Your timelines are a bit unambitious. There's nobody expecting to make significant progress with a week of work.
You underestimate my ADHD.
Source: I am mathematician.
Source: the post-it notes, ALL OF THEM.
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
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.
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.
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?
(1+x*y)^3*z+y^2*(1+x*y)*(4+3*x*y);y+3*x*(1+x*y)^2*z+3*x*y^2*(4+3*x*y);2*x-3*x^2*y-x^3*z|0,0,-1/4|1,-3/2,13/2
If LLMs are monkeys, somehow trained LLM weights allow them to model and prune massive numbers of universes in parallel.