ChatGPT spitballing fundamental physics theories
ramrajv.com
ramrajv.com
I didn't know whether ChatGPT's ability to babble convincingly was going to cause trouble or be a funny quirk that we all knew about and worked around, but this thread is really making it look like the pessimists were right about it. The problem is that it gets past many people's filters because its phrasing sends a lot of intelligent/rational/professional signals, as it was engineered to do. Nobody is used to picking smart-sounding text apart word by word to make sure they agree with it, except maybe academics, and that's the vulnerability it reaches us through.
I also think that OpenAI got human nature backwards when they trained it to hedge on everything it said - everybody knows that people who constantly demure are the most reliable! A safe chatbot would sound pushy, like a bad salesman or an ideological agent; like something incapable of self-questioning.
Like that time a science fiction writer started his own religion based on characters from his novel and got a bunch of celebrities financially tied to it
Or when holistic practitioners procedurally generate an unsubstantiated preventative cure
Might as well just turn your brain off now, you won’t need it
Raised by Wolves moment
In American English, this is frequently authority speech mimicking law enforcement, scientists, or lawyers. All while lacking any knowledge of anything but the outer dressings of something.
In this way, the problem is that the AI is just mimicking most of us on most things.
Since the same could be said about your comment, perhaps you could amend your critique?
“Dynamic Geometric Interactions in Multi-Layered Spacetime"
This hypothesis proposes that spacetime consists of multiple interconnected layers, each with its unique geometry and properties. The fundamental forces and particles emerge from the interactions between these layers and the geometric transformations that take place within and between them.
Multi-Layered Spacetime: The universe is not a single, continuous spacetime fabric but instead is composed of multiple interconnected layers. Each layer has its own geometric structure, which can be influenced by the other layers.
Interactions and Transformations: Particles and forces emerge from the interactions between the layers and the geometric transformations that occur within and between them. These transformations might involve changes in curvature, connectivity, or other geometric properties, leading to the observed behavior of particles and forces at different scales.
Unification: At high energy scales or specific conditions, the interactions and transformations between the layers might become more unified, leading to a single overarching interaction responsible for all fundamental forces.
[And a rough mathematical explanation] Let's denote the granular spacetime structures as Sij, where i and j represent the indices for the type of spacetime structure and its configuration, respectively. Suppose there are N types of spacetime structures, each corresponding to a specific force or force pattern. The interaction between particles might be described by an interaction matrix I, where each element Iij quantifies the strength of the interaction between spacetime structures Si and Sj. In a high-energy regime, the spacetime structures' patterns might begin to merge, leading to the unification of forces. We can represent this by introducing an energy-dependent matrix U(E), which modifies the interaction matrix I as a function of energy E:
I'(E) = U(E) * I
As the energy E approaches a critical energy level Ec, the matrix U(E) transforms I into a single unified interaction matrix, corresponding to the unified force.
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This comports with my understanding of the Inflaton field, which parametrically resonates (through geometric relationships?) with other fundamental fields during the Big Bang. I’ll pull some references here.
Maybe it did a better job in biology because I was able to correct it at an expert level (which I was not able to here). Given the demonstrably (like right here in these comments) myopic unimaginative nature of physics as a science today, it’s possible not a single physicist would try to entertain this system as a hypothesis generation machine. I mean we have discovered everything already right?
You would have to be an insanely skeptical person, one who would drive anybody nuts to talk to, to approach a ChatGPT session in a field you're not an expert in or maybe even one you are, and evaluate it right... The only normal human perspective that fits what ChatGPT is actually like is the one we take on people we think are terrible, so that is why I say it's awful, although it's just a machine.
Is anyone claiming there's a market niche for hypothesis generation in the natural sciences?
Full disclosure: I have a science PhD and a couple of published papers as a result. It was a long, slow, frustrating grind, but generating hypotheses wasn't even close to being the hard bit.
Is a good hypothesis important? Sure. Is it easy to get that bit wrong? Yes, and lots of people do.
I'm reminded of one of Paul Graham's quotes:
"I also have a theory about why people think this. They overvalue ideas. They think creating a startup is just a matter of implementing some fabulous initial idea. And since a successful startup is worth millions of dollars, a good idea is therefore a million dollar idea [..] startup ideas are not million dollar ideas, and here's an experiment you can try to prove it: just try to sell one. Nothing evolves faster than markets. The fact that there's no market for startup ideas suggests there's no demand. Which means, in the narrow sense of the word, that startup ideas are worthless."[0]
And this doesn’t even touch the question of what’s different between basic science and entrepreneurship.
I think you're making a mountain out of a molehill. To me ChatGPT is basically a clever way to interpolate and extrapolate coherent text based on user input and its training set. If the training set is lacking in some areas, it underfits the output.
I've tested ChatGPT in a couple of engineering fields I'm familiar and I expected the service to respond poorly, but even though it returned nonsense in some areas I thought were low-hanging topics, such as the release year of an international standard, overall its output was very impressive and very entertaining.
Perhaps it's the engineer in me talking, but it's pointless to waste time waxing lirically about human nature. Tools like ChatGPT might one day be superb expert systems and teaching tools, but like any expert system and learning tool you need to corroborate the results by yourself. Human nature has zero to do with this.
I see your point, and I agree. Nevertheless, these misdirections seem to boil down to a broad temptation to succumb to appeals to authority. People might be falling for ChatGPT misfires just like they fall for fancy talking bullshit artists, but that's hardly a failing of clever auto text generators.
That is, the ideas, strengths and limitations of the current well-known theories are very well explained and mostly correct. However, the "novel theory" is mostly filler words around some very thin concepts to make it sound like an actual theory with some depth to it, but in reality saying nothing more than that spacetime is granular and there could maybe be some matrices.
A few days ago I did a similar exercise playing with alternative definitions of gravity.
It was even able to provide (GlowScript 3.1!) code to run a simulation using the concepts we developed (and it worked).
It’s amazing the feeling of going back and forth, iterating quickly on the ideas and then being able to generate code to test them.
Will have to try the gravity one now.
Thanks for the recommendation!
(ChatGPT+ allows you to specify which model you want to use.)
We already went through this with Stable Diffusion - the content it produces looks very professional, but also somehow exactly the same no matter the subject.
ChatGPT also offers a possibility to e.g. have a real bargaining at the shops: "How much is that sword... ".
Thank you for this comment, it really made me happy.
The modern mechanics revolutions of the 20th century demonstrated that our intuitions were completely mismatched for what the truth was. Planck himself rejected the notion of curve fitting which ultimately birthed energy quanta. It’s OUR macro universe that is the weird one, a strange corner case of quantum reality in the absurdly large.
I’m a biologist by training and have already made significant progress on multiple difficult questions I’ve had trouble with for decades in the 2 days I’ve had gpt4. Can’t wait to see what all we could accomplish with it!
I tried using chatgpt 3 for light research onto British occupation of Afghanistan and poppy production, I wanted to know potential books/authors which covered how long back Afghanistan might have been an exporter of poppy/opium and it ended giving me some really bad quality answers including stating that one author had actually written a book called "Opium and the kung-fu master", which is not a book at all! But an older Chinese action movie decrying the evils of opium addiction...
This thing is not good for developing any useful theories other than a creative crutch.
Proposing new theories I'd be extremely skeptical of. It's just not what this thing is made to do.
Importantly it clearly has some understanding of these theories. At least as much as any regular person would, in my opinion.
Non the less interesting though. I am currently researching into physics-informed neural networks for quantum problems, which are guided with differential equations. Maybe if you’d extend an LLM with an execution engine/numerical model, it’d be able to actually produce differential equations to undermine its hallucinated theories. From my short testing that is something ChatGPT (4) is not that good at. Or it’s just a generally a hard problem to produce novel differential equations
while I don’t want to sound crazy…
I managed to get GPT to mathematically derive a formula and calculate actual results to explain some well known anomalies in physics.
I’m aware that gpt might be imagining and contriving false conclusions …
but I have no doubt that ai will be moving physics forward within the decade
Generative AI needs a way to receive feedback. AI learned to play chess by playing a lot, and the feedback was either winning, losing, or drawing.
If generative AI can repeatedly test physics theories faster than humans, then we may witness progress in physics. AI could generate thousands of theories and conduct experiments successfully, possibly leading to new physics models.
However, I am uncertain whether this will be achievable soon, particularly for theories requiring costly experiments.
A benefit could be that humans crave recognition for success, making papers less valuable. AI may be more willing to take risks and document its failures than humans.
I've long felt that this may be the strongest argument against an AI singularity.
The technical ability to emulate the minds of the world's theoretical physicists and run accelerated simulations of their thought processes may be developed, but the generation of valid new insights in physics might depend strongly on observations and experiments conducted in the physical world, as seems to have been the case historically, and the virtual equivalents of those experiments may prove to be inadequate or impractical to implement.
Steven Pinker made a similar argument in this 2018 discussion with Sam Harris (the remarks begin at 65m03s in this recording [1]; the full conext begins at around 50m36s [2]). Harris is concerned about existential risks posed by advances in artificial intelligence, whereas Pinker is less so, in part for this reason. I agree with Harris that there are risks associated with artificial general intelligence, but I agree with Pinker and the parent comment about the dependence of the scientific process on experiment, and that an inability to conduct accelerated experiments in the physical world may undermine the standard argument about the inevitability of an AI singularity.
An AI capable of interfacing with the physical world might develop the ability to conduct accelerated physical experiments, but it would presumably face the same fundamental and contingent limits as human researchers, and the history of human science suggests those limits may impede exponential progress.
Doesn't the author do something similar in the article? Why are you worried people will think you are crazy?
It is surprisingly amazing - accurately (verified with a native speaker) conversing in Lithuanian with phrase level translations, explaining pronunciation, explaining clauses and cases, and is able to explain some grammatical concepts (usage of commas, etc) that I haven't found explained in English elsewhere.
My honest opinion is that very few people are clear on what the thing is actual good at, great at or bad at at this stage. We're still trying to find it's real use case.
IMO it's best for things you already know quite a bit about so at least you don't mess up hard. In other words, it seems like a more advanced ELIZA. Nearly everyone who has had a good time with it has used talk to it until they had a break through.
A great gig for GPT -- Hollywood bullshitter!
This is the first example of an extended dialogue with GPT-4 that I have read, and the fact that it failed to obey the request to dispense with its repetitive disclaimers was perhaps the most interesting thing to me about it. It seems somehow more fluent to me than GPT-3, as though its verbal IQ has increased a few points, but GPT-3 was already quite articulate; I havent yet seen any examples of clear new abilities from GPT-4.
The substance of the dialogue struck me as generic and lacking novel insight, though the bar was of course set rather high (essentially 'Describe revolutionary new physics'). I've also been jaded by the past few years of advances in AI; if I had seen this transcript ten years ago I would have been surprised and impressed that an AI could have a conversation about theoretical physics, and could demonstrate an ability to discuss relevant concepts in a reasonable and confident manner.
The ability of large language models to exhibit sophisticated verbal reasoning, albeit not yet reliably so, is their most striking feature to me, and I do think that has great scientific potential; perhaps GPT-4 isn't yet a major advance in that respect, but I imagine an important foundation has been laid. I should say I'm grateful to you for publishing this Ramraj; the transcript and the impressions you and others have shared in this thread have been illuminating.
Anyone who is curious about the application of AI to theoretical physics may be interested in the work of the MIT physicist Max Tegmark and his group, which is still at an early stage. Here are some videos in which he discusses AI and physics, in increasing order of detail:
https://www.youtube.com/watch?v=dinfiuGqoQw (6 minute clip from a conversation with Lex Fridman)
https://www.youtube.com/watch?v=9atnfAHBfSI (20 minute presentation)
https://www.youtube.com/watch?v=pkJkHB_c3nA (49 minute presentation)