I think they mean improve our understanding of physics with new theoretical results or paradigms. Like if it’s 1899, would Astra develop General and Special relativity on its own?
This might just not be possible at the current time. In 1899, there was an "experimental overhang" in physics -- results that could not be explained theoretically (Michelson-Morley, but also lots and lots of empirical material/spectroscopic properties that we could today calculate using quantum mechanics). The big problem in theoretical physics today is that unifying general relativity and quantum theory has no experimental results you could get at our technological level.
I think you make a fair point, but also remember: new paradigms don't necessarily require confusing / contradictory observations. You could have the simple idea of "what if gravity is an inertial force?" at any period in time and work out the mathematics of this. It would make theoretical predictions which could then be falsified, but then again, who would take it seriously enough to test it if it was maybe say 1850 and not 1899.
A better example is maybe Maxwell's laws. Maxwell wasn't inventing a theory to try and explain confusing results, he was unifying a chaotic, empirical laws from existing experiments. That may be a cleaner example. That knowledge compression into satisfying theoretical framework is likely what is attractive.
You can potentially ask the same thing about like you say -- general relativity / quantum gravity but also likely plenty of other areas that may be like this today. Again going outside my particular area of expertise: standard model physics is in a large important sense empirical; lots of values and numbers that are simply unmotivated by theory or where we don't have a good way to make a principled theoretical choice. That could be a place where these models are able to help.
But right now: I doubt it. This is what everyone is working furiously on right now. How do you close a "science" verification loop? In principle this should be easy right: you have ideation (exploration, sampling with ~high temperature maybe as an analogue) and you have verification (which of these ideas are good) which amounts to rejection sampling in idea space. You have to have a sampler that is good at picking _good_ ideas for efficiency sake and you need a relatively fast and reliable verification step of "is this idea good and worth continuing to explore". But I may oversimplify
This is as good a time as any to note that we might be closing in on a new conceptual revolution in our own time as it relates to holography and an information centric approach to spacetime. Obviously It's the furthest possible thing from a guarantee, but it has much of the enthusiasm and motivation that string theory had previously enjoyed in prior decades.
So it could be a natural experiment for whether AI can contribute to novel physics. Specifically, there's a big question about weather. Something like our informational understanding of black holes where information inside it is equivalent to information on its boundary (which I'm sure I'm not saying correctly), might be generalized to regular space-time. More people should be freaking out with excitement about this and perhaps it's something to which AI can contribute.
Honestly I don't think I have single great article, though some Quanta ones are ok, and the Wikipedia article is okay.
The best thing I can recommend is what I did, which is ask Claude about the significance of (1) quantum computing error correction, and (2) error correction in black hole holography and research convergence between the two.
I have no idea what you're hoping the contribution would be. The AdS/CFT correspondence is 29 years old by now and it doesn't seem to apply to our spacetime, where the cosmological constant seems to be positive rather than negative. There are some puzzling consequences of the holographic principle in that scenario as well (https://arxiv.org/pdf/hep-th/0208013), but the linked articles don't talk about them?
Quanta articles are written for people with no background whatsoever, which makes them impenetrable if you have a bit of background and are trying to figure out what they're about. I don't know how good Claude is compared to that -- whenever I try asking any LLM about something I don't understand, it produces a wall of text, I have no idea whether it's correct or relevant, and I look for a textbook or review paper instead.
The wiki article has a section on 'Energy, matter, and information equivalence', the first Quanta article is almost entirely about the 'deep connection between quantum error correction and the nature of space, time and gravity' and about bringing the same information centric approach from AdS to our spacetime. The second Quanta article is explicitly about about bringing a holographic approach to our non AdS spacetime and cites an Ed Witten paper as the cornerstone of that approach (which one perhaps overly excited MIT physicist describes as 'revolutionary').
AdS is 'old' but the articles aren't suggesting it is new, and our spacetime is not AdS and the articles don't suggest otherwise. The point is that there's a search for a way to fit the holographic approach to our spacetime that's inspired by how AdS helps make sense of black holes. Quanta writing being directed at a lay audience ought to be a good thing, not a bad thing and they do link to papers if that's your jam.
Whether or not your LLM of choice produces indecipherable walls of text, and whether it ties those to sufficiently satisfying citations, I think is just a matter of how you go about the prompting.
You're right, I'm prejudiced against Quanta (often IMO they look for a clean narrative to the point of misleading and/or rely too much on metaphors) and was probably too harsh here. Sorry!
That said, I don't like them because their articles never leave me feeling like I understood something. They never go in an order of simple to complex and constantly try to hook you. (A positive example to contrast would be 3blue1brown, who manages to both hook you and make you understand, even with rather little background.)
Could you share a link to your Claude conversation? If this is a prompting issue, I would be interested in seeing what's possible. Thanks!
There was symbolic AI programs in the 1980’s that “discovered” Kepler’s laws and the resulting solar system model from just tycho brache’s astronomical observations. That was the the very first “new physics” ever.
Do you mean after? People do this!! But I think it’s a bit different. It won’t be apples to apples because the data volume I think is just so much different. Maybe there are good experiments for something like this.
For it to be like a human it wouldn't just need to solve existing phsyics problems, it would need to push the field forward and introduce new paradigms.
My comment wasn't very long, yet you somehow still ignored the main part, "and introduce new paradigms". The point is whether it can do everything humans can, entirely new theoretical frameworks and ideas, such as string theory or dark matter, are not coming out of AI at the moment.
AI could discover candidate novel physics without autonomously operating new physical experiments, and humans or instruments can later independently validate the result. This is analogous to how Einstein developed theories whose predictions were confirmed by experiments and observations only years or decades later.
Do we have any examples of an current day AI system introducing a novel concept or perspective. We've got plenty of counterexamples discovered and some theorems proven, but afaik nothing analogous to a new definition.
It could be a good theoretical physicist. Actually it could be a good experimental physicist as well since senior experimental physicists use grad students for the manual labor.
