What was the cliche? All theories are wrong, some theories are useful. It needs to be rephrased from vector codes into massively parallel codes but people can work with that.
Quantum theory isn't. It's not a single, cohesive, consistent theory.[1] There is no recipe you can apply, it's just a bunch of guessworks and heuristics that happen to produce the numerically correct equations if you keep trying long enough. This isn't secret or some sort of external criticism, you'll find this front-and-centre in the foreword of many a QM text!
Schrödinger famously arrived at his equation basically through numerical methods. He just tried things until it "fit" the desired output.
Now, there's nothing wrong with this, per-se. It's a perfectly viable approach for getting going, for getting something and using it as a starting point. But it isn't the endpoint, because approaches like this often have virtually no explanatory power.
A similar example is collecting insects, categorising them, giving them Latin names, and putting them up for display in a museum. You can learn a lot, amass enormous amounts of information, but without a theory of genetics and natural selection you will always be blind to the underlying truth of it all.
QM is just like bug collecting. We're collecting numerical equations that work, but we have essentially no clear understanding why. We've built a tree of life, and nobody has had the lightbulb moment that explains why it's a tree.
[1] There was a paper published a few years back where a bunch of working quantum physicists were asked some simple multiple-choice questions about the fundamentals of the theory. There was no consensus opinion on anything! PS: You'll get similar results if you ask priests of a random Christian sects about the basics of religion. Conversely, you will get nearly zero disagreement if asking Chemists about the basics of their science.
Also, physicists disagreeing on interpretational issues related to quantum foundations is not the same thing as disagreeing about the fundamentals of the theory.
Also chemists have the luxury of agreeing because the fundamentals of their work (not the day to day act of doing chemistry) gets to assume the presence of physics i.e. it's stampkeeping (depending on who you ask).
Note that protein structure prediction finally fell to machine learning and it was "mostly stamp collecting" (IE, the accurate predictions come from subtle analysis of rich protein sequence alignments, not from understanding the fundamental principles of protein folding).
The simplified protein folding problem states that proteins fold to their energy minimum, and a succesful heuristic can find the "correct" fold by finding the structure argmin(energy). Although this is a real simplification that doesn't represent actual proteins, even that is not something you'd solve with matrices; combinatorial math.
More importantly, "protein folding" is the biophysical process that proteins experience; what DeepMind did was solve "structure prediction", which is another simpler problem, and they didn't do it by energy minimization, they did it by exploiting sequence similarity to provide structural constraints that massively reduced the search space.
might be true, but it's computationally intractable and even if you did find a way around it you'd just learn that your force field was inaccurate, or that proteins don't actually fold to their energy minimum.
Not just hard, but NP-hard. In fact, the "protein folding problem is NP hard" is misleading; in fact, the "static protein structure problem" is NP hard, and protein folding is "harder" than that (it's a superproblem of static structure prediction).
The way to describe angles for a protein is this: you use degrees or radians to describe the torsion angles of the backbone (2 torsions per amino acid, 360 possible positions per torsion, times the number of backbone atoms in the protein). Treat side chains with rotamers, that's already a solved problem. However, you can't compute self-collisions in angle space you need to embed the protein structure in cartesian coordinates, which is how they are normally represented (as a graph representing the bond topology, and an N*3 array of positions).
> it's as solved as it can really be as far as human understanding is concerned
You handwave away several interesting parts of the problem without providing real justification for why that would be necessary or acceptable.
It's like saying "politicians are made up of atoms, and since we know how atoms interact, our understanding of politics is reasonably complete".
What DeepMind solved was a far simpler problem: reproduce the structures that get produced by some experimental method. That's a well posed problem but ultimately a less interesting one, even if it's immediately "useful".
the famous feynman have produced a response to this train of thought - usually from the laymen - where they demand an "explanatory theory". The answer is usually "don't know"; why gravity work the way it does? - don't know, but we can calculate orbits to great precision; why does photons or electrons travel the way it does? - don't know, but we can make very precise predictions via Quantum Electrodynamics theory.
The laymen demands an explanatory theory, because there's an underlying assumption they don't even verbalize - that such an explanatory theory can be understood _without the maths_, that the principles of the laws of physics operate on basic, understandable lego pieces. What is somewhat unconceivable is that the explanation _is_ the maths. To whit, we don't even have an explanation for the idea of inertia! We just observe it, and measure it (as mass). There's no explanatory theory.
"Honey did you take the garbage out?"
"When you say garbage, have you considered if garbage can even really exist?"Still, it's fun to play with this idea via figures who are a little more philosophically rarified as it were:
https://www.tiktok.com/@davecolumbo/video/706085573209017886...
Do school names determine how good a school will be? Of course not. However, schools have names which tend to be reused: cultural icons, scientists, etc.. And schools in low performing areas are going to have a different distribution of chosen names than schools in high performing areas. So you can create a model that will not only demonstrate this but also offer legitimate observational predictability that a school's name will, on average, determine how well it will do.
The only way you could really refute this hypothesis is by understanding the true confounding variable, or by running some huge scale multiple decades long experiment where you changed the names of new schools and measured the performance difference. That experiment is clearly not really practicable, so all you're left with is understanding.
And this is really where the risk is. If we ever begin to build upon something that is unsound then it risks everything from that point onward being also invalid. At best everything collapses and you realize you must have made a mistake. At worse, you simply end up adding endless epicycles until at some point everything starts to completely stall out muddled in its own invalid fundamentals and irreconcilable complexity.
"The laymen demands an explanatory theory" -- and so do scientists! Why do you assume scientists are somehow "above" explanations, and are content in ignorance?
"explanation _is_ the maths." -- People had good rules of thumb for evolution (such as dog breeding practices), and Gregor Mendel could have come up with his mathematical rules for selection before Darwin published his explanatory theory of natural selection. That doesn't mean that it's worthless to try to aim for an explanatory theory of QM instead of a purely numerical / observational one.
That's literally what goes on at CERN. They run effectively trillions of experiments, collect millions of them (after some filter), and then they draw histograms.
Unless you know nothing about mathematics, you know that histograms are inherently statistical beasts. It's meaningless to talk about the histograms of one experiment.
Could you learn to play, say, tennis by drawing histograms of player movements? Ball bounce locations? No? Why not!? It's tons and tons of data! Accurate, scientific data!
Quantum physicists would argue that only statistics exists. I like to point to the fact that one hydrogen atom can exist, and it can have on electron. Or zero electrons. In nice countable, integral quantities. You can place a single gold atom on a crystal lattice with an AFM or even draw cute pictures with them: https://cen.acs.org/analytical-chemistry/imaging/30-years-mo...
Just because some people think only collecting bugs is what biology is all about, doesn't mean that there isn't more to it...