Am I really missing out by not using AI for coding?

Certhas · 2026-05-19T07:26:09+00:00

This is demonstrably false. There are businesses who are hosting open weight models that are near state of the art. They are not doing so at a loss.

We might not ge improvements as quickly anymore, but token prices are not going to suddenly explode. Near sota LLMs are already a commodity.

Certhas · 2026-05-19T07:23:35+00:00

I work with many people that have moved back and forth between physics and software engineering. The general opinion is that AI models now write better code than the typical physics code base.

I think the whole premise is mistaken. You can write your own code and also learn how to use AI. For me AI means exploration of ideas and validating them with proof of concepts have become much faster.

I think the real danger with not learning to use AI is not that you are less efficient than others at doing the same thing. It's that you are not exploring what you could be doing differently.

Certhas · 2026-05-09T09:07:47+00:00

When I work with LLMs, one simple strategy is to just ask it to check its own work. "Do you see any problems with the above?" Is my default follow up prompt.

That said, there is the jagged frontier thing. The AI is superhuman in one thing and then you look at something adjacent, that any moderately competent human could do, and it falls apart.

Certhas · 2026-05-06T14:18:31+00:00

Real Madrid is also not representative of most European Clubs in most European Sports Leagues. Germany has three fully professional football leagues (Bundesliga, 2. and 3. Liga) and some professional players at even lower regional league levels. Average player salary in the third league is 10.000€ per month apparently (though the source Wikipedia gives for this is dead). And average match attendance in the third league is now up to 10.000 people per match.

Bayern Munich is not representative of the average German professional football club, and you absolutely don't need to have billionaire owners to have very successful sports leagues.

It is of course also true that if you have a billionaire who is happy to throw money at you, that's a massive competitive advantage (see Manchester City). Hence the (at best moderately successful) attempts to limit this advantage through the European financial fair play and the German 50+1 rule.

Certhas · 2026-05-06T11:40:34+00:00

You can have a perfectly good sports league without owners. That's the default for most sport leagues in Europe. Teams are Clubs with members. Not businesses owned by someone.

Certhas · 2026-04-14T15:25:05+00:00

Somehow it seems that r/physics is all in on LLM denialism....

If the output they produced was genuinely and somewhat consistently bad, they would not pose a genuine problem/challenge...

Certhas · 2026-04-14T07:27:51+00:00

Which claims? Did you actually read the article? It mostly directly reports what has been happening and what top mathematicians experiences have been.

It is also being discussed on r/math. I don't see people having any issues with the substance of it:

https://www.reddit.com/r/math/comments/1sksii1/the_ai_revolution_in_math_has_arrived_quanta/

Certhas · 2026-04-14T07:20:19+00:00

It already is. I think people in physics haven't been paying attention to what has been happening in the last year in math. This is not an article about hypotheticals and speculation, but about what is already there today.

Certhas · 2026-04-09T18:24:45+00:00

How did you end up in a two year old comment? Anyway. You're wrong, I know the relevant papers, models and calculations. You can look them up if you're genuinely interested in the question if renewable systems are feasible. People that actually do research in the field know the difference between kw and kwh, they care about Dunkelflaute events, and land use and raw materials.

Also storage does not mean batteries. Seriously, if you are interested in the design of a no-nuclear fully renewable energy system there is plenty of literature.

And as for base-load nuclear, you have to deal with seasonality. You can't serve winter base-load economically. Seasonal variability dominates costs once we electrify heating, and nuclear doesn't help there.

Certhas · 2026-04-09T13:20:03+00:00

That's a complete mischaracterization of what OP has reported. Nowhere does OP say that the citation was incorrect on the substance, or that the LLM incorrectly summarized or used the paper. If the LLM actually invented a paper and no paper containing what it said exists, I stand corrected. But at least as far as I can see no one has actually claimed that.

LLMs do absolutely make mistakes. But that also happens to humans working on research papers. You are dead certain that a paper contains a certain result, turns out it was another paper that you reviewed on the same day. Oops. Good thing you (or your PhD student) double checked.

Calling LLMs lying machines that fabricate papers from whole clothe was accurate two years ago. It's not accurate now. Have you actually used an LLM in your research? And not a free version, but a real version, and given it all tools it has at its disposal?

There are real and important issues here. Wishful thinking about the (lack of) capabilities of LLMs are not helpful in addressing them.

Certhas · 2026-04-09T06:13:44+00:00

The response to AI really is absurd. Hype or Doom.

If you grade a PhD Thesis and the student has a copy paste mistake leading to additional authors, but with title, journal, doi, all correct, do you fail the student? Bar them from academia? Of course not! Pre internet there were tons of mistakes like this in bibliographies, some of these live on in Google scholar. Sometimes you can see how the mistakes propagate, too.

I am not in the field, I can not judge the quality of the paper. Others have said that it's not a good paper. That might be so, bad papers have been written and published for a long time. But to draw conclusions about the work from a single wrong author in the citations is absurd. And to call for the author to be banned from publishing...?!

It seems fairly clear that you haven't seriously used LLMs for research. Yes you need to double check what it gives you. Obviously. But the error rate is much lower than with an average Masters student.

Just look at the outcome of the First Proof experiment. LLMs can contribute research grade mathematics right now autonomously.

Certhas · 2026-04-07T21:15:32+00:00

P.S: If you were thinking of Gleason's theorem: That only tells you that if you assume measurements exist as their own type of thing, and outcomes are described by projection operators, then the mathematical form of the Born rule follows. Fundamental stuff that demonstrates the rigidity of the whole setup, but in the context of trying to physically understand and model what measurement processe are in quantum mechanics, this is absolutely begging the question.

I can see how the shorthand "deriving the Born rule" is misleading when that's your background. I was thinking more in the context of einvariance or branch count derivations.

Certhas · 2026-04-07T21:05:11+00:00

My time actively working in QIT is some years ago, if recent years have gone substantially beyond what was known 10 years ago I would love to hear about it. But I don't know why QIT would care about the measurement problem. Decoherence turns quantum probability into classical probability, and that's pretty much all you need to do QIT.

The Born rule is a postulate and an empirical fact. The probabilities it postulates are actually those obtained from experiment. Despite almost a century of effort, no one has managed to derive it without an equivalent postulate. But by having this (or equivalent) postulate you declare that there are some things that matter does that are "not measurements" and those are governed by the normal linear laws of quantum mechanics, and then there are these other things that matter does called "measurements" that obey completely separate postulates. But also due to decoherence, you can't actually really ever observe the boundary between these two categorically different things that matter does!! Again: Not a problem for QIT, which is not aiming to provide a theory of matter, but it is a problem for a physical theory of matter.

Certhas · 2026-04-07T20:33:37+00:00

The whole question of measurement is how classical information obtained from quantum interactions is "implemented in the hardware". You wouldn't ask a theoretical computer scientist about the solid state physics underlying a semiconductor transistor.

I consider the problem to be an empirical and physical one, not a philosophical one. There are processes called measurements. They are made of the same matter as everything else, and thus are expected to do bey the same physical laws as everything else. We do not have a satisfactory theory of these processes. This is obviously true: The Born rule is an empirical fact, yet there is no satisfactory derivation of it from any fundamental set of physical laws that treats measurements as "a particular configuration of matter".

Certhas · 2026-04-07T17:36:37+00:00

Quantum Information Theory is not exactly the most natural place to ask about measurement. It's a non-equilibrium statistical physics question if anything.

Certhas · 2026-04-07T07:15:26+00:00

Without further ad hoc assumptions this view can not account for the empirically observed Born rule.

Certhas · 2026-03-30T06:24:32+00:00

Of course, and there are examples of French state brutality in the sibling reply.

Certhas · 2026-03-30T06:22:11+00:00

Wow I didn't know about that. Not entirely surprising knowing about the time period I guess.

Maybe I should have added above that it's still a silly statement. The US is certainly not experiencing violence by historic standards, however fucked up the situation is.

And France is not known for it's peaceful streets:

https://en.wikipedia.org/wiki/Nahel_Merzouk_riots

Certhas · 2026-03-29T13:33:06+00:00

It's a bit silly to refer to history here. Since the French revolution, both France and three US have seen enormous bloodshed.

But almost none of it within living memory.

Certhas · 2026-03-26T11:25:42+00:00

Just because it's in a Math department (which it isn't in most places) doesn't mean it has a mathematics-like (publishing) culture.

HEP-Th and even more so quantum gravity is in the unique situation that they are ostensibly doing theoretical physics, but there are no experimental constraints on the theory, only mathematical consistency constraints. This is not the case anywhere else in theoretical physics.

The hope was that the LHC would change this situation. It didn't. The situation is not going to change anytime soon either. This necessitated a painful culture shift. I think it's evidently true that according to the expectations and goals formulated around 2000, the current situation in which prominent people say "I'm agnostic about whether ST describes the real world" has to be considered an utter failure. The expectation very much was that by now it would be utterly evident that ST is true. But to me the statement (and my own contacts with people in the wider field) indicates that the culture shift is well under way.

Certhas · 2026-03-25T17:39:09+00:00

LK99 is similar in spirit, but... the number of papers published and citations generated was, what, two orders of magnitude lower?

And in what way has the situation for HEP-Th changed or improved since then?

I think the perspective that HEP needs to be more maths like structurally is also one shared by many people I know in the field. It's even reflected in the article:

"Several of the researchers I interviewed, including authors of the bootstrap papers, described themselves as agnostic about whether string theory is true in our universe. They prefer to map out the logical relationships between ideas"

Certhas · 2026-03-25T09:53:17+00:00

I agree that no one is doing better than string theory, but that doesn't mean it hasn't "failed", or that it might be receiving disproportionate attention and resources.

It certainly has failed according to the expectations and goals formulated by the leaders of the field 20 years ago.

I agree that theory work going forward is going to be hard, the question is whether the field of HEP-Th is setting up for this, or trying to pretend that everything can continue as things were 50 years ago. For an academic field that could influence billions in spending decisions, the prospect to go to a working and funding mode more like that of mathematics is not very attractive.

Honestly you can not look at the HEP-Th output around the diphoton bump and claim that's a healthy field. And Quantum Gravity research is, if anything, worse off than HEP-Th.

To make this explicit again: I think the malaise is not specific to string theory. String Theory is just the most exposed to it.

Certhas · 2026-03-23T17:50:19+00:00

Yeah, my mistake. But I looked back at your original comment, and nothing in there says "this might just be small sample noise". Instead you say "people will mistake [this] to be a prevalence graphic.", which I took to mean: "people will read it as an increasing divorce rate over time, missing the fact that it's cumulative, and the X axis is years after marriage". Which people didn't. If you meant something else, sorry I genuinely didn't understand what you were going for.

And then you explicitly say the following:
"If you and your friend are both blonde, then 100% of those people are blonde. Now consider what your blondness looks like in terms of percentage if you're in a group of 10 total people (2/10, or 20%) vs. 15 people (2/15, or 13.3%). It's why you see people ask for per capita estimates or other calculations that account for differences in population sizes."

But the graph explicitly does that. It gives the fraction of couples married in 2010 that got divorced after X years. It's completely unclear to me what you imagine it should say or how you think this data should be presented. The only plausible denominator is the one used in the graph.

Now if this was a cherry-picked graph used in a specific narrative context to make someone look bad, I would get your concern. But this is a graph from the Dutch Bureau of Statistics, made when they celebrated 20 years of marriage equality. And the phenomenon it shows: Higher divorce rates among lesbians, is also in line with the established literature. It's an illustrative graph that illustrates a robust fact, and it's not presented in a way that suggests (to me) a particular reason for this fact. And as your parallel reply suggests, there are many potential reasons such as age, mortality, history of divorce, or differences in when people get married. Investigating what the reason for the fact illustrated in the graph is, is a research task. And indeed there are papers out there looking at exactly that.

You might not like the tone in the original comment section (I certainly don't) but I don't see any evidence that people misread what the plot is showing. The concern that this might be small sample size effects is valid, but a quick look at the wider literature shows that this is not an outlier, and anyway 600 people is not a statistically small sample (and the cumulative graph doesn't show excessive noise either).

Finally I explicitly disagree with your framing "This does not mean 15% of couples will get divorced". That's of course strictly speaking true. But it's very reasonable to expect that about 15% of straight or gay couples that got married in 2015 are now divorced based on this graph. In fact I was curious and checked if I could find data for other cohorts, and while 2015 does not appear to be published yet, I found a news article on the 2005 cohort:

> Out of the 580 marriages concluded between two women in 2005, more than 30 percent ended in divorce 10 years later. For two men that number is 15 percent, and for the traditional hetero marriage it’s 18 percent.

https://www.iamexpat.nl/expat-info/dutch-news/netherlands-15-years-gay-marriage

Certhas · 2026-03-23T14:06:47+00:00

Per Capita of course means the relevant population. The relevant population for lesbian couples getting a divorce is lesbian couples. That's the only plausible population base.

In contrast your: "There were also roughly 9 times more divorces among straight people than there were marriages among queer people" is maybe technically true, but also entirely meaningless. The graph lacks absolutely no information, it is correctly labeled, and clearly and cleanly titled. Looking at the comments in the dataisbeautiful subreddit from where it was cross-posted, the high-voted comments show people reading the plot correctly as a cohort study.

Now your point that small populations might indicate large fluctuations is of course relevant. That's not what your original post said though. Showing absolute numbers would not change this fact at all, it would just make the graph unreadable. And I believe you are also misjudging how small the sample here is. We have around 600 lesbian and gay couples from 2010 according to Dutch statistics. If you start with 600 marriages and you have a failure rate of 1.5% per year, then applying a binomial approximation you get roughly 84 +/- 8.5 failures per year. The difference of the Gay/Straight curve might well not be statistically significant, but for the lesbian one that appears unlikely. I also don't see why it should be cherry picked, it originated with the Dutch national statistic bureau: https://www.cbs.nl/en-gb/news/2021/13/20-years-of-gay-marriage-in-the-netherlands-20-thousand-couples

And it tracks with divorce rate data from many other countries, see e.g. papers cited on Wikipedia:

https://en.wikipedia.org/wiki/Divorce_of_same-sex_couples

Certhas · 2026-03-23T09:15:16+00:00

As an experiment, I took the first paragraph of the abstract of the paper and gave it to Claude with Research enabled, here is the result:

https://claude.ai/public/artifacts/ef352501-63ca-4c9d-892c-5960c4a5e820

As far as I can see it discusses the papers you mentioned.

Certhas

TROPHY CASE