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AI comes up with bizarre physics experiments, but they work
- anonym00se1 1y agoFeels like we're going to see a lot of headlines like this in the future. "AI comes up with bizarre ___________________, but it works!"
- ninetyninenine 1y agoThat’s how we become numb to the progress. Like think of this in the context of a decade ago. The news would’ve been amazing. Imagine these headlines mutating slowly into “all software engineering performed by AI at certain company” and we will just dismiss it as generic because being employed and programming with keyboards is old fashioned. Give it twenty years and I bet this is the future.
- hammyhavoc 1y agoTwenty bucks says it isn't.
- somenameforme 1y agoA decade ago it wouldn't have been called AI, and it probably shouldn't be called AI today because it's absurdly misleading. It's a python program that "uses gradient descent combined with topological optimization to find minimal graphs corresponding to some target quantum experiment". Of course today call something "AI" and suddenly interest, and presumably grant opportunities, increase by a few orders of magnitude.
- ninetyninenine 1y agoGradient descent is a learning algorithm. This is AI.
- somenameforme 1y agoHahah, if you're going to go that route you may as well call all of math "AI", which is probably where we're headed anyhow! Gradient descent is used in training LLM systems, but it's no more "AI" itself than e.g. a quadratic regression is.
- ordu 1y agoNeural networks are on the hype now, but it doesn't mean that there was no AI before them. It was, it struggled to solve some problems, and to some of them it found solutions. Today people tend to reject everything that is not neural net as not "AI". If it is not neural net, then it is not AI, but general CS. However AI research generated a ton of algorithms for searching, and while gradient descent (I think) was not invented as a part of AI research, AI research adapted the idea to discrete spaces in multiple ways. OTOH, AI is very much a search in multidimensional spaces, it is so into it, that it would probably make sense to say that gradient descent is an AI tool. Not because it is used to train neural networks, but because the specialty of AI is a search in multidimensional spaces. People probably wouldn't agree, like they don't agree that Fundamental Theorem of Algebra is not of algebra (and not fundamental btw). But the disagreement is not about the deep meaning of the theorem or gradient descent, but about tradition and "we always did it this way".
- omnicognate 1y agoGradient descent is used in machine learning, which is a field in AI, to train models (eg. neural networks) on data. You get some data and use gradient descent to pick the parameters (eg. neural network weights) to minimise the error on that training data. You can then use your trained model by putting other data into it and getting its outputs. The researchers in this article didn't do that. They used gradient descent to choose from a set of experiments. The choice of experiment was the end result and the direct output of the optimisation. Nothing was "learned" or "trained". Gradient descent and other optimisation tools are used in machine learning, but long predate machine learning and are used in many other fields. Taking "AI" to include "anything that uses gradient descent" would just render an already heavily abused term almost entirely meaningless.
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- JimDabell 1y agoThat’s been called AI for about thirty years as far as I am aware. I’m pretty sure I first ran into it studying AI at uni in the 90s, reading Norvig’s Artificial Intelligence: A Modern Approach. This is just the AI Effect at work. https://en.wikipedia.org/wiki/AI_effect https://en.wikipedia.org/wiki/AI_effect
- dns_snek 1y agoYou're taking intelligently designed specialized optimization algorithms like the one in this article and trying to use their credibility and success to further inflate the hype of general-purpose LLMs that had nothing to do with this discovery.
- ninetyninenine 1y ago[flagged]
- Izkata 1y ago> Like think of this in the context of a decade ago. The news would’ve been amazing. People have been posing examples of similar "weird non-human design" results throughout here that are more than a decade old.
- viraptor 1y agoWe've seen this for a while, just not as often: antennas, IC, FPGA design, small mechanical things, ...
- deleted 1y ago[deleted]
- sandspar 1y ago"AI comes up with a bizarre short-form generative video genre that addicts user in seconds - but it works!" I'm guessing we're only a year or two away.
- eleveriven 1y agoEntering the "hold my beer" era of AI creativity
- amelius 1y ago... sometimes.
- IAmGraydon 1y agoThis is the kind of thing I like to see AI being used for. That said, as is noted in the article, this has not yet led to new physics or any indication of new physics.
- deleted 1y ago[deleted]
- markasoftware 1y agonot an LLM, in case you're wondering. From the PyTheus paper: > Starting from a dense or fully connected graph, PyTheus uses gradient descent combined with topological optimization to find minimal graphs corresponding to some target quantum experiment
- aeternum 1y agoMore hype than substance unfortunately. The AI rediscovered an interferometer technique the Russian's found decades ago, optimized a graph in an unusual way and came up with a formula to better fit a dark matter plot.
- rlt 1y agoThe discovering itself doesn’t seem like the interesting part. If the discovery wasn’t in the training data then it’s a sign AI can produce novel scientific research / experiments.
- hammyhavoc 1y agoThis is monkeys and typewriters. It's like seeing things in clouds or tea leaves.
- Supermancho 1y agoIf the "monkeys with typewriters" produces a Shakespear sonnet faster than he is reincarnated, it's a useful resource. At least, that's the thinking.
- shermantanktop 1y agoThat’s the looooong game on both counts.
- tux1968 1y ago'tis the patient plot on either side, where time doth weave its cunning, deep and wide.
- shermantanktop 1y agoyou lit-nerd sniped me with this one! but i call shenanigans on your AI-generated poetry.
- viraptor 1y agoThis sounds similar to evolved antennas https://en.wikipedia.org/wiki/Evolved_antenna https://en.wikipedia.org/wiki/Evolved_antenna There are a few things like that where we can throw AI at a problem is generating something better, even if we don't know why exactly it's better yet.
- JimDabell 1y ago> Initially, the AI’s designs seemed outlandish. “The outputs that the thing was giving us were really not comprehensible by people,” Adhikari said. “They were too complicated, and they looked like alien things or AI things. Just nothing that a human being would make, because it had no sense of symmetry, beauty, anything. It was just a mess.” This description reminds me of NASA’s evolved antennae from a couple of decades ago. It was created by genetic algorithms: https://en.wikipedia.org/wiki/Evolved_antenna https://en.wikipedia.org/wiki/Evolved_antenna
- carabiner 1y ago[mandatory GA antenna post requirement satisfied]
- esperent 1y agoThat evolved antenna is a piece of wire with exactly 6 bends. It's extremely simple, the exact opposite of a hard to understand mess.
- rcxdude 1y agoLacking symmetry, it's extremely hard to understand how the antenna actually works (i.e. why those six bends, as opposed to any other random six bends).
- jmogly 1y agoI love the idea of faith based technology, where it just works but nobody is capable of comprehending why or how.
- dialup_sounds 1y agoPraise the Omnissiah!
- isolli 1y agoThis is also quite common in medicine...
- luketaylor 1y agoReferring to this type of optimization program just as “AI” in an age where nearly everyone will misinterpret that to mean “transformer-based language model” seems really sloppy
- andai 1y agoThat's how I feel about Web 3.0...
- buu700 1y agoWeb 3(.0) always makes me think of the time around 14 years ago when Mark Zuckerberg publicly lightly roasted my room mate for asking for his predictions on Web 4.0 and 5.0.
- tomrod 1y agoI know, but can we blame the masses for misunderstanding AI when they are deliberately misinformed that transformers are the universe of AI? I think not!
- zeofig 1y agoAbsolutely agree.
- bee_rider 1y agoHow can one article be expected to fix the problem of people sloppily using “AI” when they mean LLM or something like that?
- rachofsunshine 1y agoI use "ML" when talking about more traditional/domain specific approaches, since for whatever reason LLMs haven't hijacked that term in the same way. Seems to work well enough to avoid ambiguity. But I'm not paid by the click, so different incentives.
- smj-edison 1y ago
- qz_kb 1y agoThis is not "AI", it's non-linear optimization...
- topspin 1y ago"It added an additional three-kilometer-long ring between the main interferometer and the detector to circulate the light before it exited the interferometer’s arms." Isn't that a delay line? The benefit being that when the undelayed and delayed signals are mixed, the phase shift you're looking for is amplified.
- heisenbit 1y agoSounds like ring lasers. Not really an unusual concept to increase sensitivity.
- smj-edison 1y agoAm I understanding the article correctly that the created a quantum playground, and then set thein algorithm to work optimizing the design within the playgrounds' constranits? That's pretty cool, especially for doing graph optimization. I'd be curious to know how compute intensive it was.
- MITSardine 1y agoThey mention 1.5 million CPU hours https://journals.aps.org/prx/abstract/10.1103/PhysRevX.15.021012 https://journals.aps.org/prx/abstract/10.1103/PhysRevX.15.02...
- eleveriven 1y agoFeels like we're entering a new kind of scientific method. Not sure if that's thrilling or terrifying, but definitely fascinating
- matt3210 1y agoThe "AI" here is not the same "AI" as claude, Grok or OpenAI. It's just an optimization algorithm that tries different things in parallel until it finds a better solution to inform the next round.
- jeroenhd 1y ago> It's just an optimization algorithm that tries different things in parallel until it finds a better solution to inform the next round. ... which is AI. AI existed long before GPTs were invented, and when neural networks were left unexplored as the necessary compute power wasn't there.
- LeroyRaz 1y agoThe standard term is Machine Learning (ML). It's not artificial intelligence (AI) because there is no sense of attempting to manipulate concepts (e.g., the classic symbolic conceptual manipulation algorithms, or modern foundation models).
- tgv 1y agoThe meaning of AI has been replaced through sheer popularity. Just like you can't go around calling people "gay" anymore when you mean "jolly, happy."
- kristjank 1y agoImpressive results, I remember reading about AI-generated microstrip RF filters not too long ago, and someone already mentioned evolved antenna systems. We are suffering from a severe case of calling gradient descent AI at the moment, but if it gets more money into actual research instead of LLM slop, I'm all for it.
- Huxley1 1y agoThis AI-designed experiment is pretty cool. It seemed kind of weird at first, but since it actually works, it’s worth paying attention to. AI feels more like a powerful tool that helps us think outside the box and come up with fresh ideas. Is AI more of a helper or a creator when it comes to research?
- theteapot 1y agoAFAICT "The AI" (which is never actually described in the article) is a CSOP solver.
- omnicognate 1y agoThey should stop optimizing their Company Share Option Plans and get back to work! (It was a gradient descent optimizer, so probably unconstrained optimization rather than a Constraint Satisfaction Optimization Problem, but it might have had constraints.)
- WhyNotHugo 1y agoArticle mentions that if students present these designs, they’d be dismissed as ridiculously. But when AI present them, they’re taken seriously. I wonder how many times these designes were dismissed because humans who think out of the box too much are dismissed. It seems that students are encouraged NOT to do so, severely limiting how far out they can explore.
- gewbie 1y ago[dead]
- Arkhaine_kupo 1y agoIts a cost risk analysis. We have tried letting studdents do whatever and most of the time it went nowhere, so we ended up with a more rational system (with many caveats) where experiments are proposed and people with good insights and sense of whether it might even work approve it before running it. AI is going through the wild phase were people are allowing it to test, as soon as the limits are understood the framework of limitations and the rational system built around will inevitably happen.
- wongarsu 1y agoAcross basically all fields you have to first show that you can think inside the box before you are allowed to bring out-of-the-box ideas. Once you have shown that you mastered the craft and understood the rules you can get creative, but before that creativity is rarely valued. Doesn't matter if you are an academic or an artist, the same rules apply I'm guessing AI gets the benefit of the doubt here because its ideas will be interesting and publishable no matter the outcome
- mandmandam 1y agoYou can do all the 'proving your chops' and in-the-box thinking in the world and still get ostracized for your creative insight. * Semmelweis - medicine. Demonstrated textbook obstetric technique at Vienna General Hospital, then produced statistically impeccable data showing that hand-washing slashed puerperal fever mortality. Colleagues drove him out of the profession, and he died in an asylum. * Barbara McClintock - genetics. Member of the National Academy, meticulous corn geneticist; her discovery of “jumping genes” (transposons) was ignored for 30 years and derided as “mysticism.” * Georg Cantor - mathematics. Earned a Ph.D. and published dozens of orthodox papers before writing on transfinite numbers; was then declared “a corrupter of youth”. Career was blocked, contributing to a breakdown. * Douglas Engelbart - computer science. Published conventional reports for years. When he presented the mouse, hypertext, and videoconferencing in “The Mother of All Demos” (1968), ARPA funding was slashed and he was professionally sidelined for the next twenty years. Then you've got Stravinsky, Van Gogh, Caravaggio, James Joyce; all who displayed perfect 'classical' techniques before doing their own thing. In economics you've got Joan Robinson and Elinor Ostrom. And let's not forget Galileo. I'd even put Assange in this list. So, "following the rules" before attempting to revolutionize your field doesn't seem to actually help all that much. This is a major problem, consistent across many centuries and cultures, which ought to be recognized more.
- k__ 1y ago"it had no sense of symmetry, beauty, anything. It was just a mess." Reminds me of the square packing problem, with the absurdly looking solution for packing the 17 squares. It also reminds me of edge cases in software engineering. When I let an LLM write code, I'm often confused how it starts out, thinking, I would have done it more elegantly. However, I quickly notice, that the AI handled a few edge cases I only would habe caught in testing. Guess, we should take a hint!
- codeaether 1y agoThese days, it feels like “AI” basically just means neural network-based models—especially large autoregressive ones. Even convolutional neural networks probably don’t count as “real AI” anymore in most people’s eyes. Funny how things change. Not long ago, search algorithms like A* were considered the cutting edge of AI.
- LeroyRaz 1y agoThe article is misleading and badly written. None of the mentioned works seem to have used language or knowledge based models. It looks like all the results were driven by optimization algorithms, and yet the writing describes AI 'using' concepts and "tricks". This type of language is entirely inappropriate and misleading when describing these more classical (if advanced) optimization algorithms. Looking at the paper in the first example, they used an advanced gradient descent based optimization algorithm, yet the article describes "that the AI was probably using some esoteric theoretical principles that Russian physicists had identified decades ago to reduce quantum mechanical noise." Ridiculous, and highly misleading. There is no conceptual manipulation or intuition being used by the AI algorithm! It's an optimization algorithm searching a human coded space using a human coded simulator.
- HarHarVeryFunny 1y agoRight - I hate that "AI" is just being used as (at best) a replacement term for ML, and very misleading for the public who is being encouraged to believe that some general purpose AGI-like capabiity is behind things like this. The article is so dumbed down that it's not clear if there is even any ML involved or if this is just an evaluation of combinatorial experimental setups. > The outputs that the thing was giving us were really not comprehensible by people, > Adhikari’s team realized that the AI was probably using some esoteric theoretical principles that Russian physicists had identified decades ago to reduce quantum mechanical noise. I'll chalk this one up to the Russians, not "AI".
- MITSardine 1y agoThis doesn't even seem to be ML, though.
- bubblyworld 1y agoI think it's pretty clear that they suspect the mechanism underlying the model's output is the same as the mechanism underlying said theoretical principles, not that the AI was literally manipulating the concepts in some abstract sense. I don't really get your rabid dismissal. Why does it matter that they are using optimisation models and not LLMs? Nobody in the article is claiming to have used LLMs. In fact the only mention of it is lower down where someone says they hope it will lead to advances in automatic hypothesis generation. Like, fair enough?
- sampo 1y agoNot-so-many years ago, this kind of work developing optimization algorithms would have been called optimization algorithms, not AI. > We develop Urania, a highly parallelized hybrid local-global optimization algorithm, sketched in Fig. 2(a). It starts from a pool of thousands of initial conditions of the UIFO, which are either entirely random initializations or augmented with solutions from different frequency ranges. Urania starts 1000 parallel local optimizations that minimize the objective function using an adapted version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. BFGS is a highly efficient gradient-descent optimizer that approximates the inverse Hessian matrix. For each local optimization, Urania chooses a target from the pool according to a Boltzmann distribution, which weights better-performing setups in the pool higher and adds a small noise to escape local minima. https://journals.aps.org/prx/abstract/10.1103/PhysRevX.15.021012 https://journals.aps.org/prx/abstract/10.1103/PhysRevX.15.02...
- MITSardine 1y agoThis irks me to no end, why not just call it applied mathematics algorithms to not use specific terms, rather than AI. Is grep AI? Is your web browser AI?
- pavon 1y agoIt does look like the gradient descent is paired with a type of genetic algorithm: > For each local optimization, Urania chooses a target from the pool according to a Boltzmann distribution, which weights better-performing setups in the pool higher and adds a small noise to escape local minima. These choices add a global character to the exploration. When one of the local optimizations of Urania finds a better parameter setting for a setup in the pool, it replaces the old solution with the superior one. Upon convergence, Urania repeats and chooses a new target from the pool. In parallel, Urania simplifies solutions from the pool by probabilistically removing elements whose removal does not impact the overall sensitivity.
- deleted 1y ago[deleted]
- lawlessone 1y ago>they gave the AI all the components and devices that could be mixed and matched to construct an arbitrarily complicated interferometer. The AI started off unconstrained. It could design a detector that spanned hundreds of kilometers and had thousands of elements, such as lenses, mirrors and lasers. sounds kinda like the chip designer AI