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Cosmic simulations that once needed supercomputers now run on a laptop
- thatjoeoverthr 1y agoGoogle has also a global weather model yielding by ten day predictions, and open street map runs local as well. Just today with GraphHopper and a map of Europe I can generate 2700 routes per second on my workstation. When I was young these were not things you could run at home!
- timschmidt 1y agoAdd to that Qwen3-Omni which can run on a well spec'd workstation, and will happily carry on natural language spoken conversations with you, and can work intelligently with images and video as well as all the other stuff LLMs already do. I don't think Paramount would look kindly on giving it Majel Barret's voice, but it sure feels like talking to the computer on the holodeck.
- thatjoeoverthr 1y agoFor personal use, I won't tell Paramount :)
- SwtCyber 1y agoIt's wild how much has shifted in just a couple of decades
- JumpCrisscross 1y agoThe emulator: https://github.com/CosmologicalEmulators/Effort.jl https://github.com/CosmologicalEmulators/Effort.jl
- observationist 1y agoMoore's law surprises people way more than it should by now. This is an awesome project!
- crazygringo 1y agoThis has nothing to do with Moore's law. It's about neural networks.
- crazygringo 1y ago> The breakthrough combines neural networks... This is the important part. It's not guaranteed to be accurate. They claim it "delivers essentially the same correctness as the model it imitates -- sometimes even finer detail". But can you really trust that? Especially if each frame of the simulation derives from the previous one, then errors could compound. It seems like a fantastic tool for quickly exploring hypotheses. But seems like once you find the result you want to publish, you'll still need the supercomputer to verify?
- jacquesm 1y agoThat 'finer detail' sounds suspiciously like inventing significant digits from less significant inputs. You can interpolate, for sure, but it isn't going to add any information.
- w_for_wumbo 1y agoEspecially if each frame of the simulation derives from the previous one. How do you think this universe works, to me that sounds exactly the same. Every moment is derived from the previous instant.
- HPsquared 1y agoSimulating the simulation.
- SwtCyber 1y agoStarts feeling like a philosophical problem as much as a computational one
- tom_mc 1y agoNice work, Marco! I'm glad to see emulators being built for DESI. I worked on emulators for DES. Emulators have existed in astrophysics long before ML became part of the zeitgeist. The earliest cosmology emulator paper that I'm aware of is from 2009 here: https://arxiv.org/abs/0902.0429 https://arxiv.org/abs/0902.0429. IIRC the method came from fluid dynamics. It just so happens that the interpolators used under the hood (clasically it was GPs but is NNs latelys) are also popular in ML, and so the method gets lumped into the ML pile. The key difference between emulation and typical ML is that emulation is always in an interpolation setting, whereas typically predictive ML is extrapolating in one way or another (e.g. predicting future events). Congrats to the authors!
- mosesbp 1y agoI’m glad this kind of work is getting highlighted on HN, but this is an extremely misleading title, to the point of being outright false. As often happens, this appears to be due to PR titles being controlled by non-specialists, not the study authors. While the work the authors do is important, in no sense does the tool they produced actually run a simulation. A simulation implies a physical model and usually partial differential equations that are often solved on supercomputers, but here the neural network is rather interpolating some fixed simulation output in a purely data-driven way. The simulations have not gotten faster due to neural networks, cosmologists have just gotten better at using them. Which is great! Edit: see the sub-comment in the thread by crazygringo for the lead author’s take
- sundarurfriend 1y agoThe title and the article are both independently true, just not together :) As in, there are certainly cosmic simulations that once needed supercomputers which now run on a laptop, that's just the story of computational progress. More seriously though, https://www.404media.co/a-vast-cosmic-web-connects-the-universe-really-now-we-can-emulate-it/ https://www.404media.co/a-vast-cosmic-web-connects-the-unive... is another nice article about this work. It has a bit less detail (i.e. less proper nouns in it), but is more readable for it IMO.
- SiempreViernes 1y agoThe lead author explains the work in this comment: https://news.ycombinator.com/item?id=45381598 https://news.ycombinator.com/item?id=45381598 (It was a bit difficult to find by just scrolling)
- SwtCyber 1y agoThat said, I do think the work is still a big deal. Emulators like this are crucial for exploring parameter spaces and doing inference at scale
- andrewgleave 1y agoNot cosmological but yesterday Apple released an interesting protein folding model with 3B param transformer-based arch which runs on M-series hardware and is competitive with state-of-the art models. [1] Code [2] [1] https://arxiv.org/pdf/2509.18480 https://arxiv.org/pdf/2509.18480 [2] https://github.com/apple/ml-simplefold https://github.com/apple/ml-simplefold
- metalman 1y agowords fail, simpulations, educated speculations, or whatever, the main thing is to preface these sorts of thing with some indication of there limitations and purely theoretical results, use them as such, and normalise the process of asking if the model has been verified with an observation
- k2enemy 1y agoGreat to see a Julia project featured. I keep rooting for Julia to take off, but python's dominance in AI has me doubtful. It is such a great language, and capable of ML and AI workloads, as evidenced by this research.
- SwtCyber 1y agoFeels like the kind of hybrid approach that could become the norm in other fields too