🚨🚨Please RT! 📢📢 Following last year’s success, International workshop Physics of Biological Systems is back in May! Free registration! Submit talk or poster abstract. @HiggsCentre @PhysAstroEd @SBSatEd bit.ly/EdinPBS2025

A bit of advertisement for our CECAM workshop «Stochastics processes: Inferences in complex systems» in Lausanne on May 14-16, 2025. Registration deadline for abstracts: Feb 23, 2025. More details on cecam.org/workshop-details/s…

Over time, the boundaries of physics have expanded as new ideas — once seen as outside the discipline — have been embraced by the broader community. Fields like biological physics and quantum information were once met with skepticism, yet today they are integral to physics. Now, with the 2024 Nobel Prize in Physics recognizing artificial neural networks, we're adding artificial intelligence to the list. There’s been questioning online about this year’s physics prize — specifically about whether John Hopfield and Geoffrey Hinton’s work on artificial neural networks is actually physics. Our CEO Jonathan Bagger says it is. Here’s what he said: At its core, physics focuses on understanding how the universe works. Sometimes that comes from studying complex systems, which is exactly what Hopfield and Hinton did. They used tools from statistical physics to create systems that emulate the brain. Both Hinton and Hopfield modeled neural networks as physical systems of interconnected nodes — with each node equivalent to something like an atomic spin. The interactions between the nodes can be adjusted, or trained, so that the network appears to “learn,” in that a specific “memory” is associated with the system’s ground state. Because statistical physics is essential to analyzing such systems, it is fair to say that physics underlies artificial intelligence. So while this year’s prize might not feature black holes, neutrinos, or entangled quantum states — topics most often recognized as physics — the efforts of Hopfield and Hinton are clearly grounded in physics. It’s also the latest in a long history of Nobel Prizes that spotlight impactful tools for physics and many other disciplines, from groundbreaking inventions in laser physics to new methods for discovering quantum particles. These tools are especially important now, as physics moves towards larger, more complex experiments – which will require artificial intelligence to make headway in analyzing the data and unlocking the discoveries.

Tools from statistical physics shed light on important ecology problem: how complex ecosystems maintain their stability. Work by @GiulioBiroli, @ada_altieri, and @GiuliaLorenzana. go.aps.org/3WM3ybG

In this work, I learned a lot a lot about the data and the rich framework of disordered systems! I want to really thank @ada_altieri and @SamirSuweis for their invaluable help and guidance. Also, I thank the other co-authors for their contributions. [15/n]

#RésultatScientifique 🔎 | Comment la perte de biodiversité déstabilise les écosystèmes 🤝 @ada_altieri #MSC @CNRS @univ_paris_cite @CNRS_Villejuif @CNRSphysique insis.cnrs.fr/fr/cnrsinfo/co…

#ResultatScientifique 🔎| Des physiciennes et physiciens ont montré comment l’hétérogénéité spatiale et relationnelle est un ingrédient indispensable au maintien à long terme d’une diversité écologique importante dans les vastes écosystèmes naturels. ➡️inp.cnrs.fr/fr/cnrsinfo/comm…