FIAS - Frankfurt Institute for Advanced Studies

BREAKING NEWS The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Physics to John J. Hopfield and Geoffrey E. Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks.” This year’s two Nobel Prize laureates in physics have used tools from physics to develop methods that are the foundation of today’s powerful machine learning. John Hopfield created an associative memory that can store and reconstruct images and other types of patterns in data. Geoffrey Hinton invented a method that can autonomously find properties in data, and so perform tasks such as identifying specific elements in pictures. When we talk about artificial intelligence, we often mean machine learning using artificial neural networks. This technology was originally inspired by the structure of the brain. In an artificial neural network, the brain’s neurons are represented by nodes that have different values. These nodes influence each other through connections that can be likened to synapses and which can be made stronger or weaker. The network is trained, for example by developing stronger connections between nodes with simultaneously high values. This year’s laureates have conducted important work with artificial neural networks from the 1980s onward. John Hopfield invented a network that uses a method for saving and recreating patterns. We can imagine the nodes as pixels. The Hopfield network utilises physics that describes a material’s characteristics due to its atomic spin – a property that makes each atom a tiny magnet. The network as a whole is described in a manner equivalent to the energy in the spin system found in physics, and is trained by finding values for the connections between the nodes so that the saved images have low energy. When the Hopfield network is fed a distorted or incomplete image, it methodically works through the nodes and updates their values so the network’s energy falls. The network thus works stepwise to find the saved image that is most like the imperfect one it was fed with. Geoffrey Hinton used the Hopfield network as the foundation for a new network that uses a different method: the Boltzmann machine. This can learn to recognise characteristic elements in a given type of data. Hinton used tools from statistical physics, the science of systems built from many similar components. The machine is trained by feeding it examples that are very likely to arise when the machine is run. The Boltzmann machine can be used to classify images or create new examples of the type of pattern on which it was trained. Hinton has built upon this work, helping initiate the current explosive development of machine learning. Learn more Press release: https://bit.ly/4gCTwm9 Popular information: https://bit.ly/3Bnhr9d Advanced information: https://bit.ly/3TKk1MM

Das Anwesende des Abwesenden – Kunst trifft Wissenschaft 🌌 Wir freuen uns bei der Ausstellung „Das Anwesende des Abwesenden“ im Frankfurter Kunstverein mit unserem Astrophysiker Prof. Dr. Luciano Rezzolla dabei zu sein. 📅 Das Anwesende des Abwesenden | 12. Oktober 2024 – 2. März 2025, Eröffnung am 11. Oktober 2024, um 18:30 Uhr 🕚 Di – So: 11 – 19 Uhr | Do: 11 – 21 Uhr | Mo: geschlossen 📍 Frankfurter Kunstverein, Steinernes Haus am Römerberg, Markt 44, FFM Gemeinsam mit dem internationalen Team des Event Horizon Telescope-Projekts gelang es Prof. Dr. Luciano Rezzolla, das erste Bild eines Schwarzen Lochs zu erfassen – ein Moment, der die Grenze zwischen Abwesenheit und Präsenz sprengt. In der Ausstellung werfen wir einen Blick auf dieses unfassbare Bild. Mit visuellen Darstellungen und 3D-Modellen werden die unvorstellbaren Kräfte des Universums greifbar gemacht. 🕳️💫 Die von Prof. Franziska Nori kuratierte Ausstellung zeigt, wie Kunst und Wissenschaft Hand in Hand gehen, um das Unsichtbare sichtbar zu machen und unser Verständnis von Raum und Zeit zu erweitern. 🔗 Weitere Infos zu unserer Ausstellungskooperation mit dem Frankfurter Kunstverein finden Sie im Interview: https://lnkd.in/e8TudTpP. #DasAnwesendeDesAbwesenden #Ausstellung #Exhibition #FrankfurterKunstverein #GoetheUni #LucianoRezzolla #SchwarzesLoch #Astrophysik #FranziskaNori #KunstundWissenschaft #Frankfurt #Kunst #Wissenschaft #Universum #Interview