Physics colloquium
AI research: Lecture on the story behind this year's Nobel Prize in Physics
The lecture at the BUW is dedicated to the Nobel Prize in Physics, which was awarded this year for work on artificial neural networks. // Photo Colourbox
The history of machine learning in general and artificial intelligence in particular has experienced several ups and downs since its beginnings in the 1950s. Against this background, Claudius Gros explains the contribution of this year's two Nobel Prize winners in physics, the US American John Hopfield and the Canadian Geoffrey Hinton: The first AI hype in the 1950s was followed by the AI winter, until there was a resurgence in the 1980s, for which Hopfield and Hinton were among the pioneers. The network invented by Hopfield utilised a method for storing and restoring patterns. Building on this, Hinton developed a network that can learn to recognise characteristic elements in data.
The lecture is part of the "Physics Colloquium" series and will be held in German. It will begin on 9 December at 5 pm in lecture hall 04 (building F, level 10, room 01) on the Grifflenberg campus.
AI and physics
Artificial neural networks, which are modelled on biological neuron networks in the human brain, are an essential technology for the use of artificial intelligence. Although research into artificial intelligence is not one of the core disciplines of physics, it made significant progress in the early days: Back then, research institutions already had to process and analyse large amounts of data. To this end, physics developed methods that strongly influenced the field of AI and its development.
