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Tommaso DorigoRSS Feed of this column.

Tommaso Dorigo is an experimental particle physicist, who works for the INFN at the University of Padova, and collaborates with the CMS experiment at the CERN LHC. He coordinates the European network... Read More »

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As I write these few lines, I am sitting in the nice auditorium at CSIC in Madrid, where I came for a congress that is a bit different to many others that take place around the world at all times. Truth be told, covid-19 took a big hit on the organization of these events, but slowly things are getting back to normality - the only visible sign of something different from 2019 in the auditorium is the fact that about 80 percent of the 180 scientists sitting around me wear a mask.
The "Learning to Discover" workshops and "AI and Physics" conference are taking place at Institut Pascal, a centre set on the top of a hill surrounded by woods near Orsay, France. The event focuses on new artificial intelligence techniques to improve the discovery potential of fundamental science experiments.
Below you can see a summary of the event agenda

- Apr 19-20 Representation learning workshop
- Apr 21-22 Dealing with uncertainties workshop
- Apr 25-26 Generative models workshop

- Apr 27-29 AI and Physics Conference
No.
... Ok, ok, I will elaborate. But first I feel the need to explain what we are talking about here, to anybody who does not have a Ph.D. in particle physics and is still reading this column.

Background: The Tevatron, CDF, and the W boson
Ever since experimental physics was a thing, the worth of scientists could be appraised by how carefully they designed their experiments, making sure that their devices could answer as precisely as possible the questions that crowded their mind. Indeed, the success of their research depended on making the right choices on what apparatus to build, with what materials, what precise geometry, and how to operate it for best results.


(Above: Ramsay and Pierre Curie in their lab)
The late Martin Gardner held for many years a fantastic feature in the popular Scientific American magazine. It was called "Mathematical Games", and it was worth the whole magazine by itself, although SciAm always featured many interesting articles about scientific advancements. Upon picking the magazine up at a newsstand, "Mathematical Games" was the first article I would read as a teenager eager to learn about the endless tricks Gardner taught there, in his wonderful tale-telling style.
Chess is a wonderful game, one that contains in itself a universe of situations, choices to make, strategic concepts, tactical ideas. Through its study we realize how difficult it is to take the correct decision in a maze of opportunities, even when everything is under the sun and nothing is hidden from our view. By losing game after game with stronger opponents we get to learn the hard way -but still, within an imaginary world- that our actions have consequences. Even more: we understand that if we are sometimes powerless to choose correctly even when we have all the information available to us, we cannot possibly believe we can do that in the real world, when we have to deal with incomplete, faulty, or missing data.