La intel·ligència artificial ha estat durant molt de temps un element bàsic de la fantasia i la ciència-ficció, però ja no és només això, sinó una cosa que ja tots fem servir i farem servir més cada dia. La manera com això canviarà la manera de treballar, d’estudiar o de divertir-se és encara un aspecte molt obert, però en bona part depèn de nosaltres i del bon o mal ús que en fem. En aquesta xerrada veurem, amb exemples pràctics com el Chat-GPT, que és un algorisme, com els algorismes d’intel·ligència artificial ens poden obrir possibilitats interessants i també com aquests algorismes, en males mans, poden comportar conseqüències molt negatives per tota la societat.
Aquesta xerrada es durà a terme durant la Matefest de la facultat de matemàtiques de la Universitat de Barcelona. El formulari per apuntar-se a la xerrada és el següent:
https://forms.gle/iUon7rXwWFAt5Fsp8
Universitat de Barcelona
Professor
In 2007, Jordi Vitrià joined the University of Barcelona (UB) as Full Professor, where he teaches an introductory course on Algorithms and advanced courses on Data Science and Deep Learning. From April 2011 to January 2016 he served as Head of the Applied Mathematics and Analysis Department, UB. Now, he is member of the new Mathematics & Computer Science Department at UB. He is also Direct…
In 2007, Jordi Vitrià joined the University of Barcelona (UB) as Full Professor, where he teaches an introductory course on Algorithms and advanced courses on Data Science and Deep Learning. From April 2011 to January 2016 he served as Head of the Applied Mathematics and Analysis Department, UB. Now, he is member of the new Mathematics & Computer Science Department at UB. He is also Director of the Master in Foundations of Data Science and co-director of the Big Data and Data Science Postgraduate course at the UB.
His research, when personal computers had 128KB of memory, was originally oriented towards digital image analysis and how to extract quantitative information from them, but soon evolved towards computer vision problems. After a postdoctoral year at the University of California at Berkeley in 1993, he focused on Bayesian methods for computer vision methods. Now, he is leading a research group working in deep learning, computer vision and machine learning. He has authored more than 100 peer-reviewed papers and 8 international patents. He has directed 12 PhD theses in the area of machine learning and computer vision. He has been the leader of a large number of research projects at international and national level.
He has been always interested in connecting his academic work to the social environment, and since 1993 he has been involved in a large number of projects to transfer academic knowledge to industrial production, medical diagnose and media applications. He is now director of the DataScience@UB group technology transfer group that is supported by the Generalitat de Catalunya.
GDSC Lead
GDSC Lead
GDSC Lead
Core Team Member
Core Team Member
Core Team Member
Core Team Member
Core Team Member
Core Team Member
