Forum Numerica - Marco Gori - Collectionless AI and Nature-Inspired Learning


Forum Numerica - Marco Gori - Collectionless AI and Nature-Inspired Learning
Forum Numerica - Marco Gori - Collectionless AI and Nature-Inspired Learning
Abstract

AI is revolutionizing not only the entire field of Computer Science, but nearly all fields of
Science. However, while application contexts explode and LLMs display embarrassing cognitive
qualities, the entire AI research field seems headed toward saturation of the fundamental ideas
that have enabled today’s spectacular results of large companies. Is the infamous “AI winter”
perhaps creeping into research? In this talk I argue that the time is ripe for a fundamental
rethinking of AI methodologies with the purpose to migrate intelligence from the cloud to the
growing global population of devices with on-board CPUs.
To support learning schemes inspired by mechanisms found in nature, I propose
developing intelligent systems within NARNIAN, a platform that enables social mechanisms and
fosters learning processes over time, without the need for data storage.

About the speaker

Marco Gori received the Ph.D. degree in 1990 from Università di Bologna, Italy, working partly
at the School of Computer Science (McGill University, Montreal). He is currently full professor
of computer science at the University of Siena, where he is leading the Siena Artificial Intelligence
Lab. He is mostly interested in Machine Learning with emphasis on Neural Computation.
Since, the end of 2019, He has also been collaborating with the Interdisciplinary Institutes for
Artificial Intelligence, 3IA Côte d’Azur.
The impact of his research on neural networks emerged mainly from the growing interest in
Graph Neural Networks. He introduced the first ideas in the paper “A New Model for Learning
in Graph Domains”, by M. Gori, M. Monfardini and F. Scarselli (IJCNN2005) where the
keyword Graph Neural Network was coined. A few years later, an extended paper “GraphNeural
Networks,” IEEE-TNN, 2009 provided a more robust analysis and an accurate experimental
evaluation. To date, the paper has received more than 10,000 citations (about 6-7 citations/dayin
the last months).
Professor Gori has been the chair of the Italian Chapter of the IEEE Computation Intelligence
Society and the President of the Italian Association for Artificial Intelligence. He is a Fellow of
IEEE, EurAI, IAPR, and ELLIS.