Learning Over Time 

Spring ScHool

 Let's Rethink Machine Learning Algorithms

Topics

A spring school on Machines that continuously learn over time (LOT)


...Beyond training, test and deploy

...Beyond datasets

...Beyond CENTRALIZED LEARNING

...Back to learning algorithms



what is lot about?

Time as the protagonist of learning

Sensory information is characterized by a natural temporal development of the data that is commonly neglected by current technologies. In nature, we do not learn from a huge dataset of "shuffled images", and we do not store our entire visual life, stochastically sampling from it. Interacting over time allows multiple agents to share information at different stages of their development, to grow their own skills in an appropriate manner, or to help other agents improve: we educate children in function of their skills at the current age...

Is there a problem with current AI technologies?

The growing ubiquity of Large Language Models (LLM) has recently opened strong debates on scenarios giving rise to potentially rogue AIs involving social and political aspects. The source of these debates is deeply connected with the exploitation of increasingly large data collections, which requires huge financial resources, thus leading to the centralization of information. This aspect produces undeniable privacy problems as well as very controversial geopolitical effects. In a nutshell: data centralization issues; privacy and geopolitical issues;  energy efficiency issues; limited control, customizability, and causality.

Look forward!

The outstanding results of current Machine Learning-based models should be still massively leveraged by the current technologies. However, they are all based on previously collected datasets and networks trained by stochastically sampling from them, without any dynamic human intervention: humans are only bare data labelers, then they are out of the game.


Let's discuss these topics and other related ones, let's meet in Siena! 

Let's define the new research directions that we need to follow to propose the AI ​​technologies of the future!

See you in Siena!!! :) 

Present your WORK AS A POSTER!  [new]

You have the opportunity to showcase your work if it aligns with the topics of the school (see the list on this page).

Both already published papers and ongoing projects are welcome as posters. This is a great chance to interact with school participants, receive feedback, and discuss new ideas.

Submission Details:

There are no proceedings, so don't worry! We will simply ensure the topic of your work is relevant to the school's themes.

when: March 24-27 2025

Timeline



VEnue: CErtosa di Pontignano, SIena, Italy

LECTURERS

Organizers

 University of Siena

University of Pisa

University of Pisa

Scuola IMT Alti Studi Lucca

Italian Institute of Technology

contact us

If you're keen on joining our educational community, receiving our newsletters, exploring sponsorship or partnership possibilities, or staying informed about our advancements, please don't hesitate to reach out to us via email.

ARE YOU INTERESTED IN ATTENDING? LET US KNOW!

Further details in the Registration page