Spring School on Learning Over Time

LOT 2 Spring School – Learning Over Time (LOT 2.0) – is a four-day school that will take place in CTTC, from 27 to 30 April 2026, dedicated to machines that learn continuously and sustainably over time, beyond traditional data-hungry and centralized AI paradigms. It focuses on rethinking the role of data and promoting lean, energy-efficient learning solutions, inspired by the principles of Collectionless AI.

The program will cover key topics such as continual and lifelong learning, reinforcement learning, time series, representation and universal representation learning, collaborative and decentralized learning, brain-inspired computing, online and active learning, curriculum learning, domain adaptation, transfer learning, in-context learning, and on-device learning. The school brings together leading speakers and researchers to address current challenges of large-scale AI, including data centralization, privacy and geopolitical concerns, energy efficiency, and the need for more controllable and customizable learning systems.

LOT 2 Spring School invites students, early-career researchers, and professionals to engage in an open discussion on the future of AI, where time, interaction, and continuous adaptation become central to how intelligent systems are designed and deployed. Registration is already open, and participants are also encouraged to contribute to the Call for Posters, with a Best Poster Award granted by the scientific committee during the school.