Programme

Note: work in progress. We are organising a mix of lively paper sessions, lightning talks, and tutorials on low footprint AI.

Watch this space!

Tutorials (provisional, to be confirmed)

Tutorial One (2 hours)

Circular AI Infrastructure: Repurposing Existing Compute for Scalable Workloads

Delivered by Kalavai (https://kalavai.net/)

As part of the LOCO 2026 programme at Lancaster University, this tutorial explores how AI infrastructure can be rethought through a circular, sustainability-driven lens. Rather than relying on continual hardware refresh cycles, participants will be introduced to an approach that aggregates underutilised, on-premise compute into a unified, high-performance environment.

Using the Kalavai platform, the session will demonstrate how existing resources can be repurposed to support modern AI workloads, including large language models and custom research pipelines. Attendees will gain practical insight into deploying and managing distributed compute across heterogeneous environments, while extending hardware lifetimes and reducing both cost and environmental impact. The tutorial is particularly relevant for researchers and practitioners seeking scalable AI solutions within constrained or sustainability-focused settings.

Tutorial 2 (day 2, 4 to 6 hours)

Federated Learning with Flower: From Foundations to Sustainable Systems

Delivered by Flower AI (https://flower.ai/)

This extended tutorial provides a comprehensive introduction to federated learning within the context of LOCO 2026, combining theoretical foundations with hands-on system design. Participants will work through the core principles of decentralised model training, where data remains distributed across devices or domains, and models are trained collaboratively.

Using the Flower framework, attendees will explore key challenges including communication efficiency, scalability, and privacy-preserving mechanisms. The session also considers the broader system implications of federated approaches, including their impact on resource usage and environmental footprint. By the end of the tutorial, participants will have a clear understanding of how to design, implement, and evaluate federated learning systems that are both effective and sustainable for real-world deployment.