TinyML UK Network
Call for demonstrations

Share your TinyML demo

The TinyML UK Network invites practical demonstrations of TinyML and edge AI, from smart sensing and health wearables to drones, rovers, robotics and collaborative devices. Share your prototype, show how it works and tell us what makes it useful. Call for TinyML demos (research prototypes and commercial products). We are planning high-profile events across the UK, Europe and internationally, and we are looking for high-quality demonstrations of TinyML on extreme constrained devices. We welcome demos spanning chips, model optimisation and MLops, neuromorphic and RISC-V computing, hybrid and mixed-signal architectures, heterogeneous chips, neural accelerators NPUs, GPUs, TPUs and combinations of these technologies. We are also interested in collaborative, distributed and federated learning, continual learning, generative AI, small language models #sml, open specialised models and on-device chatbots. Physical AI demonstrations are welcome, including companion robots, robotics, drones and rovers, alongside intelligent sensing, AI-based sensor management on extremely constrained devices and cyber-physical security.Applications could include healthcare and wearables, agriculture, environmental monitoring, manufacturing, infrastructure and autonomous systems. A clear TinyML contribution should be at the core, we are not looking for general IoT platforms or standard communications networks. Demos should be practical to present and easy to explain to policymakers, the public and people from different disciplines, while retaining technical substance. We want to show how the technology works, what it enables and why it matters. This will be an opportunity to demonstrate your work to leading industry experts and researchers, engage wider audiences and explore collaborations. If you have a research prototype or a commercial product suitable for demonstration, please get in touch at eiman.kanjo@ntu.ac.uk, ideally with a brief description, video or link and any practical requirements.

Submit your demo ↗ TinyML demos