On May 20, 2024, Brian Plancher, assistant professor of computer science, led the publication of a new paper in the Proceedings of the AAAI 2024 Spring Symposium Series, alongside 41 collaborators affiliated with 35 institutions around the globe, titled “TinyML4D: Scaling Embedded Machine Learning Education in the Developing World.”
The article explores the challenges and opportunities in making machine learning education more accessible worldwide. It also highlights the efforts of the TinyML4D community, of which Plancher is a leading member, in advancing this mission. TinyML4D's efforts are focused on embedded machine learning on low-power devices, also known as TinyML, which drastically lowers the cost and resources needed for hands-on machine learning applications. TinyML is an increasingly relevant branch of AI education, but, as Plancher explains, different barriers limit its accessibility, especially in developing countries. TinyML4D aims to close this gap through efforts including the development of open-source curricula and international workshops co-created by international educators.
The project originated from TinyML courses Plancher helped develop at Harvard University, offered in-person and online via the edX platform. These courses have since evolved into extensive international outreach efforts through academia-industry partnerships led on the academic side by Harvard University, The Abdus Salam International Centre for Theoretical Physics (ICTP), Universidade Federal de Itajubá (UNIFEI), and Barnard College. Industry collaborators include Arduino, Seeed Studio, Edge Impulse, Google, and the TinyML Foundation, as a result of these collaborative efforts, TinyML4D has amassed a library of free embedded ML resources, available on the TinyMLedu.org website.
Looking to the future, Plancher and his colleagues emphasize the need to further develop modular and inclusive learning resources, and build on the existing academia-industry partnerships, to fully transform embedded ML into a global gateway to embedded AI skills development.