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The Workshop on TinyML for Sustainable Development will be held in-person in São Paulo, Brazil from July 22-26 2024.
Register to attend for free by May 6, 2024 on the ICTP website!
TinyML enables machine learning on low-power microcontrollers, democratizing access to performant AI in remote, resource-constrained settings. This revolutionary technology unlocks new possibilities for sustainable development and scientific research by increasing equitable access to on-device intelligence worldwide.
The emergence of TinyML has created new possibilities for building smart, ultra-low-power devices ideal for resource-constrained settings. In recent years, TinyML has attracted significant interest from researchers, developers, and industries for its potential to enable innovative applications in healthcare, agriculture, transportation, conservation, smart homes, and more. TinyML’s extremely low bandwidth and energy requirements make it uniquely suited for regions with limited access to reliable energy and computing infrastructure. Though currently restricted in reach, TinyML intersects topics across computer science and engineering curricula, making it an impactful educational tool. This hands-on workshop focuses on TinyML applications relevant to Latin American researchers, providing training on commercially available hardware optimized for embedded ML deployment. By making TinyML more accessible, especially in the Global South, this workshop will empower researchers to develop localized solutions that benefit their communities.
Keynote Speaker Raquel Zarattini Chebabi Think Lab Brazil Manager and IBM Senior Research Scientist
Workshop Topics:
- Introduction to TinyML
- Sensors and Data Collection
- Energy Efficiency
- Environmental Monitoring
- Health Monitoring
- Agriculture Monitoring
- Smart Cities
- Ethics and TinyML
View the Workshop Flyer!
The workshop will run daily from 9:00 AM to 5:00 PM local time. You can find a draft schedule below, exact timing and topics subject to change.
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Contact edu@tinyml.org with any questions regarding this workshop.
We would like to thank ICTP, IBM Research: Brazil, Harvard SEAS, Barnard College, the Universidade Federal de Itajubá, and the tinyML Foundation for their continued leadership and support of our TinyML educational content!