Learning on the Edge
Adam Zewe | MIT News Office
A new technique enables AI models to continually learn from new data on intelligent edge devices like smartphones and sensors, reducing energy costs and privacy risks.
IIoT, Industry 4.0, and Industrial Machine Learning: a 25 Year Retrospective, Current Lessons-learned, and Future Trajectories
Wednesday, October 5, 2022 | 12:00 - 1:00pm ET, RLE Room 36-462
Speaker: Vivek Dave, Harting Innovation Hub
Near-zero Power Integrated Microsystems for the IoT
Wednesday, June 15, 2022 | 3:00pm - 4:00pm ET, Grier Room 34-401
Speaker: Matteo Rinaldi, Northeastern University
TinyML: Enable Efficient Deep Learning on Mobile Devices
Song Han
This project pursues efficient machine learning for mobile devices where hardware resources and energy budgets are very limited.
System Brings Deep Learning to “Internet of Things” Devices
Daniel Ackerman | MIT News Office
Deep learning is everywhere. This branch of artificial intelligence curates your social media and serves your Google search results.
Securing the “Internet of Things” in the Quantum Age
Rob Matheson | MIT News Office
Efficient chip enables low-power devices to run today’s toughest quantum encryption schemes.