Principal Investigator Vivienne Sze
The Deep Learning Systems Consortium highlights MIT strengths in Energy-Efficient Multimedia research. Deep learning is playing a vital role in society, and is currently used for many artificial intelligence applications including computer vision, speech recognition, robotics, etc. While deep learnign delivers state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Accordingly, designing efficient hardware and systems for deep learning is critical to enabling its wide deployment, particularly in embedded systems.
This consortium will provide comprehensive coverage of deep learning systems research spanning multiple levels including applicaitons, algorithms, architectures, circuits and devices.
Benefits of Joining the Consortium : Bi-annual Review
(1) Educational Overview (summer)(*) Comprehensive tutorial on deep learning (includes MIT course material)(*) In depth discussion on recent trends in deep learning(*) Discount on multi-day professional education course
(2) Research Review (winter)(*) Update on recent research results on deep learning(*) Guest speakers for a broad coverage of realted topics (e.g. algorithms, applicaiotns and devices)(*) Exposure to on-going EEMS research ($1M worth of funded projects)