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TinyML and Efficient Deep Learning: Course 6.S965

Fall 2022 | Tuesdays & Thursdays, 3:30 - 5:00pm ET

Speaker: Song Han, MIT

computer processor

New Hardware Offers Faster Computation for Artificial Intelligence, with Much Less Energy

Adam Zewe | MIT News Office

Engineers working on “analog deep learning” have found a way to propel protons through solids at unprecedented speeds.

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MIT, Tech Firms Seek to Improve AI’s Energy Efficiency

Emily Bamforth | EDSCOOP

The Massachusetts Institute of Technology is leading a group researching energy efficiency in artificial intelligence, anticipating a moment when advanced systems could suck up power at an unsustainable rate.

Making Quantum Circuits More Robust

Adam Zewe | MIT News Office

Researchers have developed a technique for making quantum computing more resilient to noise, which boosts performance.

microchip

Toward a Stronger Defense of Personal Data

Adam Zewe | MIT News Office

MIT Engineers have built a lower-energy chip that can prevent hackers from extracting hidden information from a smart device.

Climate Implications of Computing & Communications

Thursday, March 3 & Friday, March 4, 2022 | 10:00am - 2:00pm ET

Multiple Speakers

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How MIT’s Muriel Medard Pioneered the Universal Decoder

Kathy Pretz | IEEE Spectrum

Researchers developed a new algorithm and created an efficient silicon chip that eliminates the need for custom decoding hardware to spot signal errors.

What’s Next in AI | Enabling the Future of Computing through Efficient AI

Tuesday, December 7, 2021 | 10:00am-10:30am ET

Speaker: Dr. David Cox, MIT-IBM Watson AI Lab