Breaking the Scaling Limits of Analog Computing
Adam Zewe | MIT News Office
MIT researchers have developed a new technique could diminish errors that hamper the performance of super-fast analog optical neural networks.
Ghobadi Wins SIGCOMM Rising Star Award
Alex Shipps | MIT CSAIL News
Manya Ghobadi aims to make large-scale computer networks more efficient, ultimately developing adaptive smart networks.
Deep Learning with Light
Adam Zewe | MIT News Office
A new novel piece of hardware, called a smart transceiver, uses silicon photonics to accelerate machine-learning computations on smart speakers and other low-power connected devices.
TinyML and Efficient Deep Learning: Course 6.S965
Fall 2022 | Tuesdays & Thursdays, 3:30 - 5:00pm ET
Speaker: Song Han, MIT
INFER Fireside Chat – Reasserting U.S. Leadership in Microelectronics
Saturday, May 11, 2022 | 2:00pm - 3:00pm ET
Speaker: Jesús del Alamo, MIT
Spins, Bits, and Flips: Essentials for High-Density Magnetic Random-Access Memory
Tuesday, April 19, 2022 | 11:00am ET, von Hippel Room, 13-2137
Speaker: Tiffany S. Santos, Western Digital Corporation
A New Programming Language for High-performance Computers
Steve Nadis | MIT CSAIL
With a tensor language prototype, “speed and correctness do not have to compete ... they can go together, hand-in-hand.”
Memristor-based Hybrid Analog-Digital Computing Platform for Mobile Robotics
Monday, February 28, 2022 | 1:00 PM – 2:00 PM ET
Speaker: Wei Wu, University of Southern California
TinyML is Bringing Neural Networks to Small Microcontrollers
Ben Dickson | TechTalks
Tiny machine learning, or TinyML, suited for devices with limited memory and processing power, and in which internet connectivity is either non-present or limited.
AI’s Smarts Now Come With a Big Price Tag
Will Knight | Wired Magazine
As language models get more complex, they also get more expensive to create and run. One option is a startup, Mosaic ML, spun out of MIT that is developing software tricks designed to increase the efficiency of machine-learning training.