This compact, low-power receiver could give a boost to 5G smart devices
Researchers designed a tiny receiver chip that is more resilient to interference, which could enable smaller 5G “internet of things” devices with longer battery lives.
Researchers designed a tiny receiver chip that is more resilient to interference, which could enable smaller 5G “internet of things” devices with longer battery lives.
By performing deep learning at the speed of light, this chip could give edge devices new capabilities for real-time data analysis.
MIT researchers developed a fiber computer and networked several of them into a garment that learns to identify physical activities.
This novel circuit architecture cancels out unwanted signals at the earliest opportunity.
MIT engineers developed a tag that can reveal with near-perfect accuracy whether an item is real or fake. The key is in the glue on the back of the tag.
A system designed at MIT could allow sensors to operate in remote settings, without batteries.
With the PockEngine training method, machine-learning models can efficiently and continuously learn from user data on edge devices like smartphones.
The system could improve image quality in video streaming or help autonomous vehicles identify road hazards in real-time.
Mens, Manus and Machina (M3S) will design technology, training programs, and institutions for successful human-machine collaboration.
Abel Sanchez helps industries and executives shift their operations in order to make sense of their data and use it to help their bottom lines.
Researchers demonstrate a low-power “wake-up” receiver one-tenth the size of other devices.
The receiver chip efficiently blocks signal interference that slows device performance and drains batteries.
Cloud security and video forensics software have been transitioned to end users.
Carlo Ratti investigates how digital technologies transform our urban spaces and how they can be harnessed to design sustainable cities for the future.
A new method uses optics to accelerate machine-learning computations on smart speakers and other low-power connected devices.