Rob Matheson

Writer, MIT News Office

latest from Rob Matheson

Courtesy: Massachusetts Institute of Technology

AI and Machine Learning

Reducing AI’s carbon footprint

Courtesy: Christine Daniloff, MIT

Method for easier scaling of quantum computing devices developed

MIT computer scientist Aleksander Madry. Courtesy: Ian MacLellan, MIT

AI and Machine Learning

Doing machine learning the right way

Courtesy: Dishita Turakhia and Junyi Zhu, MIT

System Integration

Breadboards integrated onto physical products

Courtesy: Massachusetts Institute of Technology

Safety Standards

Cryptographic ID tag developed to stop supply chain counterfeiting

MIT researchers have created a “sensorized” skin, made with kirigami-inspired sensors, that gives soft robots greater awareness of the motion and position of their bodies. Courtesy: Ryan L. Truby, MIT CSAIL

Soft robotic arm uses flexible sensors to understand its position

Courtesy: Chris Vavra, CFE Media

Machine-learning tool predicts code’s speed on computer chips

An MIT-invented model demonstrates an understanding of some basic “intuitive physics” by registering “surprise” when objects in simulations move in unexpected ways, such as rolling behind a wall and not reappearing on the other side. Courtesy: Christine Daniloff, MIT

AI and Machine Learning

Helping machines perceive some laws of physics

Courtesy: CFE Media and Technology

Design and control robots with stretchy, flexible bodies

MIT and Toyota researchers have designed a new model that weighs various uncertainties and risks to help autonomous vehicles determine when it’s safe to merge into traffic at intersections with objects obstructing views, such as buildings blocking the line of sight. Courtesy: Massachusetts Institute of Technology

AI and Machine Learning

Model developed to help autonomous vehicles navigate traffic safely

A key to compiling the novel Omnipush dataset was building modular objects (pictured) that enabled the robotic system to capture a vast diversity of pushing behavior. The central pieces contain markers on their centers and points so a motion-detection system can detect their position within a millimeter. Courtesy: Massachusetts Institute of Technology (MIT)

Robots learn the fundamentals of object manipulation and pushing

A system designed by researchers at MIT and elsewhere enables interconnected smart devices to cooperatively pinpoint their positions in noisy environments where GPS usually fails, which is useful for emerging “localization-of-things” applications. Courtesy: Christine Daniloff, MIT

Industrial Networking

Location-aware system helps smart devices find their position

MIT researchers have fabricated a diamond-based quantum sensor on a silicon chip using traditional fabrication techniques (pictured), which could enable low-cost quantum hardware. Courtesy: Massachusetts Institute of Technology

Diamond-based quantum sensor fabricated on a silicon chip

MIT engineers have built a modern microprocessor from carbon nanotube field-effect transistors (pictured), which are seen as faster and greener than silicon transistors. The new approach uses the same fabrication processes used for silicon chips. Courtesy: Felice Frankel, MIT

Advanced microprocessor built out of carbon nanotubes

A battery-free underwater “piezoelectric” sensor invented by MIT researchers transmits data by absorbing or reflecting sound waves back to a receiver, where a reflected wave decodes a 1 bit and an absorbed wave decodes a 0 bit — and simultaneously stores energy. Courtesy: Massachusetts Institute of Technology

Process Instrumentation and Sensors

Battery-free sensor developed for underwater exploration

A new MIT-invented system automatically designs and 3-D prints complex robotic actuators optimized according to an enormous number of specifications, such as appearance and flexibility. To demonstrate the system, the researchers fabricated floating water lilies with petals equipped with arrays of actuators and hinges that fold up in response to magnetic fields run through conductive fluids. Courtesy: Subramanian Sundaram, MIT

Automated system generates robotic actuators

For years, researchers from MIT and Brown University have been developing an interactive system that lets users drag-and-drop and manipulate data on any touchscreen, including smartphones and interactive whiteboards. Now, they’ve included a tool that instantly and automatically generates machine-learning models to run prediction tasks on that data. Courtesy: Melanie Gonick, MIT

AI and Machine Learning

Drag-and-drop data analytics using machine learning