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by   -   December 15, 2017
As part of an investigation into the nature of humans’ physical intuitions, MIT researchers trained a neural network to predict how unstably stacked blocks would respond to the force of gravity.
Image: Christine Daniloff/MIT

Josh Tenenbaum, a professor of brain and cognitive sciences at MIT, directs research on the development of intelligence at the Center for Brains, Minds, and Machines, a multiuniversity, multidisciplinary project based at MIT that seeks to explain and replicate human intelligence.

by   -   December 11, 2017
Neural nets are so named because they roughly approximate the structure of the human brain. Typically, they’re arranged into layers, and each layer consists of many simple processing units — nodes — each of which is connected to several nodes in the layers above and below. Data is fed into the lowest layer, whose nodes process it and pass it to the next layer. The connections between layers have different “weights,” which determine how much the output of any one node figures into the calculation performed by the next.
Image: Chelsea Turner/MIT

By Larry Hardesty

Neural networks, which learn to perform computational tasks by analyzing huge sets of training data, have been responsible for the most impressive recent advances in artificial intelligence, including speech-recognition and automatic-translation systems.

by   -   October 28, 2017

Just in time for Halloween, a research team from the MIT Media Lab’s Scalable Cooperation group has introduced Shelley: the world’s first artificial intelligence-human horror story collaboration.

by   -   October 12, 2017

by Rachel Gordon
Consisting of a headset and hand controllers, CSAIL’s new VR system enables users to teleoperate a robot using an Oculus Rift headset.
Photo: Jason Dorfman/MIT CSAIL

Certain industries have traditionally not had the luxury of telecommuting. Many manufacturing jobs, for example, require a physical presence to operate machinery.

by   -   September 27, 2017
Dubbed “Primer,” a new cube-shaped robot can be controlled via magnets to make it walk, roll, sail, and glide. It carries out these actions by wearing different exoskeletons, which start out as sheets of plastic that fold into specific shapes when heated. After Primer finishes its task, it can shed its “skin” by immersing itself in water, which dissolves the exoskeleton. Credit: the researchers.

From butterflies that sprout wings to hermit crabs that switch their shells, many animals must adapt their exterior features in order to survive. While humans don’t undergo that kind of metamorphosis, we often try to create functional objects that are similarly adaptive — including our robots.

by   -   September 20, 2017

“CodeCarbonCopy enables one of the holy grails of software engineering: automatic code reuse,” says Stelios Sidiroglou-Douskos, a research scientist at CSAIL. Credit: MIT News

by Larry Hardesty

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a new system that allows programmers to transplant code from one program into another. The programmer can select the code from one program and an insertion point in a second program, and the system will automatically make modifications necessary — such as changing variable names — to integrate the code into its new context.

by   -   September 13, 2017

A new method produces a printable structure that begins to fold itself up as soon as it’s peeled off the printing platform. Credit: MIT
by Larry Hardesty

As 3-D printing has become a mainstream technology, industry and academic researchers have been investigating printable structures that will fold themselves into useful three-dimensional shapes when heated or immersed in water.

by   -   September 12, 2017

An image of some connected autonomous cars

by Peter Dizikes

This summer, a survey released by the American Automobile Association showed that 78 percent of Americans feared riding in a self-driving car, with just 19 percent trusting the technology. What might it take to alter public opinion on the issue? Iyad Rahwan, the AT&T Career Development Professor in the MIT Media Lab, has studied the issue at length, and, along with Jean-Francois Bonnefon of the Toulouse School of Economics and Azim Shariff of the University of California at Irvine, has authored a new commentary on the subject, titled, “Psychological roadblocks to the adoption of self-driving vehicles,” published today in Nature Human Behavior. Rahwan spoke to MIT News about the hurdles automakers face if they want greater public buy-in for autonomous vehicles.  

by   -   September 8, 2017
MIT President L. Rafael Reif, left, and John Kelly III, IBM senior vice president, Cognitive Solutions and Research, shake hands at the conclusion of a signing ceremony establishing the new MIT–IBM Watson AI Lab. Credit: Jake Belcher

IBM and MIT today announced that IBM plans to make a 10-year, $240 million investment to create the MIT–IBM Watson AI Lab in partnership with MIT. The lab will carry out fundamental artificial intelligence (AI) research and seek to propel scientific breakthroughs that unlock the potential of AI. The collaboration aims to advance AI hardware, software, and algorithms related to deep learning and other areas; increase AI’s impact on industries, such as health care and cybersecurity; and explore the economic and ethical implications of AI on society. IBM’s $240 million investment in the lab will support research by IBM and MIT scientists.

by   -   September 5, 2017
“The concept of my startup is, ‘Let’s use hacker tools to defeat hackers,’” PhD student Gregory Falco says. “If you don’t know how to break it, you don’t know how to fix it.”
Photo: Ian MacLellan

by Dara Farhadi

While working for the global management consulting company Accenture, Gregory Falco discovered just how vulnerable the technologies underlying smart cities and the “internet of things” — everyday devices that are connected to the internet or a network — are to cyberterrorism attacks.

by   -   September 4, 2017

MIT engineers have devised a way to automate the process of monitoring neurons in a living brain using a computer algorithm that analyzes microscope images and guides a robotic arm to the target cell. In this image, a pipette guided by a robotic arm approaches a neuron identified with a fluorescent stain.
Credit: Ho-Jun Suk

by Anne Trafton

Recording electrical signals from inside a neuron in the living brain can reveal a great deal of information about that neuron’s function and how it coordinates with other cells in the brain. However, performing this kind of recording is extremely difficult, so only a handful of neuroscience labs around the world do it.

by   -   September 1, 2017
ComText allows robots to understand contextual commands such as, “Pick up the box I put down.”
Photo: Tom Buehler/MIT CSAIL

by Adam Conner-Simons & Rachel Gordon

Despite what you might see in movies, today’s robots are still very limited in what they can do. They can be great for many repetitive tasks, but their inability to understand the nuances of human language makes them mostly useless for more complicated requests.

by   -   August 30, 2017

by Jennifer Chu
Engineers at MIT have designed an autonomous robot with “socially aware navigation,” that can keep pace with foot traffic while observing these general codes of pedestrian conduct.
Credit: MIT

Just as drivers observe the rules of the road, most pedestrians follow certain social codes when navigating a hallway or a crowded thoroughfare: Keep to the right, pass on the left, maintain a respectable berth, and be ready to weave or change course to avoid oncoming obstacles while keeping up a steady walking pace.

by   -   August 24, 2017
Interactive Robogami enables the fabrication of a wide range of robot designs. Photo: MIT CSAIL

Even as robots become increasingly common, they remain incredibly difficult to make. From designing and modeling to fabricating and testing, the process is slow and costly: Even one small change can mean days or weeks of rethinking and revising important hardware.

by   -   August 22, 2017
Credit: Shutterstock / MIT

Doctors are often deluged by signals from charts, test results, and other metrics to keep track of. It can be difficult to integrate and monitor all of these data for multiple patients while making real-time treatment decisions, especially when data is documented inconsistently across hospitals.