Matt McMarland writes for The Washington Post that a CSAIL researcher has developed a computer system that can produce tweets that read like they are written by presidential candidate Donald Trump. McFarland explains that postdoc Brad Hayes “wanted a fun way to familiarize himself with some statistical modeling techniques for his research on human and robot interactions.”
Popular Science reporter Dave Gershgorn writes that postdoc Bradley Hayes has created an algorithm that tweets fragments of Donald Trump’s speeches. Gershgorn explains that, “the algorithm works by selecting a random letter, and then predicting what letter would normally come next, based on the original text.”
In a Forbes piece about historical technology developments that occurred during the week of February 22nd, Gil Press highlights how Prof. Emeritus Jay Forrester received a patent on Feb. 28, 1956 for magnetic core memory. Forrester’s invention “became the standard for computer memory until it was supplanted by solid state RAM in the mid-seventies.”
Wired reporter Emily Reynolds writes that researchers from MIT CSAIL have developed a new communication system that is designed to help humans and robots work together in emergency situations. The new system reduces the needs for communication by 60 percent, reducing the potential for information overload.
Boston.com reporter Hilary Sargent writes that MIT researchers have developed a new device that could help guide the visually impaired. Sargent explains that a prototype system the researchers developed “is about the size of a binoculars case and is designed to be worn around someone’s neck.”
Nidhi Subbaraman writes for BetaBoston about “Cambridge 2 Cambridge,” an international cybersecurity challenge that will take place this spring between researchers from MIT CSAIL and the University of Cambridge. Prof. Howard Shrobe explained that the contest will take the form of a virtual “capture the flag” contest.
Prof. Edward Boyden speaks with Boston Globe reporter Murray Carpenter about how scientists need more powerful computers to help gain a better understanding of brain function. “The cool part of neuroengineering is that we have all these unmet needs,” Boyden says. “I think there is an enormous amount of hope generated by bringing new tools into neuroscience.”
Wall Street Journal reporter Alexandra Wolfe profiles Prof. Cynthia Breazeal and examines her latest work developing a robot, dubbed Jibo, that can assist humans with daily tasks and serve as a companion. “I’m really thinking about social robots as an extender of our human capacity,” Breazeal explains.
Boston Magazine reporter Kyle Clauss reports that researchers from MIT CSAIL have developed a drone that uses algorithms to detect obstacle-free regions in space. “Using free-space segments is a more ‘glass-half-full’ approach that works far better for drones in small, cluttered spaces,” says MIT alumnus Benoit Landry.
Researchers from MIT CSAIL have developed an algorithm that allows drones to navigate obstacle courses, reports Kelsey Atherton for Popular Science. “As drones move away from simple remote-controlled toys and become more autonomous flying tools, programs like these will keep them flying safely through unfamiliar terrain,” explains Atherton.
MIT researchers have developed an algorithm that could reduce how long planes wait before takeoff, reports Lee Moran for The Huffington Post. The formula allows air traffic controllers to use data on weather conditions and runway traffic to “hold airplanes at the gate, which would help avoid congestion.”
Cade Metz writes for Wired that MIT researchers have developed a system that allows robots to predict how objects will move. Postdoc Ilker Yildirim explains that in order for a robot to be able to assist with household tasks like washing the dishes, it must “deeply understand its physical environments.”
Boston Magazine reporter Madeline Bilis writes about the Reality Editor, an application developed by researchers from the MIT Media Lab. “Users can ‘edit reality’ by drawing virtual lines to and from objects with their smartphone’s camera to alter their uses and capabilities,” Bilis explains.
MIT computer scientists have developed a program that can predict how objects will move with the same accuracy as humans, reports Mary Beth Griggs for Popular Science. The researchers hope to eventually be able to program the system to “make predictions in the natural world even faster than we can.”
An AI system created by MIT researchers can predict how physical objects move through the world with human-like accuracy, reports Curt Woodward for BetaBoston. “Where humans learn to make such judgments intuitively, we essentially had to teach the system each of these properties,” explains postdoc Ilker Yildirim.