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BBC Click reports on an AI system developed by CSAIL researchers that simplifies image editing. “Instead of requiring the user to select the pixels very accurately, our system can just detect it and give the opacities for every object in the image automatically, which can then be used for editing the images in a realistic way,” explains visiting researcher Yagiz Aksoy.
CSAIL researchers have created a system that allows robots to see and pick up objects they have never encountered without assistance from humans, writes Jason Murdock for Newsweek. The researchers are now working on teaching the system to “move objects with a specific goal in mind, such as cleaning a desk,” reports Murdock.
MIT researchers have developed a model that can help detect depression by analyzing an individual’s speech patterns, reports Kaveh Waddell for Axios. Waddell explains that the researchers, “trained an AI system using 142 recorded conversations to assess whether a person is depressed and, if so, how severely.”
CSAIL researchers have developed a new system that gives robots a greater visual understanding of the world around them, reports Heather Kelly for CNN. “We want robots to learn by themselves how to very richly and visually understand lots of objects that are useful for lots of tasks,” explains graduate student Pete Florence.
Wired reporter Matt Simon writes that MIT researchers have developed a new system that allows robots to be able to visually inspect and then pick up new objects, all without human guidance. Graduate student Lucas Manuelli explains that the system is “all about letting the robot supervise itself, rather than humans going in and doing annotations.”
MIT researchers have developed a new system that can detect depression by examining a patient’s speech and writing, reports John Biggs for TechCrunch. Biggs writes that the system could “help real therapists find and isolate issues automatically versus the long process of analysis. It’s a fascinating step forward in mental health.”
Quanta Magazine reporter Natalie Wolchover spotlights how the work of Profs. William Freeman, Antonio Torralba and Ramesh Raskar is shedding light on how visual signals can be used to uncover information on hidden objects. Freeman explains that he is thrilled by the idea that “the world is rich with lots of things yet to be discovered.”
TechRepublic reporter Nick Heath writes about Julia 1.0, a programming language created by MIT researchers. “The breadth of Julia's capabilities and ability to spread workloads across hundreds of thousands of processing cores have led to its use for everything from machine learning to large-scale supercomputer simulation,” writes Heath.
Fast Company reporter Mark Wilson writes that MIT researchers have developed a new tool for computer-aided drafting software that can optimize the design for any product. Wilson explains that the tool could “help designers optimize their existing processes–and, crucially, deconstruct what works and what doesn’t, sooner.”
CSAIL Postdoc Gregory Falco writes in the San Francisco Chronicle about the importance of cybersecurity for satellites that interact with cars, televisions, and the internet. With new technological advancements like CubeSats, “we need to understand more about the legacy infrastructure on which these new technologies rely,” Falco concludes.
Engadget reporter Jon Fingas writes that MIT researchers have developed an encryption method that can secure sensitive data in neural networks without slowing machine learning systems. The method, notes Fingas, could “lead to more uses of internet-based neural networks for handling vital info, rather than forcing companies and institutions to either build expensive local equivalents or forget AI-based systems altogether.”
In an article for Popular Mechanics, Tiana Cline spotlights SoFi, an autonomous, soft, robotic fish that can swim alongside real fish. “SoFi has the potential to be a new type of tool for ocean exploration and to open up new avenues for uncovering the mysteries of marine life,” Cline notes.
In an article for Forbes about how AI could improve healthcare, Bernard Marr highlights an algorithm developed by MIT researchers that can analyze 3-D scans up to 1,000 times faster than is currently possible. “When saving minutes can mean saving lives, AI and machine learning can be transformative,” writes Marr.
New Scientist reporter Chelsea Whyte spotlights Prof. Regina Barzilay’s quest to revolutionize cancer treatment by applying AI techniques in ways that could help doctors detect cancer earlier. Barzilay explains that she is committed to, "applying the best technologies available to what we care about the most – our health.”
Kate Baggaley writes for NBC News that movement tracking technology developed by MIT researchers can be helpful for monitoring the elderly or sick. The system could be used to monitor an elderly relative and, “receive an instant alert if he or she falls,” or a doctor could use it to monitor the progression of a patient’s disease, explains Baggaley.