Rachel Metz reports for CNN that researchers at MIT and the Qatar Computing Research Institute have developed an AI system that can look at a picture of a pizza and determine which toppings should go on which layer. Postdoc Dimitrios Papadopoulos “believes this research could lead to non-food applications as well, such as a digital shopping assistant that uses AI to figure out how to put together a fashionable outfit,” writes Metz.
Prof. Markus Buehler speaks with Ira Flatow of Science Friday about his research, which attempts to better understand and create new proteins by translating them into music. Buehler explains that they were able to listen to proteins after discovering that “amino acids have a unique frequency spectrum which we could then make audible using a concept of transposition.”
A study co-authored by Prof. Cynthia Breazeal found that a “social robot” teddy bear “boosted spirits, eased anxiety and even lowered perceived pain levels” among Boston Children’s Hospital patients aged 3 to 10 years old, reports Robert Preidt for US News & World Report. “We want technology to support everyone who's invested in the quality care of a child," says Breazeal.
Researchers at MIT and Brown University created an interactive data system that “could give everyone AI superpowers,” writes Darrell Etherington for TechCrunch. Known as ‘Northstar,’ the system can instantly generate machine-learning models to use with existing data sets in order to generate useful predictions, explains Etherington.
In a new study, Prof. Markus Buehler converted 20 types of amino acids into a 20-tone scale to create musical compositions. “Those altered compositions were converted back into a conceptual amino acid chain, which enabled the team to generate variations of proteins that have never been seen in nature,” writes Becky Ferreira for Motherboard.
Paul Carter of BBC’s Click highlights CSAIL research to teach a robot how to feel an object just by looking at it. This will ultimately help the robot “grip better when lifting things like the handle of a mug,” says Carter.
Gizmodo reporter Victoria Song writes that MIT researchers have developed a new system that can teach a machine how to make pizza by examining a photograph. “The researchers set out to teach machines how to recognize different steps in cooking by dissecting images of pizza for individual ingredients,” Song explains.
Using a tactile sensor and web camera, MIT researchers developed an AI system that allows robots to predict what something feels like just by looking at it, reports David Williams for CNN. “This technology could be used to help robots figure out the best way to hold an object just by looking at it,” explains Williams.
Forbes contributor Charles Towers-Clark explores how CSAIL researchers have developed a database of tactile and visual information that could be used to allow robots to infer how different objects look and feel. “This breakthrough could lead to far more sensitive and practical robotic arms that could improve any number of delicate or mission-critical operations,” Towers-Clark writes.
MIT researchers have created a new system that enables robots to identify objects using tactile information, reports Darrell Etherington for TechCrunch. “This type of AI also could be used to help robots operate more efficiently and effectively in low-light environments without requiring advanced sensors,” Etherington explains.
Fast Company reporter Michael Grothaus writes that CSAIL researchers have developed a new system that allows robots to determine what objects look like by touching them. “The breakthrough could ultimately help robots become better at manipulating objects,” Grothaus explains.
TechCrunch reporter Darrell Etherington writes that MIT researchers have developed a system that can predict a perso's trajectory. The tool could allow “robots that typically freeze in the face of anything even vaguely resembling a person walking in their path to continue to operate and move around the flow of human foot traffic."
During a Times Higher Ed summit, Prof. Shigeru Miyagawa, senior associate dean for open learning, emphasized the importance of integrating attention to ethical implications into AI education, reports Paul Baskin. “My plan is to educate a new generation of young people who will have intuition behind computational thinking,” says Miyagawa.
Mashable highlights how MIT researchers have developed a new system of computationally simple robots inspired by biological cells that can connect in large groups to move around, transport objects and complete tasks. Mashable explains that robots made up of simplistic components, “could enable more scalable, flexible and robust systems.”
Motherboard reporter Rob Dozier writes about Glitch, an MIT startup that uses machine learning to design clothing. “These tools are meant to empower human designers,” explains graduate student Emily Salvador. “What I think is really cool about these creative-focused AI tools is that there’s still this really compelling need for a human to intervene with the algorithm.”