Los Angeles Times reporter Amina Khan writes that researchers have developed a program that learns to recognize and draw handwritten characters based off a few examples. Prof. Joshua Tenenbaum explains that the system, “can learn a large class of visual concepts in ways that are hard to distinguish from human learners.”
Hilary Brueck writes for Fortune that researchers from MIT, NYU and the University of Toronto have developed a new technique that allows machines to learn in a more human-like manner. The new technique “comes one step closer to getting machines to learn new things in a one-shot manner, more like humans do.”
Researchers have developed a learning program that can recognize handwritten characters after seeing only a few examples, reports Emily Chung for CBC News. The program “could lead to computers that are much better at speech recognition — especially recognizing uncommon words — or classifying objects and behaviour for businesses or the military.”
In a piece for Wired, Robert McMillan examines new MIT research showing that computers “powered by the latest ‘deep learning’ algorithms,” are catching up in tests that compare their intelligence to those of monkeys.
In a piece for New Scientist about teaching robots to communicate like humans, Aviva Rutkin highlights how researchers from MIT developed a new approach to communicating with a robot called inverse semantics. Using this approach, “the robot tries to choose the right words by looking at its environment,” Rutkin writes.