The age of big data has seen a host of newtechniques for analyzing large data sets. But before any of those techniques can be applied, the target data has to be aggregated, organized, and cleaned up.
That turns out to be a shockingly time-consuming task. In a 2016 survey, 80 data scientists told the company CrowdFlower that, on average, they spent 80 percent of their time collecting and organizing data and only 20 percent analyzing it.
This fall’s new FAA regulations have made drone flight easier than ever for both companies and consumers. But what if the drones out on the market aren’t exactly what you want?
A new system from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) is the first to allow users to design, simulate and build their own custom drone. Users can change the size, shape and structure of their drone based on the specific needs they have for payload, cost, flight time, battery usage and other factors.
MIT researchers and their colleagues have developed a new computational model of the human brain’s face-recognition mechanism that seems to capture aspects of human neurology that previous models have missed.
In a new collaborative initiative in autonomy and robotics, MIT and Lockheed Martin scientists will focus on innovations needed to enable generation-after-next autonomous systems. Improvements in human/machine teaming and navigation in complex environments are among the research challenges that Lockheed Martin is inviting MIT faculty and their students to help solve.
At the annual meeting of the Association for the Advancement of Artificial Intelligence last weekend, researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) presented a new way of modeling robot collaboration that reduces the need for communication by 60 percent. They believe that their model could make it easier to design systems that enable humans and robots to work together — in, for example, emergency-response teams.
Getting drones to fly around without hitting things is no small task. Obstacle-detection and motion-planning are two of computer science’s trickiest challenges because of the complexity involved in creating real-time flight plans that avoid obstacles and handle surprises like wind and weather. In a pair of projects announced this week, CSAIL researchers demonstrated software that allow drones to stop on a dime to make hairpin movements over, under, and around some 26 distinct obstacles in a simulated “forest.”
Coming to life in the 1970s with then-instructor Professor Emeritus Woodie Flowers at the lead, 2.007 was at the forefront of a revolution in engineering education, becoming one of the first hands-on classes to teach students not only how to design an object but also how to build it. Today, it’s a fun celebration of making that ends in an annual head-to-head robot competition on MechE’s Innovation Day in May.
Last Friday, MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) hosted 150 local high school students for its second annual “Hour of Code” event, tied to the international initiative focused on getting kids interested in programming.
NASA announced today that MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) is one of two university research groups nationwide that will receive a 6-foot, 290-pound humanoid robot to test and develop for future space missions to Mars and beyond.