Thursday night, dozens of robots designed and built by undergraduates in a mechanical engineering class endured hours of intense, boisterous, and often jubilant competition as they scrambled to rack up points in one-on-one clashes on special “Star Wars”-themed playing arenas.
From self-driving cars to the internet of things, artificial intelligence (AI) has reached new levels of sophistication in recent years. With that in mind, this week MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) launched an industry collaboration focused on using machine learning to create functional human-like systems.
In the latest issue of the journal Autonomous Robots, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory and their colleagues present a new technique for preventing malicious hackers from commandeering robot teams’ communication networks. The technique could provide an added layer of security in systems that encrypt communications, or an alternative in circumstances in which encryption is impractical.
For robots to do what we want, they need to understand us. Too often, this means having to meet them halfway: teaching them the intricacies of human language, for example, or giving them explicit commands for very specific tasks. But what if we could develop robots that were a more natural extension of us and that could actually do whatever we are thinking?
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.