General-purpose language works for computer vision, robotics, statistics, and more.
Users feed Gen relatively short code defining a target task, and the system automatically generates the results.
Image: Chelsea Turner, MIT
A team of MIT researchers is making it easier for novices to get their feet wet with artificial intelligence, while also helping experts advance the field.
In a paper presented at the Programming Language Design and Implementation conference this week, the researchers describe a novel probabilistic-programming system named "Gen." Users write models and algorithms from multiple fields where AI techniques are applied - such as computer vision, robotics, and statistics - without having to deal with equations or manually write high-performance code. Gen also lets expert researchers write sophisticated models and inference algorithms - used for prediction tasks - that were previously infeasible.
In their paper, for instance, the researchers demonstrate that a short Gen program can infer 3-D body poses, a difficult computer-vision inference task that has applications in autonomous systems, human-machine interactions, and augmented reality. Behind the scenes, this program includes components that perform graphics rendering, deep-learning, and types of probability simulations. The combination of these diverse techniques leads to better accuracy and speed on this task than earlier systems developed by some of the researchers.
