New AI Programming Language Goes Beyond Deep Learning

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According to a recent press release, “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.”

The release goes on, “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.”

It adds, “Due to its simplicity — and, in some use cases, automation — the researchers say Gen can be used easily by anyone, from novices to experts. ‘One motivation of this work is to make automated AI more accessible to people with less expertise in computer science or math,’ says first author Marco Cusumano-Towner, a PhD student in the Department of Electrical Engineering and Computer Science. ‘We also want to increase productivity, which means making it easier for experts to rapidly iterate and prototype their AI systems’.”


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