A team of MIT analysis 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 on the Programming Language Design and Implementation conference this week, the researchers describe a novel probabilistic-programming system named “Gen.” Customers write fashions and algorithms from multiple fields where AI methods are applied — such as pc vision, robotics, and statistics — without having to deal with equations or manually write high-performance code. Gen additionally lets professional researchers write refined models and inference algorithms — used for prediction duties — that were previously infeasible.
Peter Norvig, director of analysis at Google, who additionally was not concerned on this analysis, praised the work as well. “[Gen] permits an issue-solver to make use of probabilistic programming, and thus have a more principled method to the issue, however not be restricted by the choices made by the designers of the probabilistic programming system,” he says. “General-purpose programming languages. have been successful because they make the job easier for a programmer, but additionally, make it potential for a program to create something brand new to solve a brand new problem efficiently. Gen does the identical for probabilistic programming.”
Gen’s source code is openly available and is being presented at future open-source developer gatherings, including Unusual Loop and JuliaCon. The work is supported, in part, by DARPA.