• At the Computer Vision and Pattern Recognition conference in June, MIT researchers will demonstrate that on some standard computer-vision tasks, short programs—less than 50 lines long—written in a probabilistic programming language are competitive with conventional systems with thousands of lines of code.
  • In a probabilistic programming language, the heavy lifting is done by the inference algorithm—the algorithm that continuously readjusts probabilities on the basis of new pieces of training data.
  • The whole hope is to write very flexible models, both generative and discriminative models, as short probabilistic code, and then not do anything else. General-purpose inference schemes solve the problems.

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