Uber AI Labs is releasing its probabilistic programming language, Pyro, into open source this week. Pyro is part of Uber’s larger plan to provide reliable transportation by matching riders to drivers, suggesting routes, finding carpool combinations, and designing next generation vehicles.
“To solve these challenges, we are combining state-of-the-art artificial intelligence (AI) techniques with the rich expertise of data scientists, engineers, and other users. We are exploring a tool-first approach that will enable us and others to make the next generation of AI solutions,” Noah Goodman, researcher at Uber AI Labs, wrote in a post.
Pyro is used for deep probabilistic modeling, and combines modern deep learning with Bayesian modeling. “The goal of Pyro is to accelerate research and applications of these techniques, and to make them more accessible to the broader AI community,” wrote Goodman.
The language is written in Python and supported by PyTorch, a Python deep learning framework. The current version of Pyro (alpha) can represent any computable probability distribution, scale to large data sets, implement with composable abstractions, and provides automation and control, according to the Pyro team.
Goodman explains probabilistic modeling is necessary to “correctly capture uncertainty in models and predictions for unsupervised and semi-supervised learning, and to provide AI systems with declarative prior knowledge.”
The team hopes the open sourcing of Pyro will encourage the scientific community to collaborate on AI tools that are easy-to-use, flexible and open.
Going forward, Pyro will be updated with improved abstractions for rapid modeling, and additional objects and techniques for estimating gradient expectations.
“Longer term, we hope that the main directions of Pyro development will be driven by applications and the priorities of the emerging Pyro community
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