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Control-Data Separation and Logical Condition Propagation for Efficient Inference on Probabilistic Programs

arXiv.org Artificial Intelligence

In the recent rise of statistical machine learning, probabilistic programming languages are attracting a lot attention as a programming infrastructure for data processing tasks. Probabilistic programming frameworks allow users to express statistical models as programs, and offer a variety of methods for analyzing the models. Probabilistic programs feature randomization and conditioning. Randomization can take different forms, such as probabilistic branching (ifp in Program 1) and random assignment from a probability distribution (denoted by, see Program 2).


Rebel AI group raises record cash after machine learning schism

#artificialintelligence

A breakaway group of artificial intelligence researchers has raised a record first round of financing for a new start-up involved in general-purpose AI,ย โ€ฆ


The Musk/Zuckerberg Dustup Represents a Growing Schism in AI

#artificialintelligence

Frank White is the author of The Overview Effect: Space Exploration and Human Evolution. He is working on a book about artificial intelligence. Recently, two tech heavyweights stepped into the social media ring and threw a couple of haymakers at one another. The topic: artificial intelligence (AI) and whether it is a boon to humanity or an existential threat. Elon Musk, founder and CEO of SpaceX and Tesla, has been warning of the dangers posed by AI for some time and called for its regulation at a conference of state governors in July.