Beyond Bayes: Automating Human Reasoning

An ICML workshop focused on paths towards universal reasoning systems

One of the goals of AI research is the automation of reasoning. Advances is probabilistic modeling, causal inference, combined with the deep learning revolution, have brought us significantly closer to this outcome.

However, these advances have also exposed both gaps in our basic understanding of reasoning and challenges in making automated reasoning technologies flexible and composable.

With this problem in mind, I’m co-organizing a workshop called Beyond Bayes: Paths Towards Universal Reasoning Systems at ICML in July. This workshop aims to reinvigorate work on the grand challenge of developing a computational foundation for reasoning in minds, brains, and machines.

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Job Announcement: PennFoster is looking for a senior data scientist.

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We’ve just extended the deadline to Tuesday June 7th. If you are writing papers and have interesting ideas in topics ranging from neuroscience, cognitive science, Bayesian and causal inference, machine learning, logic, programming languages, or theorem proving, I’d encourage you to submit!