Rise of the Machines: Survey of AI Researchers

These predictions are from a recent survey of AI/ML researchers. See SSC and also here for more discussion of the results. When Will AI Exceed Human Performance? Evidence from AI Experts Katja Grace, John Salvatier, Allan Dafoe, Baobao Zhang, Owain Evans Advances in artificial intelligence (AI) will transform modern life by reshaping transportation, health, science, …

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Epistemic Caution and Climate Change

I have not, until recently, invested significant time in trying to understand climate modeling. These notes are primarily for my own use, however I welcome comments from readers who have studied this issue in more depth. I take a dim view of people who express strong opinions about complex phenomena without having understood the underlying …

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History of Bayesian Neural Networks

This talk gives the history of neural networks in the framework of Bayesian inference. Deep learning is (so far) quite empirical in nature: things work, but we lack a good theoretical framework for understanding why or even how. The Bayesian approach offers some progress in these directions, and also toward quantifying prediction uncertainty. I was …

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Neural Networks and Deep Learning 2

Inspired by the topics discussed in this earlier post, I’ve been reading Michael Nielsen’s online book on neural nets and deep learning. I particularly liked the subsection quoted below. For people who think deep learning is anything close to a solved problem, or anticipate a near term, quick take-off to the Singularity, I suggest they …

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Neural Networks and Deep Learning

One of the SCI FOO sessions I enjoyed the most this year was a discussion of deep learning by AI researcher Juergen Schmidhuber. For an overview of recent progress, see this recent paper. Also of interest: Michael Nielsen’s pedagogical book project. An application which especially caught my attention is described by Schmidhuber here: Many traditional methods …

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