Richard Socher on the future of deep learning

The O’Reilly Bots Podcast: Making neural networks more accessible. In this episode of the O’Reilly Bots Podcast , Pete Skomoroch and I talk with Richard Socher , chief scientist at Salesforce . He was previously the founder and CEO of MetaMind, a deep learning startup that Salesforce acquired in 2016. Socher also teaches the “ Deep Learning for Natural Language Processing ” course at Stanford University. Our conversation focuses on where deep learning and NLP are headed, and interesting current and near-future applications. Discussion points: Accessibility, in a couple of senses: making deep learning easier for computer scientists to implement, and making the power of deep learning available through intuitive applications AI-enabled question answering systems and dynamic co-attention networks The issue of interpretability, and progress in creating more interpretable models Why Socher believes that human-in-the-loop is the best solution for the current “fake news” controversy, the hottest topic in NLP now Why Quasi-Recurrent Neural Networks (QRNNs) are an advancement over Long Short Term Memory networks (LSTMs), the subject of a recent paper co-authored by Socher Other links: The Stanford Question Answering Dataset TensorFlow and Chainer , two frameworks for working with neural networks Summaries of recent papers by the Salesforce research team

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Richard Socher on the future of deep learning is an episode from O'Reilly Bots Podcast - O'Reilly Media Podcast by O'Reilly Media.

This episode is 00:57:46 long.

This episode was published on Dec 1, 2016.

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