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Epipolar Geometry to Improve Neural Rendering in Scene Representation

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To hear about Josh Tobin’s various projects in robot learning, check out the full interview! The discussion on projects outside of the NeurIPS paper picks up at 15:58 in the podcast. Enjoy! Robots have a particularly hard time with “reading a room.” In order to know how to act, they first need to understand their…

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Dex-Net and the Third Wave of Robot Learning

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Ken Goldberg is involved in several projects in collaboration with multiple organizations at UC Berkeley including some technology-based art projects. To hear about all of them, check out the recent TWIML AI Podcast interview, The Third Wave of Robotic Learning with Ken Goldberg.   Ever thought you had a good grip on your phone and…

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ViLBERT: Bridging Visual and Linguistic Inputs to Improve Interaction between Humans and Machines

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Stefan Lee is involved in a number of projects around emergent communication. To hear about more of them, in addition to the ViLBERT model, check out the full interview! TWiML Talk #358 with Stefan Lee. One of the major barriers keeping robots from full immersion in our daily lives, is the reality that meaningful human…

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COVID-19 Update from Team TWIML

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Hi everyone! Unless you’re Jared Leto, or a contestant on Big Brother Germany, you’ve undoubtedly seen your world shift dramatically over the last few weeks. For most of us, this is uncharted territory and unfortunately, we’re not quite able to see the finish line just yet. Now, more than ever before, is the time for…

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Upside Down Reinforcement Learning

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Jürgen and his research lab at IDSIA, are involved in a number of fascinating projects, to hear about their work beyond Upside-Down Reinforcement Learning, check out the full interview! [TWiML Talk #357 with Jüergen Schmidhuber].    Jürgen Schmidhuber is co-founder and chief scientist of NNAISENSE, scientific director at IDSIA (Swiss AI Lab), and professor of…

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SLIDE: The Algorithmic Alternative that Outperforms GPUs

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For more on the SLIDE algorithm check out the podcast that inspired this article—[TWIML AI Podcast #355 with Beidi Chen]. The conversation goes deeper into the team’s work on locality-sensitive hashing.   Graphics Processing Units (GPUs) have become the accepted industry standard for training deep learning models. While the raw compute power of GPUs has…

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Stabilizing Off-Policy Reinforcement Learning

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For more on the latest advancements in reinforcement learning, check out the podcast that inspired this article—[TWIML AI Podcast #355 with Sergey Levine]. In addition to discussing his team’s work on off-policy reinforcement learning, he also updates us on their efforts in model-based and causal RL. Typically, reinforcement learning involves an agent that interacts with…

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Managing Real-Life Data Science Projects with Metaflow

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Last November, Sam had the pleasure of sitting down for a conversation with Ville Tuulos, Manager of Machine Learning Infrastructure at Netflix. They spoke just hours after he announced the open-sourcing of their Python library, Metaflow. At the time, we’d planned to launch a new video series called TWIML Democasts as a way to walk…

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TWIML on TR’s Breakthrough Technologies

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TWIML takes a closer look at 10 “breakthrough technologies” as they relate to ML and AI, including drug development, cybersecurity, and more!

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AI Enterprise Workflow Study Group Recap

AI Enterprise Workflow Study Group Recap – Course 1

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Recently we kicked off a study group to work through the AI Enterprise Workflow sequence of courses created by IBM and on Coursera. Each of the courses in the six course series is two weeks long, and we just completed the second week of the first course. In this post we’ll recap some of the…

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