Talking Machines

In episode nine of season three we chat about the difference between models and algorithms, take a listener question about summer schools and learning in person as opposed to learning digitally, and we chat with John Quinn of the United Nations Global Pulse lab in Kampala, Uganda and Makerere University's Artificial Intelligence Research group.See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode eight of season three we return to the epic (or maybe not so epic) clash between frequentists and bayesians, take a listener question about the ethical questions generators of machine learning should be asking of themselves (not just their tools) and we hear a conversation with Ernest Mwebaze of Makerere University. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode seven of season three we take a minute to break way from our regular format and feature a conversation with Dina Machuve of the Nelson Mandela African Institute of Science and Technology we cover everything from her work to how cell phone access has changed data patterns. We got to talk with her at the Data Science Africa confrence and workshop.See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode six of season three we chat about the difference between frequentists and Bayesians, take a listener question about techniques for panel data, and have an interview with Katherine Heller of Duke See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode five of season three we compare and contrast AI and data science, take a listener question about getting started in machine learning, and listen to an interview with Joaquin Quiñonero Candela. For a great place to get started with foundational ideas in ML, take a look at Andrew Ng’s course on Coursera. Then check out Daphne Kohler’s course. Talking Machines is now working with Midroll to source and organize sponsors for our show. In order find sponsors who are a good fit for us, and of worth to you, we’re surveying our listeners. If you’d like to help us get a better idea of who makes up the Talking Machines community take the survey at http://podsurvey.com/MACHINES. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode four of season three Neil introduces us to the ideas behind the bias variance dilemma (and how how we can think about it in our daily lives). Plus, we answer a listener question about how to make sure your neural networks don't get fooled. Our guest for this episode is Jeff Dean,  Google Senior Fellow in the Research Group, where he leads the Google Brain project. We talk about a closet full of robot arms (the arm farm!), image recognition for diabetic retinopathy, and equality in data and the community.  Fun Fact: Geoff Hinton’s distant relative invented the word tesseract. (How cool is that. Seriously.) See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In this episode three of season three of Talking Machines we dive into overfitting, take a listener question about unbalanced data and talk with Professor (Emeritus) Tom Dietterich from Oregon State University.See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode two of season three Neil takes us through the basics on dropout, we chat about the definition of inference (It's more about context than you think!) and hear an interview with Jennifer Chayes of Microsoft.See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

Talking Machines is entering its third season and going through some changes. Our founding host Ryan is moving on and in his place Neil Lawrence of Amazon is taking over as co host. We say thank you and good bye to Ryan with an interview about his work.See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode seventeen of season two we get an introduction to Min Hashing, talk with Frank Wood the creator of ANGLICAN, about probabilistic programming and his new company, INVREA, and take a listener question about how to choose an architecture when using a neural network.See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode sixteen of season two, we get an introduction to Restricted Boltzmann Machines, we take a listener question about tuning hyperparameters,  plus we talk with Eric Lander of the Broad Institute.See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode fifteen of season two, we talk about Hamiltonian Monte Carlo, we take a listener question about unbalanced data, plus we talk with Doug Eck of Google’s Magenta project.See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode fourteen of season two, we talk about Perturb-and-MAP, we take a listener question about classic artificial intelligence ideas being used in modern machine learning, plus we talk with Jake Abernethy of the University of Michigan about municipal data and his work on the Flint water crisis.See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode thirteen of season two, we talk about t-Distributed Stochastic Neighbor Embedding (t-SNE) we take a listener question about statistical physics, plus we talk with Hal Daume of the University of Maryland. (who is a great follow on Twitter.)See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode twelve of season two, we talk about generative adversarial networks, we take a listener question about using machine learning to improve or create products, plus we talk with Iain Murray of the University of Edinburgh.See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode eleven of season two, we talk about the machine learning toolkit  Spark, we take a listener question about the differences between NIPS and ICML conferences, plus we talk with Sinead Williamson of The University of Texas at Austin.See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode ten of season two, we talk about Computational Learning Theory and Probably Approximately Correct Learning originated by Professor Leslie Valiant of SEAS at Harvard, we take a listener question about generative systems, plus we talk with Aviv Regev, Chair of the Faculty and Director of the Klarman Cell Observatory and the Cell Circuits Program at the Broad Institute.See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

In episode nine of season two, we talk about sparse coding, take a listener question about the next big demonstration for AI after AlphaGo. Plus we talk with Clement Farabet about MADBITS and the work he’s doing at Twitter Cortex.See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

Recently Professor David MacKay passed away. We’ll spend this episode talking about his extensive body of work and its impacts. We’ll also talk with Philipp Hennig, a research group leader at the Max Planck Institute for Intelligent Systems, who trained in Professor MacKay’s group (with Ryan).See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

Episode seven of season two is a little different than our usual episodes, Ryan and Katherine just returned from a conference where they got to talk with Neil Lawrence of the University of Sheffield about some of the larger issues surrounding machine learning and society. They discuss anthropomorphic intelligence, data ownership, and the ability to empathize. The entire episode is given over to this conversation in hopes that it will spur more discussion of these important issues as the field continues to grow.See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.