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Talking Machines - all episodes

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These are magic links to individual episodes for Talking Machines, provided to help you share episode links for this podcast that work on any device. This page is in the order of the RSS feed.

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Gods and Robots
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Sep 9 2021
Responsibility, Risk, and Publishing
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Aug 19 2021
ICML 2021: Test of Time(ly) Award
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Jul 24 2021
Learning with Less, Invisible Labor and Combating Anti-Blackness S7/E1
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Jul 9 2021
Let's Reflect
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Jun 13 2020
Predicting Floods and Really Doing Good S6/E9
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May 29 2020
ICLR: accessible, inclusive, virtual S6/E8
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May 14 2020
Humans in the Loop and Outside of the Classroom S6/E7
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May 1 2020
The Evolution of ML and Furry Little Animals S6/E6
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Apr 16 2020
Talking Machines Live and Understanding Modeling Viruses S6/E5
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Apr 3 2020
Prioritizing Problems and 100 episodes S6/E4
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Mar 20 2020
The Great AI Fallacy S6/E3
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Mar 5 2020
If a Machine Could Predict Your Death, Should it? S6/E2
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Feb 20 2020
Predicting the Decade and Distributing Conferences S6/E1
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Feb 6 2020
Debating Project Debater and Hello NeurIPS S5/E23
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Nov 21 2019
De-Enchanting AI with the Law S5/E22
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Nov 7 2019
How to Ask an Actionable Question S5/E21
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Oct 25 2019
Children are the Future and Ada Lovelace Day S5/E20
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Oct 10 2019
News from Neil and Updates from DALI S5/E19
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Sep 26 2019
A Cooperative Path to Artificial Intelligence S5/E18
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Sep 13 2019
What Does Red Sound Like S5/E17
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Aug 30 2019
Not What But Why S5/E16
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Aug 15 2019
Idea Pandemics and Workshop Walkthrough S5/E15
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Aug 1 2019
PosterSession.ai and Deep Quaggles S5/E14
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Jul 18 2019
The View from Addis Ababa S5/E13
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Jul 4 2019
DSA Addis Ababa and ICML Los Angeles S5/E12
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Jun 21 2019
Data Trusts and Citation Trends S5/E11
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Jun 6 2019
Reproducibly and Revisiting History S5/E10
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May 23 2019
Insights from AISTATS S5/E9
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May 10 2019
The Deep End of Deep Learning S5/E8
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Apr 25 2019
Exploring MARS and Getting back to Bayesics S5/E7
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Apr 11 2019
The Sweetness of a Bitter Lesson and Bringing ML and Healthcare Closer S5/E6
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Mar 28 2019
Slowed Down Conferences and Even More Summer Schools S5/E5
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Mar 14 2019
Jupyter Notebooks and Modern Model Distribution S5/E4
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Feb 28 2019
Real World Real Time and Five Papers for Mike Tipping S5/E3
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Feb 15 2019
The Bezos Paradox and Machine Learning Languages S5/E2
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Feb 1 2019
Being Global Bit by Bit S5/E1
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Jan 17 2019
The Possibility Of Explanation and The End of Season Four S4/E22
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Nov 29 2018
Neural Information Processing Systems and Distributed Internal Intelligence Systems S4/E21
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Nov 16 2018
Data Driven Ideas and Actionable Privacy S4/E20
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Nov 1 2018
AI for Good and The Real World S4/E19
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Oct 18 2018
Systems Design and Tools for Transparency S4/E18
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Oct 5 2018
How to Research in Hype and CIFAR's Strategy S4/E17
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Sep 20 2018
Troubling Trends and Climbing Mountains S4/E16
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Sep 7 2018
Gaussian Processes, Grad School, and Richard Zemel S4/E15
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Aug 23 2018
Long Term Fairness S4/E14
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Aug 9 2018
Simulated Learning and Real World Ethics S4/E13
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Jul 27 2018
ICML 2018 with Jennifer Dy S4/E12
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Jul 12 2018
Aspirational Asimov and How to Survive a Conference S4/E11
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Jun 28 2018
Explanations and Reviews S4/E10
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Jun 14 2018
Statements on Statements S4/E9
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May 31 2018
The Futility of Artificial Carpenters and Further Reading S4/E8
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May 17 2018
Economies, Work and AI S4/E7
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May 3 2018
Explainability and the Inexplicable S4/E6
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Apr 19 2018
Good Data Practice Rules S4/E5
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Apr 5 2018
Can an AI Practitioner Fix a Radio? S4/E4
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Mar 22 2018
Natural vs Artificial Intelligence and Doing Unexpected Work S4/E3
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Mar 8 2018
Scientific Rigor and Turning Information into Action S4/E2
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Feb 22 2018
Code Review for Community Change S4/E1
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Feb 8 2018
The Pace of Change and The Public View of ML E10
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Oct 5 2017
The Long View and Learning in Person E9
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Sep 21 2017
Machine Learning in the Field and Bayesian Baked Goods
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Sep 8 2017
Data Science Africa with Dina Machuve
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Aug 10 2017
The Church of Bayes and Collecting Data
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Jul 28 2017
Getting a Start in ML and Applied AI at Facebook
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Jul 13 2017
Bias Variance Dilemma for Humans and the Arm Farm
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Jun 29 2017
Overfitting and Asking Ecological Questions with ML
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Jun 15 2017
Graphons and "Inferencing"
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May 25 2017
Hosts of Talking Machines: Neil Lawrence and Ryan Adams
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Apr 27 2017
ANGLICAN and Probabilistic Programming
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Sep 1 2016
Eric Lander and Restricted Boltzmann Machines
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Aug 18 2016
Generative Art and Hamiltonian Monte Carlo
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Aug 4 2016
Perturb-and-MAP and Machine Learning in the Flint Water Crisis
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Jul 21 2016
Automatic Translation and t-SNE
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Jul 7 2016
Fantasizing Cats and Data Numbers
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Jun 16 2016
Spark and ICML
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Jun 2 2016
Computational Learning Theory and Machine Learning for Understanding Cells
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May 19 2016
Sparse Coding and MADBITS
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May 5 2016
Remembering David MacKay
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Apr 21 2016
Machine Learning and Society
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Apr 8 2016
Software and Statistics for Machine Learning
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Mar 24 2016
Machine Learning in Healthcare and The AlphaGo Matches
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Mar 10 2016
AI Safety and The Legacy of Bletchley Park
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Feb 25 2016
Robotics and Machine Learning Music Videos
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Feb 11 2016
OpenAI and Gaussian Processes
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Jan 28 2016
Real Human Actions and Women in Machine Learning
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Jan 14 2016
Open Source Releases and The End of Season One
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Nov 22 2015
Probabilistic Programming and Digital Humanities
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Nov 5 2015
Workshops at NIPS and Crowdsourcing in Machine Learning
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Oct 22 2015
Machine Learning Mastery and Cancer Clusters
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Oct 8 2015
Data from Video Games and The Master Algorithm
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Sep 24 2015
Strong AI and Autoencoders
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Sep 10 2015
Active Learning and Machine Learning in Neuroscience
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Aug 27 2015
Machine Learning in Biology and Getting into Grad School
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Aug 13 2015
Machine Learning for Sports and Real Time Predictions
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Jul 30 2015
Really Really Big Data and Machine Learning in Business
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Jul 16 2015
Solving Intelligence and Machine Learning Fundamentals
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Jul 2 2015
Working With Data and Machine Learning in Advertising
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Jun 18 2015
The Economic Impact of Machine Learning and Using The Kernel Trick on Big Data
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Jun 4 2015
How We Think About Privacy and Finding Features in Black Boxes
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May 21 2015
Interdisciplinary Data and Helping Humans Be Creative
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May 7 2015
Starting Simple and Machine Learning in Meds
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Apr 23 2015
Spinning Programming Plates and Creative Algorithms
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Apr 9 2015
The Automatic Statistician and Electrified Meat
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Mar 26 2015
The Future of Machine Learning from the Inside Out
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Mar 13 2015
The History of Machine Learning from the Inside Out
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Feb 26 2015
Using Models in the Wild and Women in Machine Learning
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Feb 12 2015
Common Sense Problems and Learning about Machine Learning
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Jan 29 2015
Machine Learning and Magical Thinking
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Jan 15 2015
Hello World!
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Jan 1 2015

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