All Episodes

Gods and Robots

Responsibility, Risk, and Publishing

ICML 2021: Test of Time(ly) Award

S7 Ep1: Learning with Less, Invisible Labor and Combating Anti-Blackness

Let's Reflect

S6 Ep9: Predicting Floods and Really Doing Good

S6 Ep8: ICLR: accessible, inclusive, virtual

Humans in the Loop and Outside of the Classroom

S6 Ep8: TM_Andersson_041520_mixdown

S6 Ep2: Talking Machines Live and Understanding Modeling Viruses

S6 Ep4: Prioritizing Problems and 100 episodes

S6: The Great AI Fallacy

S6 Ep2: If a Machine Could Predict Your Death, Should it?

S6 Ep1: Predicting the Decade and Distributing Conferences

S5 Ep23: Debating Project Debater and Hello NeurIPS

S5 Ep22: De-Enchanting AI with the Law

S5 Ep21: How to Ask an Actionable Question

S5 Ep20: Children are the Future and Ada Lovelace Day

S5 Ep19: News from Neil and Updates from DALI

S5 Ep18: A Cooperative Path to Artificial Intelligence

S5 Ep17: What Does Red Sound Like

S5 Ep16: Not What But Why

S5 Ep15: Idea Pandemics and Workshop Walkthrough

S5 Ep14: PosterSession.ai and Deep Quaggles

S5 Ep13: The View from Addis Ababa

S5 Ep12: DSA Addis Ababa and ICML Los Angeles

S5 Ep11: Data Trusts and Citation Trends

S5 Ep10: Reproducibly and Revisiting History

S5 Ep9: May 9th Episode

S5 Ep8: The Deep End of Deep Learning

S5 Ep7: Exploring MARS and Getting back to Bayesics

S5 Ep6: The Sweetness of a Bitter Lesson and Bringing ML and Healthcare Closer

S5 Ep5: Slowed Down Conferences and Even More Summer Schools

S5 Ep4: Jupyter Notebooks and Modern Model Distribution

S5 Ep3: Real World Real Time and Five Papers for Mike Tipping

S5 Ep2: The Bezos Paradox and Machine Learning Languages

S5 Ep1: Being Global Bit by Bit

S4 Ep22: The Possibility Of Explanation and The End of Season Four

S4 Ep21: Neural Information Processing Systems and Distributed Internal Intelligence Systems

S4 Ep20: Data Driven Ideas and Actionable Privacy

S4 Ep19: AI for Good and The Real World

S4 Ep18: Systems Design and Tools for Transparency

S4 Ep17: How to Research in Hype and CIFAR's Strategy

S4 Ep16: Troubling Trends and Climbing Mountains

S4 Ep15: Gaussian Processes, Grad School, and Richard Zemel

S4 Ep14: Long Term Fairness

S4 Ep13: Simulated Learning and Real World Ethics

S4 Ep12: ICML 2018 with Jennifer Dy

S4 Ep11: Aspirational Asimov and How to Survive a Conference

S4 Ep9: Explanations and Reviews

9: Statements on Statements

S4 Ep8: The Futility of Artificial Carpenters and Further Reading

7: Economies, Work and AI

Explainability and the Inexplicable

Good Data Practice Rules

Can an AI Practitioner Fix an Evolved System?

Natural vs Artificial Intelligence and Doing Unexpected Work

Scientific Rigor and Turning Information into Action

Code Review for Community Change

The Pace of Change and The Public View of ML

The Long View and Learning in Person

Machine Learning in the Field and Bayesian Baked Goods

Data Science Africa with Dina Machuve

The Church of Bayes and Collecting Data

Getting a Start in ML and Applied AI at Facebook

Bias Variance Dilemma for Humans and the Arm Farm

Overfitting and Asking Ecological Questions with ML

Graphons and "Inferencing"

Hosts of Talking Machines: Neil Lawrence and Ryan Adams

ANGLICAN and Probabilistic Programming

Eric Lander and Restricted Boltzmann Machines

Generative Art and Hamiltonian Monte Carlo

Perturb-and-MAP and Machine Learning in the Flint Water Crisis

Automatic Translation and t-SNE

Fantasizing Cats and Data Numbers

Spark and ICML

Computation Learning Theory and Machine Learning for Understanding Cells

Sparse Coding and MADBITS

Remembering David MacKay

Machine Learning and Society

Software and Statistics for Machine Learning

Machine Learning in Healthcare and The AlphaGo Matches

AI Safety and The Legacy of Bletchley Park

Robotics and Machine Learning Music Videos

OpenAI and Gaussian Processes

Real Human Actions and Women in Machine Learning

Open Source Releases and The End of Season One

Probabilistic Programming and Digital Humanities

Workshops at NIPS and Crowdsourcing in Machine Learning

Machine Learning Mastery and Cancer Clusters

Data from Video Games and The Master Algorithm

Strong AI and Autoencoders

Active Learning and Machine Learning in Neuroscience

Machine Learning in Biology and Getting into Grad School

Machine Learning for Sports and Real Time Predictions

Really Really Big Data and Machine Learning in Business

Solving Intelligence and Machine Learning Fundamentals

Working With Data and Machine Learning in Advertising

The Economic Impact of Machine Learning and Using The Kernel Trick on Big Data

How We Think About Privacy and Finding Features in Black Boxes