Talking Machines
By Tote Bag Productions
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Category: Technology
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Subscribers: 582
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Episodes: 110
Description
Talking Machines is your window into the world of machine learning. Your hosts, Katherine Gorman and Neil Lawrence, bring you clear conversations with experts in the field, insightful discussions of industry news, and useful answers to your questions. Machine learning is changing the questions we can ask of the world around us, here we explore how to ask the best questions and what to do with the answers. Hosted on Acast. See acast.com/privacy for more information.
| Episode | Date |
|---|---|
|
Gods and Robots
|
Sep 09, 2021 |
|
Responsibility, Risk, and Publishing
|
Aug 19, 2021 |
|
ICML 2021: Test of Time(ly) Award
|
Jul 24, 2021 |
|
Learning with Less, Invisible Labor and Combating Anti-Blackness
|
Jul 09, 2021 |
|
Let's Reflect
|
Jun 13, 2020 |
|
Predicting Floods and Really Doing Good
|
May 29, 2020 |
|
ICLR: accessible, inclusive, virtual
|
May 14, 2020 |
|
Humans in the Loop and Outside of the Classroom
|
May 01, 2020 |
|
The Evolution of ML and Furry Little Animals
|
Apr 16, 2020 |
|
Talking Machines Live and Understanding Modeling Viruses
|
Apr 03, 2020 |
|
Prioritizing Problems and 100 episodes
|
Mar 20, 2020 |
|
The Great AI Fallacy
|
Mar 05, 2020 |
|
If a Machine Could Predict Your Death, Should it?
|
Feb 20, 2020 |
|
Predicting the Decade and Distributing Conferences
|
Feb 06, 2020 |
|
Debating Project Debater and Hello NeurIPS
|
Nov 21, 2019 |
|
De-Enchanting AI with the Law
|
Nov 07, 2019 |
|
How to Ask an Actionable Question
|
Oct 25, 2019 |
|
Children are the Future and Ada Lovelace Day
|
Oct 10, 2019 |
|
News from Neil and Updates from DALI
|
Sep 26, 2019 |
|
A Cooperative Path to Artificial Intelligence
|
Sep 13, 2019 |
|
What Does Red Sound Like
|
Aug 30, 2019 |
|
Not What But Why
|
Aug 15, 2019 |
|
Idea Pandemics and Workshop Walkthrough
|
Aug 01, 2019 |
|
PosterSession.ai and Deep Quaggles
|
Jul 18, 2019 |
|
The View from Addis Ababa
|
Jul 04, 2019 |
|
DSA Addis Ababa and ICML Los Angeles
|
Jun 21, 2019 |
|
Data Trusts and Citation Trends
|
Jun 06, 2019 |
|
Reproducibly and Revisiting History
|
May 23, 2019 |
|
Insights from AISTATS
|
May 10, 2019 |
|
The Deep End of Deep Learning
|
Apr 25, 2019 |
|
Exploring MARS and Getting back to Bayesics
|
Apr 11, 2019 |
|
The Sweetness of a Bitter Lesson and Bringing ML and Healthcare Closer
|
Mar 28, 2019 |
|
Slowed Down Conferences and Even More Summer Schools
|
Mar 14, 2019 |
|
Jupyter Notebooks and Modern Model Distribution
|
Feb 28, 2019 |
|
Real World Real Time and Five Papers for Mike Tipping
|
Feb 15, 2019 |
|
The Bezos Paradox and Machine Learning Languages
|
Feb 01, 2019 |
|
Being Global Bit by Bit
|
Jan 17, 2019 |
|
The Possibility Of Explanation and The End of Season Four
|
Nov 29, 2018 |
|
Neural Information Processing Systems and Distributed Internal Intelligence Systems
|
Nov 16, 2018 |
|
Data Driven Ideas and Actionable Privacy
|
Nov 01, 2018 |
|
AI for Good and The Real World
|
Oct 18, 2018 |
|
Systems Design and Tools for Transparency
|
Oct 05, 2018 |
|
How to Research in Hype and CIFAR's Strategy
|
Sep 20, 2018 |
|
Troubling Trends and Climbing Mountains
|
Sep 07, 2018 |
|
Gaussian Processes, Grad School, and Richard Zemel
|
Aug 23, 2018 |
|
Long Term Fairness
|
Aug 09, 2018 |
|
Simulated Learning and Real World Ethics
|
Jul 27, 2018 |
|
ICML 2018 with Jennifer Dy
|
Jul 12, 2018 |
|
Aspirational Asimov and How to Survive a Conference
|
Jun 28, 2018 |
|
Explanations and Reviews
|
Jun 14, 2018 |
|
Statements on Statements
|
May 31, 2018 |
|
The Futility of Artificial Carpenters and Further Reading
|
May 17, 2018 |
|
Economies, Work and AI
|
May 03, 2018 |
|
Explainability and the Inexplicable
|
Apr 19, 2018 |
|
Good Data Practice Rules
|
Apr 05, 2018 |
|
Can an AI Practitioner Fix a Radio?
|
Mar 22, 2018 |
|
Natural vs Artificial Intelligence and Doing Unexpected Work
|
Mar 08, 2018 |
|
Scientific Rigor and Turning Information into Action
|
Feb 22, 2018 |
|
Code Review for Community Change
|
Feb 08, 2018 |
|
The Pace of Change and The Public View of ML
|
Oct 05, 2017 |
|
The Long View and Learning in Person
|
Sep 21, 2017 |
|
Machine Learning in the Field and Bayesian Baked Goods
|
Sep 08, 2017 |
|
Data Science Africa with Dina Machuve
|
Aug 10, 2017 |
|
The Church of Bayes and Collecting Data
|
Jul 28, 2017 |
|
Getting a Start in ML and Applied AI at Facebook
|
Jul 13, 2017 |
|
Bias Variance Dilemma for Humans and the Arm Farm
|
Jun 29, 2017 |
|
Overfitting and Asking Ecological Questions with ML
|
Jun 15, 2017 |
|
Graphons and "Inferencing"
|
May 25, 2017 |
|
Hosts of Talking Machines: Neil Lawrence and Ryan Adams
|
Apr 27, 2017 |
|
ANGLICAN and Probabilistic Programming
|
Sep 01, 2016 |
|
Eric Lander and Restricted Boltzmann Machines
|
Aug 18, 2016 |
|
Generative Art and Hamiltonian Monte Carlo
|
Aug 04, 2016 |
|
Perturb-and-MAP and Machine Learning in the Flint Water Crisis
|
Jul 21, 2016 |
|
Automatic Translation and t-SNE
|
Jul 07, 2016 |
|
Fantasizing Cats and Data Numbers
|
Jun 16, 2016 |
|
Spark and ICML
|
Jun 02, 2016 |
|
Computational Learning Theory and Machine Learning for Understanding Cells
|
May 19, 2016 |
|
Sparse Coding and MADBITS
|
May 05, 2016 |
|
Remembering David MacKay
|
Apr 21, 2016 |
|
Machine Learning and Society
|
Apr 08, 2016 |
|
Software and Statistics for Machine Learning
|
Mar 24, 2016 |
|
Machine Learning in Healthcare and The AlphaGo Matches
|
Mar 10, 2016 |
|
AI Safety and The Legacy of Bletchley Park
|
Feb 25, 2016 |
|
Robotics and Machine Learning Music Videos
|
Feb 11, 2016 |
|
OpenAI and Gaussian Processes
|
Jan 28, 2016 |
|
Real Human Actions and Women in Machine Learning
|
Jan 14, 2016 |
|
Open Source Releases and The End of Season One
|
Nov 22, 2015 |
|
Probabilistic Programming and Digital Humanities
|
Nov 05, 2015 |
|
Workshops at NIPS and Crowdsourcing in Machine Learning
|
Oct 22, 2015 |
|
Machine Learning Mastery and Cancer Clusters
|
Oct 08, 2015 |
|
Data from Video Games and The Master Algorithm
|
Sep 24, 2015 |
|
Strong AI and Autoencoders
|
Sep 10, 2015 |
|
Active Learning and Machine Learning in Neuroscience
|
Aug 27, 2015 |
|
Machine Learning in Biology and Getting into Grad School
|
Aug 13, 2015 |
|
Machine Learning for Sports and Real Time Predictions
|
Jul 30, 2015 |
|
Really Really Big Data and Machine Learning in Business
|
Jul 16, 2015 |
|
Solving Intelligence and Machine Learning Fundamentals
|
Jul 02, 2015 |
|
Working With Data and Machine Learning in Advertising
|
Jun 18, 2015 |
|
The Economic Impact of Machine Learning and Using The Kernel Trick on Big Data
|
Jun 04, 2015 |
|
How We Think About Privacy and Finding Features in Black Boxes
|
May 21, 2015 |
|
Interdisciplinary Data and Helping Humans Be Creative
|
May 07, 2015 |
|
Starting Simple and Machine Learning in Meds
|
Apr 23, 2015 |
|
Spinning Programming Plates and Creative Algorithms
|
Apr 09, 2015 |
|
The Automatic Statistician and Electrified Meat
|
Mar 26, 2015 |
|
The Future of Machine Learning from the Inside Out
|
Mar 13, 2015 |
|
The History of Machine Learning from the Inside Out
|
Feb 26, 2015 |
|
Using Models in the Wild and Women in Machine Learning
|
Feb 12, 2015 |
|
Common Sense Problems and Learning about Machine Learning
|
Jan 29, 2015 |
|
Machine Learning and Magical Thinking
|
Jan 15, 2015 |
|
Hello World!
|
Jan 01, 2015 |