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Talking Machines

Updated 7 days ago

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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.

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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.

iTunes Ratings

128 Ratings
Average Ratings
103
12
5
4
4

Frequent Deep Dives

By Toby Patterson - Aug 25 2016
Read more
This is the most in-depth podcast on machine learning to date.

Fantastic show

By 01001011 01100110 - Jun 11 2016
Read more
Gives insight not only to the new tech but the ideas behind machine learning and how it works.

iTunes Ratings

128 Ratings
Average Ratings
103
12
5
4
4

Frequent Deep Dives

By Toby Patterson - Aug 25 2016
Read more
This is the most in-depth podcast on machine learning to date.

Fantastic show

By 01001011 01100110 - Jun 11 2016
Read more
Gives insight not only to the new tech but the ideas behind machine learning and how it works.
Cover image of Talking Machines

Talking Machines

Latest release on Nov 21, 2019

Read more

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.

Rank #1: Common Sense Problems and Learning about Machine Learning

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On episode three of Talking Machines we sit down with Kevin Murphy who is currently a research scientist at Google. We talk with him about the work he’s doing there on the Knowledge Vault, his textbook, Machine Learning: A Probabilistic Perspective (and its arch nemesis which we won’t link to), and how to learn about machine learning (Metacademy is a great place to start). We tackle a listener question about the dream of a one step solution to strong Artificial Intelligence and if Deep Neural Networks might be it. Plus, Ryan introduces us to a new way of thinking about questions in machine learning from Yoshua Bengio’s Lab at the University of Montreal out lined in their new paper, Identifying and attacking the saddle point problem in high-dimensional non-convex optimization, and Katherine brings up Facebook’s release of open source machine learning tools and we talk about what it might mean. If you want to explore some open source tools for machine learning we also recommend giving these a try:Super big list of ML Open Source Projects! Torch Gaussian Process Machine Learning ToolboxPyMCMalletStanWekaTheanoCaffeSpearmint

Jan 29 2015

40mins

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Rank #2: Economies, Work and AI

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In episode seven of season four we chat about Ellis and the UK AI Sector Deal , we take a listener question about the next AI winter and if/when it is coming, plus we hear from Christina Colclough Director of Platform and Agency Workers, Digitalization and Trade UNI Global Union.

May 03 2018

42mins

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Rank #3: The Deep End of Deep Learning

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In this episode as we prep for ICLR we take a break from our usual format to bring you a talk from Hugo LaRochelle at TedX Boston on Deep Learning.

Apr 25 2019

19mins

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Rank #4: Jupyter Notebooks and Modern Model Distribution

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In episode four of season five we talk about Jupyter Notebooks and Neil's dream of a world craft software and devices, we take a listener question about the conversation surrounding Open AI's GPT-2 its announcement and the coverage and we hear an interview with Brooks Paige of the Alan Turing Instiute

Feb 28 2019

36mins

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Rank #5: Gaussian Processes, Grad School, and Richard Zemel

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Aug 23 2018

43mins

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Rank #6: The Bezos Paradox and Machine Learning Languages

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In episode two of season five we unpack the Bezos Paradox (TM Neil Lawrence) take a listener question about best papers and chat with Dougal Maclaurin of Google Brain.

Feb 01 2019

41mins

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Rank #7: Natural vs Artificial Intelligence and Doing Unexpected Work

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In season four episode three of Talking Machines we chat about Neil’s recent thinking (definitely not work) on the core differences between natural intelligence and machine intelligence, he recently wrote blog post on the subject and in the fall of 2017 he gave a TedX talk about the topic. We also take a listener question about what maths you should take to get into building ML tools. Our guests this week are Moshe Vardi, Karen Ostrum George Distinguished Service Professor in Computational Engineering and Director of the Ken Kennedy Institute for Information Technology at Rice University and Margaret Levi Director of the Center for Advanced Study in the Behavioral Sciences(CASBS) at Stanford and Professor of Political Science, Stanford University, and Jere L. Bacharach Professor Emerita of International Studies in the Department of Political Science at the University of Washington. They co-organized a symposium put on by the American Academy of Arts and Sciences and the Royal Society about the future of work. We got a chance to speak to both of them about their work and the event.

Mar 08 2018

58mins

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Rank #8: Using Models in the Wild and Women in Machine Learning

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In episode four we talk with Hanna Wallach, of Microsoft Research. She's also a professor in the Department of Computer Science, University of Massachusetts Amherst and one of the founders of Women in Machine Learning (better known as WiML). We take a listener question about scalability and the size of data sets. And Ryan takes us through topic modeling using Latent Dirichlet allocation (say that five times fast).

Feb 12 2015

45mins

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Rank #9: Simulated Learning and Real World Ethics

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In episode thirteen of season four we chat about simulations, reinforcement learning, and Philippa Foot. We take a listener question about the update to the ACM code of ethics (first time since 1992!) and We talk with professor Mike Jordan.

Jul 27 2018

57mins

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Rank #10: Exploring MARS and Getting back to Bayesics

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In episode seven of season five of we chat about MARS and Re: MARS OpenAI's status changes and We talk with Jasper Snoek of Google Brain

Apr 11 2019

1hr 8mins

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Rank #11: Computational Learning Theory and Machine Learning for Understanding Cells

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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.

May 19 2016

40mins

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Rank #12: What Does Red Sound Like

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In episode seventeen of season five we talk about Why Red Doesn't Sound Like a Bell, take a listener question about our Turing brackets (and Invent the Very Good Sort Awards) and listen to a chat with Tewodros Abebe

Aug 30 2019

49mins

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Rank #13: Eric Lander and Restricted Boltzmann Machines

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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.

Aug 18 2016

53mins

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Rank #14: Not What But Why

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In this episode of Talking Machines we take a listen to Professor Engelhardt's TedX Boston talk, Not What But Why: Machine Learning for Understanding Genomics

Aug 15 2019

19mins

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Rank #15: A Cooperative Path to Artificial Intelligence

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In episode eighteen of season five we hear Michael Littman's talk A Cooperative Path to Artificial Intelligence

Sep 13 2019

17mins

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Rank #16: The Long View and Learning in Person

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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.

Sep 21 2017

1hr 5mins

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Rank #17: Generative Art and Hamiltonian Monte Carlo

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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.

Aug 04 2016

47mins

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Rank #18: Machine Learning in the Field and Bayesian Baked Goods

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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.

Sep 08 2017

59mins

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Rank #19: Being Global Bit by Bit

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In episode one of season five we talk about Bit by Bit, take a listener question on machine learning gatherings on the African continent (Deep Learning INDABA! DSA!) and hear an interview with Daphne Koller recorded at ODSC West

Jan 17 2019

48mins

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Rank #20: Getting a Start in ML and Applied AI at Facebook

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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.

Jul 13 2017

57mins

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Debating Project Debater and Hello NeurIPS

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In our last episode for season five Katherine and Neil debate his debating project debater and talk about whats coming up at NeurIPS. Hope to see you there!

Nov 21 2019

41mins

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De-Enchanting AI with the Law

Nov 07 2019

19mins

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How to Ask an Actionable Question

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In Episode 21 of Season five we sit down with Marzyeh Ghassemi to talk about her work and how she's refined her focus.

Oct 25 2019

38mins

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Children are the Future and Ada Lovelace Day

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In episode twenty of season five we talk with Neil about a discussion he had about the impact of ML tools on children talk about the new Diversity Dashboard from the Turing Institute in response to a question about cool things for Ada Lovelace day plus we sit down with Corinna Cortes of Google AI

Oct 10 2019

54mins

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News from Neil and Updates from DALI

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In episode eighteen of season five we talk about DALI, get some big news about the next thing for Neil and talk with Benjamin Akera.

Sep 26 2019

1hr 8mins

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A Cooperative Path to Artificial Intelligence

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In episode eighteen of season five we hear Michael Littman's talk A Cooperative Path to Artificial Intelligence

Sep 13 2019

17mins

Play

What Does Red Sound Like

Podcast cover
Read more

In episode seventeen of season five we talk about Why Red Doesn't Sound Like a Bell, take a listener question about our Turing brackets (and Invent the Very Good Sort Awards) and listen to a chat with Tewodros Abebe

Aug 30 2019

49mins

Play

Not What But Why

Podcast cover
Read more

In this episode of Talking Machines we take a listen to Professor Engelhardt's TedX Boston talk, Not What But Why: Machine Learning for Understanding Genomics

Aug 15 2019

19mins

Play

Idea Pandemics and Workshop Walkthrough

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in episode 15 of season five of Talking Machines we' chat about the recently announced workshops at NeurIPS 2019, find ourselves in the middle of an I Love Lucy Episode about technical term usage and talk with Randy Goebel of the Alberta Machine Intelligence Institute

Aug 01 2019

59mins

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PosterSession.ai and Deep Quaggles

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In episode 14 of season five we talk about On the marginal likelihood and cross-validation, Katherine is STILL excited about PosterSession.ai, we invent Deep Quaggles and listen to a conversation with professor Elaine Nsoesie of BU

Jul 18 2019

45mins

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The View from Addis Ababa

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In episode thirteen of season five we bring you a the rest of our conversation with Michael Melese from Addis Ababa University and Charles Saidu of Baze University Abuja

Jul 04 2019

22mins

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DSA Addis Ababa and ICML Los Angeles

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In episode twelve of season five we bring you a rundown of Data Science Africa's latest workshop answer a listener question about what got us excited at ICML and hear the first part of our conversation with Michael Melese from Addis Ababa University and Charles Saidu of Baze University Abuja

Jun 21 2019

55mins

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Data Trusts and Citation Trends

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In episode eleven of season five, we dig in to just what a data trust actually is, take a look at citation trends and other places (PMLR) you can dig up data to understand the field and talk with Raia Hadsell of DeepMind.

Jun 06 2019

54mins

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Reproducibly and Revisiting History

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In episode ten of season five we talk about reproducibility, take a listener question on re understanding the history of the field given where we are now and how other fields are reviewing their own history and listen to a conversation with Graham Taylor of the Vector Institute.

May 23 2019

46mins

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Insights from AISTATS

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In episode nine of season five we talk about some interesting work from AISTATS, dive into unbiased implicit variational inference, and chat with Jon McAuliffe CIO of Voleon

May 10 2019

52mins

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The Deep End of Deep Learning

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In this episode as we prep for ICLR we take a break from our usual format to bring you a talk from Hugo LaRochelle at TedX Boston on Deep Learning.

Apr 25 2019

19mins

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Exploring MARS and Getting back to Bayesics

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In episode seven of season five of we chat about MARS and Re: MARS OpenAI's status changes and We talk with Jasper Snoek of Google Brain

Apr 11 2019

1hr 8mins

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The Sweetness of a Bitter Lesson and Bringing ML and Healthcare Closer

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In episode six of season five we talk about Richard Sutton's A Bitter Lesson. Chat about IEEE's new Ethical Guidelines and talk with Andrew Beam Senior Fellownn at Flagship Pioneering, Head of Machine Learning for Flagship VL57 and Assistant Professor, Department of Epidemiology, Harvard T.H. Chan School of Public Health.

Here are some of the papers we got to chat about! Also, VL57 is hiring!

Adversarial attacks on Medical ML Science paper

Finlayson, S.G., Bowers, J.D., Ito, J., Zittrain, J.L., Beam, A.L. and Kohane, I.S., 2019. Adversarial attacks on medical machine learning. Science363(6433), pp.1287-1289.

Link: https://cyber.harvard.edu/story/2019-03/adversarial-attacks-medical-ai-health-policy-challenge

JAMA Papers

Beam, A.L. and Kohane, I.S., 2016. Translating artificial intelligence into clinical care. Jama316(22), pp.2368-2369.

Link: https://www.dropbox.com/s/4o1va07tqwvrxsn/Beam_TranslatingAI_2016.pdf?dl=0

Beam, A.L. and Kohane, I.S., 2018. Big data and machine learning in health care. Jama319(13), pp.1317-1318.

Link: https://www.dropbox.com/s/q1cixzmsdugq3vy/Beam_BigData_ML.pdf?dl=0

Opportunities in machine learning for healthcare:

Ghassemi, M., Naumann, T., Schulam, P., Beam, A.L. and Ranganath, R., 2018. Opportunities in machine learning for healthcare. arXiv preprint arXiv:1806.00388.

Link: https://arxiv.org/abs/1806.00388

Mar 28 2019

50mins

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Slowed Down Conferences and Even More Summer Schools

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In episode five of season five we talk about the Stu Hunter conference, Summer schools options (DLRLSS!) and chat with Adrian Weller of the Alan Turing Institute

Mar 14 2019

43mins

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Jupyter Notebooks and Modern Model Distribution

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In episode four of season five we talk about Jupyter Notebooks and Neil's dream of a world craft software and devices, we take a listener question about the conversation surrounding Open AI's GPT-2 its announcement and the coverage and we hear an interview with Brooks Paige of the Alan Turing Instiute

Feb 28 2019

36mins

Play

iTunes Ratings

128 Ratings
Average Ratings
103
12
5
4
4

Frequent Deep Dives

By Toby Patterson - Aug 25 2016
Read more
This is the most in-depth podcast on machine learning to date.

Fantastic show

By 01001011 01100110 - Jun 11 2016
Read more
Gives insight not only to the new tech but the ideas behind machine learning and how it works.