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Rank #58 in Technology category

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Talking Machines

Updated 9 days ago

Rank #58 in Technology category

Technology
Tech News
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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

121 Ratings
Average Ratings
97
12
4
4
4

Frequent Deep Dives

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

Fantastic show

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

iTunes Ratings

121 Ratings
Average Ratings
97
12
4
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

Updated 9 days ago

Rank #58 in Technology category

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: 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
59 mins
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Rank #2: Hello World!

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In the first episode of Talking Machines we meet our hosts, Katherine Gorman (nerd, journalist) and Ryan Adams (nerd, Harvard computer science professor), and explore some of the interviews you'll be able to hear this season. Today we hear some short clips on big issues, we'll get technical, but today is all about introductions.We start with Kevin Murphy of Google talking about his textbook that has become a standard in the field. Then we turn to Hanna Wallach of Microsoft Research NYC and UMass Amherst and hear about the founding of WiML (Women in Machine Learning). Next we discuss academia's relationship with business with Max Welling from the University of Amsterdam, program co-chair of  the 2013 NIPS conference (Neural Information Processing Systems). Finally, we sit down with three pillars of the field Yann LeCun, Yoshua Bengio, and Geoff Hinton to hear about where the field has been and where it might be headed.
Jan 01 2015
41 mins
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Rank #3: Machine Learning and Magical Thinking

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Today on Talking Machines we hear from Google researcher Ilya Sutskever about his work, how he became interested in machine learning, and why it takes a little bit of magical thinking. We take your questions, and explore where the line between human programming and computer learning actually is. And we sift through some news from the field, Ryan explains the concepts behind one of the best papers  at NIPS this year, A * Sampling, and Katherine brings up an open letter about research priorities and ethical questions that was recently published.
Jan 15 2015
35 mins
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Rank #4: Gaussian Processes, Grad School, and Richard Zemel

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Aug 23 2018
43 mins
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Rank #5: 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
36 mins
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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
41 mins
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Rank #7: 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
40 mins
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Rank #8: The Pace of Change and The Public View of ML

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In episode ten of season three we talk about the rate of change (prompted by Tim Harford), take a listener question about the power of kernels, and talk with Peter Donnelly in his capacity with the Royal Society's Machine Learning Working Group about the work they've done on the public's views on AI and ML.

Oct 05 2017
40 mins
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Rank #9: Explainability and the Inexplicable

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In episode six of season four we chat about AI and religion, we take a listener question about personal bias checking and we hear from Been Kim of Google Brain.

Apr 19 2018
43 mins
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Rank #10: ANGLICAN and Probabilistic Programming

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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.
Sep 01 2016
44 mins
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Rank #11: 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
45 mins
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Rank #12: Software and Statistics for Machine Learning

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In episode six of season two, we talk about how to build software for machine learning (and what the roadblocks are), we take a listener question about how to start exploring a new dataset, plus, we talk with Rob Tibshirani of Stanford University.
Mar 24 2016
39 mins
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Rank #13: OpenAI and Gaussian Processes

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In episode two of season two Ryan introduces us to Gaussian processes, we take a listener question on K-means. Plus, we talk with Ilya Sutskever the director of research for OpenAI. (For more from Ilya, you can listen to our season one interview with him.)
Jan 28 2016
35 mins
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Rank #14: 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
57 mins
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Rank #15: 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
57 mins
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Rank #16: 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
47 mins
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Rank #17: 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
1 hour 8 mins
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Rank #18: Good Data Practice Rules

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In episode five of season four we talk about the GDPR or as we like to think of it Good Data Practice Rules. (If you actually read it, you move to expert level!) We take a listener question about the power of approximate inference, and we hear from our guest Andrew Blake of The Alan Turing Institute.

Apr 05 2018
51 mins
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Rank #19: Active Learning and Machine Learning in Neuroscience

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In episode eighteen we talk with Sham Kakade, of Microsoft Research New England, about his expansive work which touches on everything from neuroscience to theoretical machine learning. Ryan introduces us to active learning (great tutorial here) and we take a question on evolutionary algorithms. Today we're announcing that season two of Talking Machines is moving into development, but we need your help! In order to raise funds, we've opened the show up to sponsorship and started a Kickstarter and we've got some great nerd cred prizes to thank you with. But more than just getting you a totally sweet mug your donation will fuel journalism about the reality of scientific research, something that is unfortunately hard to find. Lend a hand if you can!
Aug 27 2015
53 mins
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Rank #20: 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
19 mins
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