Talking Machines

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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 c…

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    • Sep 9, 2021 LATEST EPISODE
    • monthly NEW EPISODES
    • 41m AVG DURATION
    • 110 EPISODES

    4.6 from 134 ratings Listeners of Talking Machines that love the show mention: machine learning, audio quality, concepts, side, deep, like, great, content, show, good.



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    Latest episodes from Talking Machines

    Gods and Robots

    Play Episode Listen Later Sep 9, 2021 40:05


    In this episode of the podcast we shake things up! Neil is on the guest side of the table with his partner Rabbi Laura Janner-Klausner to discuss their upcoming project Gods and Robots. Katherine is joined on the host side by friend of the show professor Michael Littman.  See omnystudio.com/listener for privacy information.

    Responsibility, Risk, and Publishing

    Play Episode Listen Later Aug 19, 2021 25:40


    On this episode we feature an interview with Madhulika Shrikumar of the Partnership on AI about their recent work Managing Risk and Responsible Publication See omnystudio.com/listener for privacy information.

    ICML 2021: Test of Time(ly) Award

    Play Episode Listen Later Jul 24, 2021 19:18


    Neil and Katherine chat about ICML and the timely award winner of this years test of time award! Bayesian Learning via Stochastic Gradient Langevin Dynamics See omnystudio.com/listener for privacy information.

    Learning with Less, Invisible Labor and Combating Anti-Blackness

    Play Episode Listen Later Jul 9, 2021 36:33


    Devin Guillory of UC Berkeley, is our guest on this episode. We talk about his love of robotics, working at the center of a new hype (learning with less labels) and his paper Combatting Anti-Blackness in the AI Community. He recently gave a talk on the subject the University of Toronto   See omnystudio.com/listener for privacy information.

    Let's Reflect

    Play Episode Listen Later Jun 13, 2020 0:30


    We're not bringing you an episode this week. We're taking some time to think about the systems we take part in and how those perpetuate anti black racism and the effects of that on the work in this field. We'd like to bring you meaningful conversations around those systems and how we can change them and ourselves.  We encourage everyone to explore the amazing work of Black in AI, Data Science Africa and Shut Down STEM.  Take care of yourselves, take care of each other, and stay tuned.

    black ai reflect data science africa
    Predicting Floods and Really Doing Good

    Play Episode Listen Later May 29, 2020 39:12


    In this episode of Talking Machines we talk with Sella Nevo of Google Research about the Google Flood Forecasting Project,what they'vebeen doing, and what is means to really move the needle on AI for Good. 

    ICLR: accessible, inclusive, virtual

    Play Episode Listen Later May 14, 2020 38:42


    In episode eight of season six we talk with Alexander Rush and Shakir Mohamed about their work on ICLR this year which was first to take place in Ethiopia and then became totally virtual! 

    Humans in the Loop and Outside of the Classroom

    Play Episode Listen Later Apr 30, 2020 38:04


    In episode seven of season six we talk with Michael Littman about his work in reinforcement learning, on scientific communication, and in the classroom. 

    The Evolution of ML and Furry Little Animals

    Play Episode Listen Later Apr 16, 2020 47:59


    In episode six of season six we chat with Professor Terry Sejnowski about his work, the evolution of the field, and the development of the NeurIPS conference. We taped this episode live and took questions from the audience. Want to join our "studio audience"? Check out @tlkngmchns on Twitter.

    Talking Machines Live and Understanding Modeling Viruses

    Play Episode Listen Later Apr 2, 2020 39:53


    Episode five of season six is our first live episode! We talk with Elaine Nsoesie of Boston University about modeling disease and Covid 19 in the African context. plus we take listen questions live! Want to join our "studio audience" check out our twitter feed for how to sign up! 

    Prioritizing Problems and 100 episodes

    Play Episode Listen Later Mar 19, 2020 30:56


    Episode four of season six is our 100th episode! (Well it's Katherine's). We take a break from our regular format for Neil and Katherine to chat about the current situation around Covid-19, understanding exponentials, and what impact this might have on how problems get prioritized. 

    The Great AI Fallacy

    Play Episode Listen Later Mar 5, 2020 48:03


    In this episode we talk about the Great AI Fallacy, take a listener question about Federated Learning, and catch up with Ross Goodwin and Oscar Sharp 

    If a Machine Could Predict Your Death, Should it?

    Play Episode Listen Later Feb 20, 2020 18:07


    in episode two of season six we hear Ziad Obermeyer's talk from TedX Boston entitled If a Machine Could Predict Your Death, Should it?

    death predict tedx boston
    Predicting the Decade and Distributing Conferences

    Play Episode Listen Later Feb 6, 2020 66:43


    In episode one of season six we make some predictions about what will happen in the field in the next decade and talk with Margot Gerritsen about her work and WiDS You can listen to the WiDS podcast here!

    Debating Project Debater and Hello NeurIPS

    Play Episode Listen Later Nov 21, 2019 41:50


    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!

    De-Enchanting AI with the Law

    Play Episode Listen Later Nov 7, 2019 20:10


    in episode twenty two of season five we hear a talk from Kenneth Anderson on how the field of AI and the law can work together to form regulation from TedX Boston

    How to Ask an Actionable Question

    Play Episode Listen Later Oct 24, 2019 38:58


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

    Children are the Future and Ada Lovelace Day

    Play Episode Listen Later Oct 10, 2019 54:51


    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

    News from Neil and Updates from DALI

    Play Episode Listen Later Sep 26, 2019 68:32


    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.

    A Cooperative Path to Artificial Intelligence

    Play Episode Listen Later Sep 12, 2019 17:50


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

    What Does Red Sound Like

    Play Episode Listen Later Aug 29, 2019 49:58


    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

    Not What But Why

    Play Episode Listen Later Aug 15, 2019 19:58


    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

    Idea Pandemics and Workshop Walkthrough

    Play Episode Listen Later Aug 1, 2019 59:16


    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

    PosterSession.ai and Deep Quaggles

    Play Episode Listen Later Jul 18, 2019 45:17


    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

    The View from Addis Ababa

    Play Episode Listen Later Jul 4, 2019 22:43


    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

    DSA Addis Ababa and ICML Los Angeles

    Play Episode Listen Later Jun 20, 2019 55:45


    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

    Data Trusts and Citation Trends

    Play Episode Listen Later Jun 6, 2019 54:15


    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.

    Reproducibly and Revisiting History

    Play Episode Listen Later May 23, 2019 46:10


    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.

    Insights from AISTATS

    Play Episode Listen Later May 9, 2019 52:09


    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

    The Deep End of Deep Learning

    Play Episode Listen Later Apr 25, 2019 19:23


    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.

    Exploring MARS and Getting back to Bayesics

    Play Episode Listen Later Apr 11, 2019 68:54


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

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

    Play Episode Listen Later Mar 28, 2019 50:38


    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. Science, 363(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. Jama, 316(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. Jama, 319(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

    Slowed Down Conferences and Even More Summer Schools

    Play Episode Listen Later Mar 14, 2019 43:02


    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

    Jupyter Notebooks and Modern Model Distribution

    Play Episode Listen Later Feb 28, 2019 36:57


    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

    Real World Real Time and Five Papers for Mike Tipping

    Play Episode Listen Later Feb 14, 2019 61:33


    In season five episode three we chat about take a listener question about Five Papers for Mike Tipping, take a listener question on AIAI and chat with Eoin O'Mahony of Uber Here are Neil's five papers. What are yours? Stochastic variational inference by Hoffman, Wang, Blei and Paisley http://arxiv.org/abs/1206.7051 A way of doing approximate inference for probabilistic models with potentially billions of data ... need I say more? Austerity in MCMC Land: Cutting the Metropolis Hastings by Korattikara, Chen and Welling http://arxiv.org/abs/1304.5299 Oh ... I do need to say more ... because these three are at it as well but from the sampling perspective. Probabilistic models for big data ... an idea so important it needed to be in the list twice.  Practical Bayesian Optimization of Machine Learning Algorithms by Snoek, Larochelle and Adams http://arxiv.org/abs/1206.2944 This paper represents the rise in probabilistic numerics, I could also have chosen papers by Osborne, Hennig or others. There are too many papers out there already. Definitely an exciting area, be it optimisation, integration, differential equations. I chose this paper because it seems to have blown the field open to a wider audience, focussing as it did on deep learning as an application, so it let's me capture both an area of developing interest and an area that hits the national news. Kernel Bayes Rule by Fukumizu, Song, Gretton http://arxiv.org/abs/1009.5736 One of the great things about ML is how we have different (and competing) philosophies operating under the same roof. But because we still talk to each other (and sometimes even listen to each other)  these ideas can merge to create new and interesting things. Kernel Bayes Rule makes the list. http://www.cs.toronto.edu/~hinton/absps/imagenet.pdf An obvious choice, but you don't leave the Beatles off lists of great bands just because they are an obvious choice.

    The Bezos Paradox and Machine Learning Languages

    Play Episode Listen Later Jan 31, 2019 41:02


    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.

    Being Global Bit by Bit

    Play Episode Listen Later Jan 17, 2019 48:58


    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

    The Possibility Of Explanation and The End of Season Four

    Play Episode Listen Later Nov 29, 2018 18:13


    For the end of season four we take a break from our regular format and bring you a talk from Professor Finale Doshi Velez of Harvard University on the possibility of explanation Tune in next season!

    Neural Information Processing Systems and Distributed Internal Intelligence Systems

    Play Episode Listen Later Nov 15, 2018 36:36


    In episode twenty one of season four we talk about distributed intelligence systems (mainly those internal to humans), talk about what were excited to see at the Conference on Neural Information Processing Systems and in advance of our trek to Canada we chat with Garth Gibson president and CEO of the Vector Institute.

    Data Driven Ideas and Actionable Privacy

    Play Episode Listen Later Nov 1, 2018 45:20


    In episode twenty of season four we talk about the importance of crediting your data, answer a listener question about internships vs salaried positions and talk with Matt Kusner of the Alan Turing institute the UK’s national institute for data science and AI.

    AI for Good and The Real World

    Play Episode Listen Later Oct 18, 2018 32:35


    In episode nineteen of season four we talk about causality in the real world, take a question about being surprised by the elephant in the room and talk with Kush Varshney of IBM.

    Systems Design and Tools for Transparency

    Play Episode Listen Later Oct 4, 2018 40:21


    In episode 18 of season four we talk about systems design, (remember the 3 d's!), tools for transparency and fairness and we talk with Adria Gascon of The Alan Turing Institute, the UK’s national institute for data science and AI.

    How to Research in Hype and CIFAR's Strategy

    Play Episode Listen Later Sep 20, 2018 37:08


    In episode 17 of season four we talk about how to research in a time of hype (and other lessons from Tom Griffiths book) Neil's love of variational methods, and with Chat with Elissa Strome director of the Pan-Canadian AI Strategy for CIFAR

    Troubling Trends and Climbing Mountains

    Play Episode Listen Later Sep 6, 2018 39:32


    In this episode we talk about an article Troubling Trends in Machine learning Scholarship the difference between engineering and science (and the mountains you climb to span the distance) plus we talk with David Duvenaud of the University of Toronto

    Simulated Learning and Real World Ethics

    Play Episode Listen Later Jul 26, 2018 57:32


    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.

    ICML 2018 with Jennifer Dy

    Play Episode Listen Later Jul 12, 2018 19:54


    Season four episode twelve finds us at ICML! We bring you a special episode with Jennifer Dy, co-program chair of the conference.

    Aspirational Asimov and How to Survive a Conference

    Play Episode Listen Later Jun 28, 2018 45:03


    In season four episode eleven we talk about the possibility of the NIPS conference changing its name, what to do at ICML, And we talk with Bernhard Schölkopf.

    Explanations and Reviews

    Play Episode Listen Later Jun 14, 2018 23:35


    In episode 10 of season 4 we chat about Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR, take a listener question about how reviews of papers work at NIPS and we hear from Sven Strohband, CTO of Khosla Ventures.

    Statements on Statements

    Play Episode Listen Later May 31, 2018 26:48


    In episode 9 of season 4 we talk about the Statement on Nature Machine Intelligence. We reached out to Nature for a statement on the statement and received the following: “At Springer Nature we are very clear in our mission to advance discovery and help researchers share their work. Having an extensive, and growing, open access portfolio is one important way we do this but it is important to remember that while open access has been around for 20 years now it still only accounts for a small percentage of overall global research output with demand for subscription content remaining high. This is because the move to open access is complex, and for many, simply not a viable option. Nature Machine Intelligence is a new subscription journal that aims to stimulate cross-disciplinary interactions, reach broad audiences and explore the impact that AI research has on other fields by publishing high-quality research, reviews and commentary on machine learning, robotics and AI. It involves substantial editorial development, offers high levels of author service and publishes informative, accessible content beyond primary research all of which requires considerable investment. At present, we believe that the fairest way of producing highly selective journals like this one and ensuring their long-term sustainability as a resource for the widest possible community, is to spread these costs among many readers — instead of having them borne by a few authors.     We also offer multiple open access options for AI authors. We already publish AI papers in Scientific Reports and Nature Communications, which are the largest open access journal in the world and the most cited open access journal respectively. We offer hybrid publishing options and are set to launch a new AI multidisciplinary, open access journal later this year. We help all researchers to freely share their discoveries by encouraging preprint posting and data- and code-sharing and continue to extend access to all Nature journals in various ways, including our free SharedIt content-sharing initiative, which provides authors and subscribers with shareable links to view-only versions of published papers.” We also get a chance to talk with Maithra Raghu from the Google Brain team about her work.

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