Explorez tous les épisodes du podcast Talking Machines
| Titre | Date | Durée | |
|---|---|---|---|
| Gods and Robots | 09 Sep 2021 | 00:40:05 | |
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. Hosted on Acast. See acast.com/privacy for more information. | |||
| Responsibility, Risk, and Publishing | 19 Aug 2021 | 00:25:40 | |
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. Hosted on Acast. See acast.com/privacy for more information. | |||
| Prioritizing Problems and 100 episodes | 20 Mar 2020 | 00:30:55 | |
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. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Interdisciplinary Data and Helping Humans Be Creative | 07 May 2015 | 00:34:17 | |
In Episode 10 we talk with David Blei of Columbia University. We talk about his work on latent dirichlet allocation, topic models, the PhD program in data that he’s helping to create at Columbia and why exploring data is inherently multidisciplinary. We learn about Markov Chain Monte Carlo and take a listener question about how machine learning can make humans more creative. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Starting Simple and Machine Learning in Meds | 23 Apr 2015 | 00:38:24 | |
In episode nine we talk with George Dahl, of the University of Toronto, about his work on the Merck molecular activity challenge on kaggle and speech recognition. George recently successfully defended his thesis at the end of March 2015. (Congrats George!) We learn about how networks and graphs can help us understand latent properties of relationships, and we take a listener question about just how you find the right algorithm to solve a problem (Spoiler: start simple.) See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Spinning Programming Plates and Creative Algorithms | 09 Apr 2015 | 00:35:18 | |
On episode eight we talk with Charles Sutton, a professor in the School of Informatics University of Edinburgh about computer programming and using machine learning how to better understand how it’s done well. Ryan introduces us to collaborative filtering, a process that helps to make predictions about taste. Netflix and Amazon use it to recommend movies and items. It's the process that the Netflix Prize competition further helped to hone. Plus, we take a listener question on creativity in algorithms. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| The Automatic Statistician and Electrified Meat | 26 Mar 2015 | 00:45:40 | |
In episode seven of Talking Machines we talk with Zoubin Ghahramani, professor of Information Engineering in the Department of Engineering at the University of Cambridge. His project, The Automatic Statistician, aims to use machine learning to take raw data and give you statistical reports and natural languages summaries of what trends that data shows. We get really hungry exploring Bayesian Non-parametrics through the stories of the Chinese Restaurant Process and the Indian Buffet Process (but remember, there’s no free lunch). Plus we take a listener question about how much we should rely on ourselves and our ideas about what intelligence in electrified meat looks like when we try to build machine intelligences. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| The Future of Machine Learning from the Inside Out | 13 Mar 2015 | 00:28:14 | |
We hear the second part of our conversation with with Geoffrey Hinton (Google and University of Toronto), Yoshua Bengio (University of Montreal) and Yann LeCun (Facebook and NYU). They talk with us about this history (and future) of research on neural nets. We explore how to use Determinantal Point Processes. Alex Kulesza and Ben Taskar (who passed away recently) have done some really exciting work in this area, for more on DPPs check out their paper on the topic. Also, we take a listener question about machine learning and function approximation (spoiler alert: it is, and then again, it isn’t). See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| The History of Machine Learning from the Inside Out | 26 Feb 2015 | 00:32:36 | |
In episode five of Talking Machines, we hear the first part of our conversation with Geoffrey Hinton (Google and University of Toronto), Yoshua Bengio (University of Montreal) and Yann LeCun (Facebook and NYU). Ryan introduces us to the ideas in tensor factorization methods for learning latent variable models (which is both a tongue twister and and one of the new tools in ML). To find out more on the topic, the paper Tensor decompositions for learning latent variable models is a good place to start. You can also take a look at the work of Daniel Hsu, Animashree Anandkumar and Sham M. Kakade Plus we take a listener question about just where statistics stops and machine learning begins. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Using Models in the Wild and Women in Machine Learning | 12 Feb 2015 | 00:45:06 | |
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). See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Common Sense Problems and Learning about Machine Learning | 29 Jan 2015 | 00:40:55 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Machine Learning and Magical Thinking | 15 Jan 2015 | 00:35:10 | |
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. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Hello World! | 01 Jan 2015 | 00:41:28 | |
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. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| The Great AI Fallacy | 05 Mar 2020 | 00:48:03 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| If a Machine Could Predict Your Death, Should it? | 20 Feb 2020 | 00:18:07 | |
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? See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Predicting the Decade and Distributing Conferences | 06 Feb 2020 | 01:06:43 | |
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! See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Debating Project Debater and Hello NeurIPS | 21 Nov 2019 | 00:41:50 | |
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! See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| De-Enchanting AI with the Law | 07 Nov 2019 | 00:20:10 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| How to Ask an Actionable Question | 25 Oct 2019 | 00:38:57 | |
In Episode 21 of Season five we sit down with Marzyeh Ghassemi to talk about her work and how she's refined her focus. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Children are the Future and Ada Lovelace Day | 10 Oct 2019 | 00:54:50 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| News from Neil and Updates from DALI | 26 Sep 2019 | 01:08:32 | |
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. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| A Cooperative Path to Artificial Intelligence | 13 Sep 2019 | 00:17:50 | |
In episode eighteen of season five we hear Michael Littman's talk A Cooperative Path to Artificial Intelligence See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| ICML 2021: Test of Time(ly) Award | 24 Jul 2021 | 00:19:18 | |
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. Hosted on Acast. See acast.com/privacy for more information. | |||
| What Does Red Sound Like | 30 Aug 2019 | 00:49:58 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Not What But Why | 15 Aug 2019 | 00:19:57 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Idea Pandemics and Workshop Walkthrough | 01 Aug 2019 | 00:59:16 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| PosterSession.ai and Deep Quaggles | 18 Jul 2019 | 00:45:16 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| The View from Addis Ababa | 04 Jul 2019 | 00:22:43 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| DSA Addis Ababa and ICML Los Angeles | 21 Jun 2019 | 00:55:44 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Data Trusts and Citation Trends | 06 Jun 2019 | 00:54:15 | |
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. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Reproducibly and Revisiting History | 23 May 2019 | 00:46:10 | |
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. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Insights from AISTATS | 10 May 2019 | 00:52:09 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| The Deep End of Deep Learning | 25 Apr 2019 | 00:19:22 | |
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. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Learning with Less, Invisible Labor and Combating Anti-Blackness | 09 Jul 2021 | 00:36:33 | |
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. Hosted on Acast. See acast.com/privacy for more information. | |||
| Exploring MARS and Getting back to Bayesics | 11 Apr 2019 | 01:08:53 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| The Sweetness of a Bitter Lesson and Bringing ML and Healthcare Closer | 28 Mar 2019 | 00:50:38 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Slowed Down Conferences and Even More Summer Schools | 14 Mar 2019 | 00:43:01 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Jupyter Notebooks and Modern Model Distribution | 28 Feb 2019 | 00:36:57 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Real World Real Time and Five Papers for Mike Tipping | 15 Feb 2019 | 01:01:32 | |
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. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| The Bezos Paradox and Machine Learning Languages | 01 Feb 2019 | 00:41:02 | |
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. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Being Global Bit by Bit | 17 Jan 2019 | 00:48:57 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| The Possibility Of Explanation and The End of Season Four | 29 Nov 2018 | 00:18:12 | |
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! See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Neural Information Processing Systems and Distributed Internal Intelligence Systems | 16 Nov 2018 | 00:36:36 | |
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. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Data Driven Ideas and Actionable Privacy | 01 Nov 2018 | 00:45:19 | |
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. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Let's Reflect | 13 Jun 2020 | 00:00:29 | |
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.
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| AI for Good and The Real World | 18 Oct 2018 | 00:32:34 | |
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. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Systems Design and Tools for Transparency | 05 Oct 2018 | 00:40:20 | |
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. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| How to Research in Hype and CIFAR's Strategy | 20 Sep 2018 | 00:37:07 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Troubling Trends and Climbing Mountains | 07 Sep 2018 | 00:39:32 | |
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 See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information. | |||
| Gaussian Processes, Grad School, and Richard Zemel | 23 Aug 2018 | 00:43:43 | |
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