Talking Machines

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 AbebeSee omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

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 GenomicsSee omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

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 InstituteSee omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

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.

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 AbujaSee omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

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 AbujaSee omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

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.

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.

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 VoleonSee omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

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.

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 BrainSee omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

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 paperFinlayson, 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 PapersBeam, 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 m

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 InstituteSee omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

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 InstiuteSee omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

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 UberHere are Neil's five papers. What are yours?Stochastic variational inference by Hoffman, Wang, Blei and Paisleyhttp://arxiv.org/abs/1206.7051A 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 Wellinghttp://arxiv.org/abs/1304.5299Oh ... 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 Adamshttp://arxiv.org/abs/1206.2944This paper represents the rise in probabilistic numerics, I could also have chosen papers by Osborne, Hennig or others. There are too many papers out

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.

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 WestSee omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.

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.

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.

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.