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
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
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.
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.
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.,...
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
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
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...
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
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.
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.
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.
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