Rank #1: Common Sense Problems and Learning about Machine Learning
Jan 29 2015
Rank #2: Economies, Work and AI
May 03 2018
Rank #4: Jupyter Notebooks and Modern Model Distribution
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
Rank #5: Gaussian Processes, Grad School, and Richard Zemel
Aug 23 2018
Rank #6: The Bezos Paradox and Machine Learning Languages
Feb 01 2019
Rank #7: Natural vs Artificial Intelligence and Doing Unexpected Work
In season four episode three of Talking Machines we chat about Neil’s recent thinking (definitely not work) on the core differences between natural intelligence and machine intelligence, he recently wrote blog post on the subject and in the fall of 2017 he gave a TedX talk about the topic. We also take a listener question about what maths you should take to get into building ML tools. Our guests this week are Moshe Vardi, Karen Ostrum George Distinguished Service Professor in Computational Engineering and Director of the Ken Kennedy Institute for Information Technology at Rice University and Margaret Levi Director of the Center for Advanced Study in the Behavioral Sciences(CASBS) at Stanford and Professor of Political Science, Stanford University, and Jere L. Bacharach Professor Emerita of International Studies in the Department of Political Science at the University of Washington. They co-organized a symposium put on by the American Academy of Arts and Sciences and the Royal Society about the future of work. We got a chance to speak to both of them about their work and the event.
Mar 08 2018
Rank #8: Using Models in the Wild and Women in Machine Learning
Feb 12 2015
Rank #9: Simulated Learning and Real World Ethics
Jul 27 2018
Rank #11: Computational Learning Theory and Machine Learning for Understanding Cells
May 19 2016
Rank #13: Eric Lander and Restricted Boltzmann Machines
Aug 18 2016
Rank #14: Not What But Why
Aug 15 2019
Rank #16: The Long View and Learning in Person
In episode nine of season three we chat about the difference between models and algorithms, take a listener question about summer schools and learning in person as opposed to learning digitally, and we chat with John Quinn of the United Nations Global Pulse lab in Kampala, Uganda and Makerere University's Artificial Intelligence Research group.
Sep 21 2017
Rank #17: Generative Art and Hamiltonian Monte Carlo
Aug 04 2016
Rank #18: Machine Learning in the Field and Bayesian Baked Goods
In episode eight of season three we return to the epic (or maybe not so epic) clash between frequentists and bayesians, take a listener question about the ethical questions generators of machine learning should be asking of themselves (not just their tools) and we hear a conversation with Ernest Mwebaze of Makerere University.
Sep 08 2017
Rank #20: Getting a Start in ML and Applied AI at Facebook
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.
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Jul 13 2017