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by   -   May 22, 2015

data_eye_privacyIn episode eleven we chat with Neil Lawrence from the University of Sheffield. We talk about the problems of privacy in the age of machine learning, and the responsibilities that come with using machine learning tools and making data more open. We learn about the Markov decision process (and what happens when you use it in the real world and it becomes a partially observable Markov decision process) and take a listener question about finding insights into features in the black boxes of deep learning.

interview by Robots Podcast   -   May 15, 2015
Image: MIT d'Arbeloff Laboratory
Image: MIT d’Arbeloff Laboratory

Link to audio file (19:55). Transcript below.

In this episode, Audrow Nash interviews Federico Parietti, a PhD candidate at the Massachusetts Institute of Technology, about his research on supernumerary robotic limbs that can be used in manufacturing and for rehabilitative purposes, among other uses.

by   -   May 7, 2015

Talking Machines

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.

interview by Robots Podcast   -   May 1, 2015

In this episode, Audrow Nash interviews Todd Hylton, Senior Vice President at Brain Corporation, about neuromorphic computers. They discuss the robotics development board bStem, which approximates a neuromorphic computer, as well as the eyeRover: a small balancing robot that demonstrates how the bStem can be used in mobile robots.

by   -   April 28, 2015
Baymax, Chris Atkeson and Hiro from Disney's Big Hero 6. Source: Chris Atkeson
Baymax, Chris Atkeson and Hiro from Disney’s Big Hero 6. Source: Chris Atkeson

Baymax, the lovable, inflatable robot star of Disney’s recent hit, Big Hero 6, is far from a movie fantasy. With their soft cushiony bodies, robots like Baymax have very real prospects as future care-givers, space-travellers and more. Robohub’s Helmut Hauser spoke to the man who inspired Baymax – Chris Atkeson, Professor of Robotics at Carnegie Mellon University – about the hard science behind soft robotics.

by   -   April 24, 2015

Kaggle  The Home of Data ScienceIn 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.)

interview by Robots Podcast   -   April 17, 2015
image: Soft Robotics Toolkit
image: Soft Robotics Toolkit

In this podcast, Ron Vanderkley speaks to Donal Holland of Harvard University about his team’s work on the Soft Robotics Toolkit.

by   -   April 9, 2015

Plates-Spinning-on-SticksIn episode eight we talk with Charles Sutton, a professor in the School of Informatics University of Edinburgh about computer programming and using machine learning to better understand how it’s done well.

interview by Robots Podcast   -   April 3, 2015


In this episode, Sabine Hauert interviews main stakeholders in European Robotics at the European Robotics Forum in Vienna.

by   -   March 26, 2015
Source: Automatic Statistician.
Source: Automatic Statistician.

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.

interview by Robots Podcast   -   March 20, 2015


In this episode, Audrow Nash interviews Christina Brester, from the Siberian State Aerospace University, about her research on a method to identify emotional state from speech. This method performs speech analysis with a self-adaptive, multi-objective, genetic algorithm for feature selection and uses a neural network to classify those features. In this interview, we’ll discuss exactly what that means, as well as the implications and future of this research.

by   -   March 17, 2015

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), who talk with us about the history (and future) of research on neural nets. 

interview by Robots Podcast   -   March 6, 2015

In this episode, Audrow Nash interviews Kurosh Madani from the University of Paris-EST Créteil (UPEC) about neural networks. The talk begins with an overview of neural networks before discussing their possible applications.

by   -   February 27, 2015

Livestream  Rodney Brooks  Abhinav Gupta  Andrew McAfee on AI and the rise of robots   RobohubLivestream of the Council of Foreign Relations’ Malcolm and Carolyn Wiener Annual Lecture on Science and Technology starting 02/27/2015 at 12:45 EST.

by   -   February 26, 2015

mind-AI-intelligence-learning-data-brainIn 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 take a look at the work of Daniel HsuAnimashree Anandkumar and Sham M. Kakade Plus we take a listener question about just where statistics stops and machine learning begins.

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