Talking Machines
129 episodes - English - Latest episode: almost 3 years ago - ★★★★★ - 140 ratingsTalking Machines is your window into the world of machine learning. Your hosts, Katherine Gorman and Neil Lawrence, bring you clear conversations with experts in the field, insightful discussions of industry news, and useful answers to your questions. Machine learning is changing the questions we can ask of the world around us, here we explore how to ask the best questions and what to do with the answers.
Hosted on Acast. See acast.com/privacy for more information.
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Episodes
Machine Learning in Healthcare and The AlphaGo Matches
March 10, 2016 16:30 - 48 minutes - 44.4 MBIn episode five of Season two Ryan walks us through variational inference, we put some listener questions about Go and how to play it to Andy Okun, president of the American Go Association (who is in Seoul South Korea watching the Lee Sedol/AlphaGo games). Plus we hear from Suchi Saria of Johns Hopkins about applying machine learning to understanding health care data. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.
AI Safety and The Legacy of Bletchley Park
February 25, 2016 15:24 - 48 minutes - 44.8 MBIn episode four of season two, we talk about some of the major issues in AI safety, (and how they’re not really that different from the questions we ask whenever we create a new tool.) One place you can go for other opinions on AI safety is the Future of Life Institute. We take a listener question about time series and we talk with Nick Patterson of the Broad Institute about everything from ancient DNA to Alan Turing. If you're as excited about AlphaGo playing Lee Sedol at Nick is, you can ge...
Robotics and Machine Learning Music Videos
February 11, 2016 16:00 - 40 minutes - 36.8 MBIn episode three of season two Ryan walks us through the Alpha Go results and takes a lister question about using Gaussian processes for classifications. Plus we talk with Michael Littman of Brown University about his work, robots, and making music videos. Also not to be missed, Michael’s appearance in the recent Turbotax ad! See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.
OpenAI and Gaussian Processes
January 28, 2016 18:20 - 35 minutes - 32.5 MBIn episode two of season two Ryan introduces us to Gaussian processes, we take a listener question on K-means. Plus, we talk with Ilya Sutskever the director of research for OpenAI. (For more from Ilya, you can listen to our season one interview with him.) See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.
Real Human Actions and Women in Machine Learning
January 14, 2016 11:35 - 59 minutes - 54.5 MBIn episode one of season two, we celebrate the 10th anniversary of Women in Machine Learning (WiML) with its co-founder (and our guest host for this episode) Hanna Wallach of Microsoft Research. Hanna and Jenn Wortman Vaughan, who also helped to found the event, tell us how about how the 2015 event went. Lillian Lee (Cornell), Raia Hadsell (Google Deepmind), Been Kim (AI2/University of Washington), and Corinna Cortes (Google Research) gave invited talks at the 2015 event. WiML also released a...
Open Source Releases and The End of Season One
November 22, 2015 20:37 - 40 minutes - 37.2 MBIn episode twenty four we talk with Ben Vigoda about his work in probabilistic programming (everything from his thesis, to his new company) Ryan talks about Tensor Flow and Autograd for Torch, some open source tools that have been recently releases. Plus we talk a listener question about the biggest thing in machine learning this year. This is the last episode in season one. We want to thanks all our wonderful listeners for supporting the show, asking us questions, and making season two possi...
Probabilistic Programming and Digital Humanities
November 05, 2015 21:45 - 48 minutes - 44.1 MBIn episode 23 we talk with David Mimno of Cornell University about his work in the digital humanities (and explore what machine learning can tell us about lady zombie ghosts and huge bodies of literature) Ryan introduces us to probabilistic programming and we take a listener question about knowledge transfer between math and machine learning. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.
Workshops at NIPS and Crowdsourcing in Machine Learning
October 22, 2015 12:53 - 47 minutes - 43.7 MBIn episode twenty two we talk with Adam Kalai of Microsoft Research New England about his work using crowdsourcing in Machine Learning, the language made of shapes of words, and New England Machine Learning Day. We take a look at the workshops being presented at NIPS this year, and we take a listener question about changing the number of features your data has. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.
Machine Learning Mastery and Cancer Clusters
October 08, 2015 13:30 - 26 minutes - 24.5 MBIn episode twenty one we talk with Quaid Morris of the University of Toronto, who is using machine learning to find a better way to treat cancers. Ryan introduces us to expectation maximization and we take a listener question about how to master machine learning. See omnystudio.com/listener for privacy information. Hosted on Acast. See acast.com/privacy for more information.
Data from Video Games and The Master Algorithm
September 24, 2015 21:55 - 46 minutes - 42.4 MBIn episode 20 we chat with Pedro Domingos of the University of Washington, he's just published a book The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World. We get some insight into Linear Dynamical Systems which the Datta Lab at Harvard Medical School is doing some interesting work with. Plus, we take a listener question about using video games to generate labeled data (spoiler alert, it's an awesome idea!)We're in the final hours of our Fundraising Camp...
Strong AI and Autoencoders
September 10, 2015 17:00 - 36 minutes - 33 MBIn episode nineteen we chat with Hugo Larochelle about his work on unsupervised learning, the International Conference on Learning Representations (ICLR), and his teaching style. His Youtube courses are not to be missed, and his twitter feed @Hugo_Larochelle is a great source for paper reviews. Ryan introduces us to autoencoders (for more, turn to the work of Richard Zemel) plus we tackle the question of what is standing in the way of strong AI. Talking Machines is beginning development of se...
Active Learning and Machine Learning in Neuroscience
August 27, 2015 15:12 - 53 minutes - 49.3 MBIn episode eighteen we talk with Sham Kakade, of Microsoft Research New England, about his expansive work which touches on everything from neuroscience to theoretical machine learning. Ryan introduces us to active learning (great tutorial here) and we take a question on evolutionary algorithms. Today we're announcing that season two of Talking Machines is moving into development, but we need your help! In order to raise funds, we've opened the show up to sponsorship and started a Kickstarter ...
Machine Learning in Biology and Getting into Grad School
August 13, 2015 17:07 - 48 minutes - 44.4 MBIn episode seventeen we talk with Jennifer Listgarten of Microsoft Research New England about her work using machine learning to answer questions in biology. Recently, With her collaborator Nicolo Fusi, she used machine learning to make CRISPR more efficient and correct for latent population structure in GWAS studies. We take a question from a listener about the development of computational biology and Ryan gives us some great advice on how to get into grad school (Spoiler alert: apply to th...
Machine Learning for Sports and Real Time Predictions
July 30, 2015 15:06 - 29 minutes - 26.7 MBIn episode sixteen we chat with Danny Tarlow of Microsoft Research Cambridge (in the UK not MA). Danny (along with Chris Maddison and Tom Minka) won best paper at NIPS 2014 for his paper A* Sampling. We talk with him about his work in applying machine learning to sports and politics. Plus we take a listener question on making real time predictions using machine learning, and we demystify backpropagation. You can use Torch, Theano or Autograd to explore backprop more. See omnystudio.com/listen...
Really Really Big Data and Machine Learning in Business
July 16, 2015 16:57 - 23 minutes - 21.8 MBIn episode fifteen we talk with Max Welling, of the University of Amsterdam and University of California Irvine. We talk with him about his work with extremely large data and big business and machine learning. Max was program co-chair for NIPS in 2013 when Mark Zuckerberg visited the conference, an event which Max wrote very thoughtfully about. We also take a listener question about the relationship between machine learning and artificial intelligence. Plus, we get an introduction to change p...
Solving Intelligence and Machine Learning Fundamentals
July 02, 2015 21:31 - 30 minutes - 27.7 MBIn episode fourteen we talk with Nando de Freitas. He’s a professor of Computer Science at the University of Oxford and a senior staff research scientist Google DeepMind. Right now he’s focusing on solving intelligence. (No biggie) Ryan introduces us to anchor words and how they can help us expand our ability to explore topic models. Plus, we take a question about the fundamentals of tackling a problem with machine learning. See omnystudio.com/listener for privacy information. Hosted on Aca...
Working With Data and Machine Learning in Advertising
June 18, 2015 16:35 - 39 minutes - 35.9 MBIn episode thirteen we talk with Claudia Perlich, Chief Scientist at Dstillery. We talk about her work using machine learning in digital advertising and her approach to data in competitions. We take a look at information leakage in competitions after ImageNet Challenge this year. The New York Times covered the events, and Neil Lawrence has been writing thoughtfully about it and its impact. Plus, we take a listener question about trends in data size. See omnystudio.com/listener for privacy inf...
The Economic Impact of Machine Learning and Using The Kernel Trick on Big Data
June 04, 2015 13:57 - 40 minutes - 37.2 MBIn episode twelve we talk with Andrew Ng, Chief Scientist at Baidu, about how speech recognition is going to explode the way we use mobile devices and his approach to working on the problem. We also discuss why we need to prepare for the economic impacts of machine learning. We’re introduced to Random Features for Large-Scale Kernel Machines, and talk about how using this twist on the Kernel trick can help you dig into big data. Plus, we take a listener question about the size of computing po...
How We Think About Privacy and Finding Features in Black Boxes
May 21, 2015 19:46 - 33 minutes - 30.9 MBIn 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, the responsibilities that come with using ML 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. See omnys...
Interdisciplinary Data and Helping Humans Be Creative
May 07, 2015 16:32 - 34 minutes - 31.4 MBIn 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
April 23, 2015 14:31 - 38 minutes - 35.2 MBIn 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/li...
Spinning Programming Plates and Creative Algorithms
April 09, 2015 11:18 - 35 minutes - 32.3 MBOn 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 al...
The Automatic Statistician and Electrified Meat
March 26, 2015 14:15 - 45 minutes - 41.8 MBIn 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 (b...
The Future of Machine Learning from the Inside Out
March 13, 2015 22:16 - 28 minutes - 25.9 MBWe 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 qu...
The History of Machine Learning from the Inside Out
February 26, 2015 16:24 - 32 minutes - 29.9 MBIn 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...
Using Models in the Wild and Women in Machine Learning
February 12, 2015 15:40 - 45 minutes - 41.3 MBIn 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 aca...
Common Sense Problems and Learning about Machine Learning
January 29, 2015 14:26 - 40 minutes - 37.5 MBOn 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...
Machine Learning and Magical Thinking
January 15, 2015 13:52 - 35 minutes - 32.2 MBToday 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 prioritie...
Hello World!
January 01, 2015 18:09 - 41 minutes - 38 MBIn 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 UM...