Data Skeptic

The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.

https://dataskeptic.com

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      The Imitation Game


      This week on Data Skeptic, we begin with a skit to introduce the topic of this show: The Imitation Game. We open with a scene in the distant future. The year is 2027, and a company called Shamony is announcing their new product, Ada, the most advanced...


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         1h0m
       
       

      Eugene Goostman


      In this episode, Kyle shares his perspective on the chatbot Eugene Goostman which (some claim) "passed" the Turing Test. As a second topic Kyle also does an intro of the Winograd Schema Challenge.


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         17m
       
       

      The Theory of Formal Languages


      In this episode, Kyle and Linhda discuss the theory of formal languages. Any language can (theoretically) be a formal language. The requirement is that the language can be rigorously described as a set of strings which are considered part of the...


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         23m
       
       

      The Loebner Prize


      The Loebner Prize is a competition in the spirit of the Turing Test.  Participants are welcome to submit conversational agent software to be judged by a panel of humans.  This episode includes interviews with Charlie Maloney, a judge in the...


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         33m
       
       

      Chatbots


      In this episode, Kyle chats with Vince from iv.ai and Heather Shapiro who works on the Microsoft Bot Framework. We solicit their advice on building a good chatbot both creatively and technically. Our sponsor today is Warby Parker.


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         27m
       
       

      The Master Algorithm


      In this week’s episode, Kyle Polich interviews Pedro Domingos about his book, The Master Algorithm: How the quest for the ultimate learning machine will remake our world. In the book, Domingos describes what machine learning is doing for...


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       2018-03-16  46m
       
       

      The No Free Lunch Theorems


      What's the best machine learning algorithm to use? I hear that XGBoost wins most of the Kaggle competitions that aren't won with deep learning. Should I just use XGBoost all the time? That might work out most of the time in practice, but a proof...


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       2018-03-09  27m
       
       

      ML at Sloan Kettering Cancer Center


      For a long time, physicians have recognized that the tools they have aren't powerful enough to treat complex diseases, like cancer. In addition to data science and models, clinicians also needed actual products — tools that physicians and...


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       2018-03-02  38m
       
       

      Optimal Decision Making with POMDPs


      In a previous episode, we discussed Markov Decision Processes or MDPs, a framework for decision making and planning. This episode explores the generalization Partially Observable MDPs (POMDPs) which are an incredibly general framework that describes...


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       2018-02-23  18m
       
       

      AI Decision-Making


      Making a decision is a complex task. Today's guest Dongho Kim discusses how he and his team at Prowler has been building a platform that will be accessible by way of APIs and a set of pre-made scripts for autonomous decision making based on...


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       2018-02-16  42m