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    Human Factors in Machine Intelligence with James Guszcza

    As you all know, a few weeks ago, I spent some time in SF at the Artificial Intelligence Conference. While there, I sat down with James Guszcza, US Chief Data Scientist at Deloitte Consulting to talk about human factors in machine intelligence. James was in San Francisco to give a talk at the O’Reilly AI Conference on “Why AI needs human-centered design.”

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    Human Factors in Machine Intelligence with James Guszcza
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    I sat down with James Guszcza, US Chief Data Scientist at Deloitte Consulting to talk about human factors in machine intelligence. We explored the many reasons why the human element is so important in ML and AI, along with useful ways to build algorithms and models that reflect this human element, while avoiding out problems like group-think and bias.

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    Intel Nervana Devcloud with Naveen Rao & Scott Apeland
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    In this episode, I talk to Naveen Rao, VP and GM of Intel’s AI Products Group, and Scott Apeland, director of Intel’s Developer Network. It’s been a few months since we last spoke to Naveen, so he gives us a quick update on what Intel’s been up to and we discuss his perspective on some…

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    AI-Powered Conversational Interfaces with Paul Tepper
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    My guest for this show is Paul Tepper, worldwide head of cognitive innovation and product manager for machine learning & AI at Nuance Communications. We covered a bunch of topics, like voice UI design, behavioral biometrics and a ton of other interesting things that Nuance has in the works.

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    Topological Data Analysis with Gunnar Carlsson
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    My guest for this show is Gunnar Carlsson, professor emeritus of mathematics at Stanford University and president and co-founder of machine learning startup Ayasdi.

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    ML Use Cases at Think Big Analytics with Mo Patel and Laura Frølich
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    This time around, I speak with Mo Patel, practice director of AI & deep learning and Laura Frølich, data scientist, of Think Big Analytics. Mo and Laura joined me at the AI conference after their session on “Training vision models with public transportation datasets.”

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    Ray: A Distributed Computing Platform for Reinforcement Learning with Ion Stoica
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    I talk with Ion Stoica, professor of computer science & director of the RISE Lab at UC Berkeley. We dive into Ray, a new distributed computing platform for RL, as well as RL generally, along with some of the other projects RISE Lab is working on, like Clipper & Tegra.

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    Bayesian Optimization for Hyperparameter Tuning with Scott Clark
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    This week I catch up with Scott Clark, Co-Founder and CEO of Sigopt, a company whose software is focused on automatically tuning your model’s parameters through Bayesian optimization.

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    Symbolic and Sub-Symbolic Natural Language Processing with Jonathan Mugan
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    Like last week’s interview with Bruno Goncalves, this week’s interview was also recorded at the last O’Reilly AI Conference back in New York in June. Also like last week’s show, this week’s is also focused on Natural Language Processing and I think you’ll enjoy it. I’m joined by Jonathan Mugan, co-founder and CEO of Deep…

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    Word2Vec & Friends with Bruno Goncalves
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    This week i’m bringing you an interview from Bruno Goncalves, a Moore-Sloan Data Science Fellow at NYU. As you’ll hear in the interview, Bruno is a longtime listener of the podcast. We were able to connect at the NY AI conference back in June after I noted on a previous show that I was interested…

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    Evolutionary Algorithms in Machine Learning with Risto Miikkulainen
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    My guest this week is Risto Miikkulainen, professor of computer science at UT-Austin and vice president of Research at Sentient Technologies. Risto came locked and loaded to discuss a topic that we’ve received a ton of requests for — evolutionary algorithms.

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    Agile Machine Learning at Walmart with Jennifer Prendki
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    My guest this week is Jennifer Prendki, former senior data science manager and principal data scientist at Walmart Labs, since moved on to become head of data science at Atlassian. We focus on some of the practices she helped develop and implement at Walmart around the measurement and management of and more generally, building agile processes and teams for, machine learning.

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    LSTM’s, plus a Deep Learning History Lesson with Jürgen Schmidhuber
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    This week’s guest is Jürgen Schmidhuber, Scientific Director of IDSIA in Switzerland. We talked a bunch about his work on neural networks, especially LSTM’s and along the way, Jurgen walks us through a deep learning history lesson that spans 50+ years.

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