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Sam Charrington

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Sam Charrington
Word2Vec & Friends with Bruno Gonçalves - TWiML Talk #48

Sep 19, 2017 - 00:33:43

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 in learning more about word2vec. Bruno graciously agreed to come on the show and walk us through an overview of word embeddings, word2vec and related ideas. He provides a great overview of not only word2vec, related NLP concepts such as Skip Gram, Continuous Bag of Words, Node2Vec and TFIDF. Notes for this show can be found at twimlai.com/talk/48.

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Sam Charrington
Evolutionary Algorithms in Machine Learning with Risto Miikkulainen - TWiML Talk #47

Sep 11, 2017 - 01:00:40

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. During our talk we discuss some of the things Sentient is working on in the financial services and retail fields, and we dig into the technology behind it, evolutionary algorithms, which is also the focus of Risto’s research at UT. I really enjoyed this interview and learned a ton, and I’m sure you will too! Notes for this show can be found at twimlai.com/talk/47.

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Sam Charrington
Agile Machine Learning with Jennifer Prendki - TWiML Talk #46

Sep 5, 2017 - 00:50:46

My guest this week is Jennifer Prendki. That name might sound familiar, as she was one of the great speakers from my Future of Data Summit back in May. At the time, Jennifer was senior data science manager and principal data scientist at Walmart Labs, but she's since moved on to become head of data science at Atlassian. Back at the summit, Jennifer gave an awesome talk on what she calls Data Mixology, the slides for which you can find on the show notes page. My conversation with Jennifer begins with a recap of that talk. After that, we shift our focus to some of the practices she helped develop and implement at Walmart around the measurement and management of machine learning models in production, and more generally, building agile processes and teams for machine learning. The notes for this show can be found at twimlai.com/talk/46

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Sam Charrington
LSTMs, Plus a Deep Learning History Lesson with Jürgen Schmidhuber - TWiML Talk #44

Aug 28, 2017 - 01:06:24

This week we have a very special interview to share with you! Those of you who’ve been receiving my newsletter for a while might remember that while in Switzerland last month, I had the pleasure of interviewing Jurgen Schmidhuber, in his lab IDSIA, which is the Dalle Molle Institute for Artificial Intelligence Research in Lugano, Switzerland, where he serves as Scientific Director. In addition to his role at IDSIA, Jurgen is also Co-Founder and Chief Scientist of NNaisense, a company that is using AI to build large-scale neural network solutions for “superhuman perception and intelligent automation.” Jurgen is an interesting, accomplished and in some circles controversial figure in the AI community and we covered a lot of very interesting ground in our discussion, so much so that I couldn't truly unpack it all until I had a chance to sit with it after the fact. We talked a bunch about his work on neural networks, especially LSTM’s, or Long Short-Term Memory networks, which are a key innovation behind many of the advances we’ve seen in deep learning and its application over the past few years. Along the way, Jurgen walks us through a deep learning history lesson that spans 50+ years. It was like walking back in time with the 3 eyed raven. I know you’re really going to enjoy this one, and by the way, this is definitely a nerd alert show! For the show notes, visit twimlai.com/talk/44

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Sam Charrington
Machine Teaching for Better Machine Learning with Mark Hammond - TWiML Talk #43

Aug 21, 2017 - 01:09:00

Today’s show, which concludes the first season of the Industrial AI Series, features my interview with Bonsai co-founder and CEO Mark Hammond. I sat down with Mark at Bonsai HQ a few weeks ago and we had a great discussion while I was there. We touched on a ton of subjects throughout this talk, including his starting point in Artificial intelligence, how Bonsai came about & more. Mark also describes the role of what he calls “machine teaching” in delivering practical machine learning solutions, particularly for enterprise or industrial AI use cases. This was one of my favorite conversations, I know you’ll enjoy it! The notes for this show can be found at twimlai.com/talk/43

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Sam Charrington
Marrying Physics-Based and Data-Driven ML Models with Josh Bloom - TWiML Talk #42

Aug 14, 2017 - 00:55:33

Recently I had a chance to catch up with a friend and friend of the show, Josh Bloom, vice president of data & analytics at GE Digital. If you’ve been listening for a while, you already know that Josh was on the show around this time last year, just prior to the acquisition of his company Wise.io by GE Digital. It was great to catch up with Josh on his journey within GE, and the work his team is doing around Industrial AI, now that they’re part of the one of the world’s biggest industrial companies. We talk about some really interesting things in this show, including how his team is using autoencoders to create training datasets, and how they incorporate knowledge of physics and physical systems into their machine learning models. The notes for this show can be found at twimlai.com/talk/42.

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Sam Charrington
Cognitive Biases in Data Science with Drew Conway - TWiML Talk #39

Aug 5, 2017 - 00:36:50

This show features my interview with Drew Conway, whose Wrangle keynote could have been called “Confessions of a CIA Data Scientist.” The focus of our interview, and of Drew’s presentation, is an interesting set of observations he makes about the role of cognitive biases in data science. If your work involves making decisions or influencing behavior based on data-driven analysis--and it probably does or will--you’re going to want to hear what he has to say. A quick note before we dive in: As is the case with my other field recordings, there’s a bit of unavoidable background noise in this interview. Sorry about that! The show notes for this episode can be found at https://twimlai.com/talk/39

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Sam Charrington
Data Pipelines at Zymergen with Airflow with Erin Shellman - TWiML Talk #41

Aug 5, 2017 - 00:36:13

The show you’re listening to features my interview with Erin Shellman. Erin is a statistician and data science manager with Zymergen, a company using robots and machine learning to engineer better microbes. If you’re wondering what exactly that means, I was too, and we talk about it in the interview. Our conversation focuses on Zymergen’s use of Apache Airflow, an open-source data management platform originating at Airbnb, that Erin and her team uses to create reliable, repeatable data pipelines for its machine learning applications. A quick note before we dive in: As is the case with my other field recordings, there’s a bit of unavoidable background noise in this interview. Sorry about that! The show notes for this episode can be found at https://twimlai.com/talk/41

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Sam Charrington
Web Scale Engineering for Machine Learning with Sharath Rao - TWiML Talk #40

Aug 4, 2017 - 00:32:06

The show you’re about to listen to features my interview with Sharath Rao, Tech Lead Manager & Machine Learning Engineer at Instacart I reached out to Sharath about being on the show and was blown away when he replied that not only had he heard about the show, but that he was a fan and an avid listener. My conversation with him digs into some of the practical lessons and patterns he’s learned by building production-ready, web-scale data products based on machine learning models, including the search and recommendation systems at Instacart. We also spend a few minutes discussing our upcoming TWiML Paper Reading Meetup! A quick note before we dive in: As is the case with my other field recordings, there’s a bit of unavoidable background noise in this interview. Sorry about that! The show notes for this episode can be found at https://twimlai.com/talk/40.

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Sam Charrington
Deep Learning for Warehouse Operations with Calvin Seward - TWiML Talk #38

Jul 31, 2017 - 00:48:16

This week, I’m happy to bring you my interview with Calvin Seward, a research scientist with Berlin, Germany based Zalando. While our American listeners might not know the name Zalando, they’re one of the largest e-commerce companies in Europe with a focus on fashion and shoes. Calvin is a research scientist there, while also pursuing his doctorate studies at Johannes Kepler University in Linz, Austria. Our discussion, which continues our Industrial AI series, focuses on how Calvin’s team tackled an interesting warehouse optimization problem using deep learning. Calvin also gives his thoughts on the distinction between AI and ML, and the four P’s that he focuses on: Prestige, Products, Paper, and Patents. The notes for this show can be found at https://twimlai.com/talk/38.

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Sam Charrington
Deep Robotic Learning with Sergey Levine - TWiML Talk #37

Jul 24, 2017 - 00:49:12

This week we continue our Industrial AI series with Sergey Levine, an Assistant Professor at UC Berkeley whose research focus is Deep Robotic Learning. Sergey is part of the same research team as a couple of our previous guests in this series, Chelsea Finn and Pieter Abbeel, and if the response we’ve seen to those shows is any indication, you’re going to love this episode! Sergey’s research interests, and our discussion, focus in on include how robotic learning techniques can be used to allow machines to acquire autonomously acquire complex behavioral skills. We really dig into some of the details of how this is done and I found that our conversation filled in a lot of gaps for me from the interviews with Pieter and Chelsea. By the way, this is definitely a nerd alert episode! Notes for this show can be found at twimlai.com/talk/37

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Sam Charrington
Smart Buildings & IoT with Yodit Stanton - TWiML Talk #36

Jul 17, 2017 - 00:56:10

After a brief hiatus, the Industrial AI Series is making its triumphant return! Our guest this week is Yodit Stanton, a self-described Data Nerd, and the Founder & CEO of Opensensors.io. OpenSensors.io is a real-time data exchange for IoT, that enables anyone to publish and subscribe to real time open data in order to build higher order smart systems and better understand the world around them. Our discussion focuses on Smart Buildings and how they’re enabled by IoT and machine learning techniques. The notes for this show can be found at twimlai.com/talk/36

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Sam Charrington
Enhancing Customer Experiences With Emotional AI with Rana El Kaliouby - TWiML Talk #35

Jul 5, 2017 - 00:33:40

My guest for this show is Rana el Kaliouby. Rana is co-founder and CEO of Affectiva. Affectiva, as Rana puts it, "is on a mission to humanize technology by bringing in artificial emotional intelligence". If you liked my conversation about Emotional AI with Pascale Fung from last year’s O’Reilly AI conference, you’re going to love this one. My conversation with Rana kind of picks up where the previous one left off, with a focus on how her company is bringing Artificial Emotional Intelligence services to market. Rana and her team have developed a machine learning / computer vision platform that can use the camera on any device to read your facial expressions in real time, then maps it to an emotional state. Using data science to mine the world’s largest emotion repository, Affectiva has collected over 5.5 million pieces of emotional expression data to date, from laptop, driving, cellular interactions. Understanding the importance of personal privacy, Rana and her Co-Founder Rosalind Wright Picard have vowed to shy away from partnerships that would subject consumers to unknowing surveillance, a commendable effort. The notes for this show can be found at https://twimlai.com/talk/35

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Sam Charrington
Intel Nervana Update + Productizing AI Research with Naveen Rao And Hanlin Tang - TWiML Talk #31

Jul 5, 2017 - 00:42:21

I talked about Intel’s acquisition of Nervana Systems on the podcast when it happened almost a year ago, so I was super excited to have an opportunity to sit down with Nervana co-founder Naveen Rao, who now leads Intel’s newly formed AI Products Group, for the first show in our O'Reilly AI series. We talked about how Intel plans to extend its leadership position in general purpose compute into the AI realm by delivering silicon designed specifically for AI, end-to-end solutions including the cloud, enterprise data center, and the edge; and tools that let customers quickly productize and scale AI-based solutions. I also spoke with Hanlin Tang, an algorithms engineer at Intel’s AIPG, about two tools announced at the conference: version 2.0 of Intel Nervana’s deep learning framework Neon and Nervana Graph, a new toolset for expressing and running deep learning applications as framework and hardware-independent computational graphs. Nervana Graph in particular sounds like a very interesting project, not to mention a smart move for Intel, and I’d encourage folks to take a look at their Github repo. The show notes for this page can be found at https://twimlai.com/talk/31

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Sam Charrington
Expressive AI - Generated Music With Google's Performance RNN - Doug Eck - TWiML Talk #32

Jul 6, 2017 - 00:46:30

My guest for this second show in our O’Reilly AI series is Doug Eck of Google Brain. Doug did a keynote at the O’Reilly conference on Magenta, Google’s project for melding machine learning and the arts. Magenta’s goal is to produce open-source tools and models that help people in their personal creative processes. Doug’s research starts with using so-called “generative” machine learning models to create engaging media. Additionally, he is working on how to bring other aspects of the creative process into play. We talk about the newly announced Performance RNN project, which uses neural networks to create expressive, AI-generated music. We also touch on QuickDraw, a project by Google AI Experiments, in which users as Doug describes it, “play Pictionary” with a visual classifier. We dig into what he foresees as possibilities for Magenta, machine learning models eventually developing storylines, generative models for media and creative coding. The notes for this episode can be found at https://twimlai.com/talk/32.

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Sam Charrington
The Power Of Probabilistic Programming with Ben Vigoda - TWiML Talk #33

Jul 5, 2017 - 00:42:43

My guest for this third episode in the O'Reilly AI series is Ben Vigoda. Ben is the founder and CEO of Gamalon, a DARPA-funded startup working on Bayesian Program Synthesis. We dive into what exactly this means and how it enables what Ben calls idea learning in the show. Gamalon's first application structures unstructured data — input a paragraph or phrase of unstructured text and output a structured spreadsheet/database row or API call. This can be applicable to a wide range of data challenges, including enterprise product and customer information, AI or digital assistant, and many others. Before Gamalon, Ben was co-founder and CEO of Lyric Semiconductor, Inc., which created the first microprocessor architectures dedicated for statistical machine learning. The company was based on his PhD thesis at MIT and acquired by Analog Devices. In today’s talk we are discussing probabilistic programming, his new approach to deep learning, posterior distribution, and the difference between sampling methods and variational methods and how solvers work in the system. Nerd alert: We go pretty deep in this discussion. The notes for this show can be found at https://twimlai.com/talk/33

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Sam Charrington
Video Object Detection At Scale with Reza Zadeh - TWiML Talk #34

Jul 5, 2017 - 00:52:41

My guest for the fourth show in the O'Reilly AI Series is Reza Zadeh. Reza is an adjunct professor of computational mathematics at Stanford University and founder and CEO of the startup Matroid. Reza has a background in machine translation and distributed machine learning, along with having helped build Apache Spark, and the"Who to Follow" feature on Twitter, which is based on a chapter from his PhD thesis. Our conversation focused on some of the challenges and approaches to scaling deep learning, both in general and in the context of his company’s video object detection service. Our conversation focused on some of the challenges and approaches to scaling deep learning, both in general and in the context of his company’s video object detection service. We also spoke about the advancement of computer vision technologies, using CPU's, GPU's, the upcoming shift to TPU's and we get below the surface on Apache Spark.

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Sam Charrington
Natural Language Understanding for Amazon Alexa with Zornitsa Kozareva - TWiML Talk #30

Jun 29, 2017 - 00:56:53

Our guest this week is Zornitsa Kozareva, Manager of Machine Learning with Amazon Web Services Deep Learning, where she leads a group focused on natural language processing and dialogue systems for products like Alexa and Lex, the latter of which we introduce in the podcast. We spend most of our time talking through the architecture of modern Natural Language Understanding systems, including the role of deep learning, and some of the various ways folks are working to overcome the challenges in this field, such as understanding human intent. If you’re interested in this field she mentions the AWS Chatbot Challenge, which you’ve still got a couple more weeks to participate in. The notes for this show can be found at twimlai.com/talk/30.

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Sam Charrington
Robotic Perception and Control with Chelsea Finn - TWiML Talk #29

Jun 23, 2017 - 00:56:08

This week we continue our series on industrial applications of machine learning and AI with a conversation with Chelsea Finn, a PhD student at UC Berkeley. Chelsea’s research is focused on machine learning for robotic perception and control. Despite being early in her career, Chelsea is an accomplished researcher with more than 14 published papers in the past 2 years, on subjects like Deep Visual Foresight , Model-Agnostic Meta-Learning and Visuomotor Learning to name a few, all of which we discuss in the show, along with topics like zero-shot, one-shot and few-shot learning. I’d also like to give a shout out to Shreyas, a listener who wrote in to request that we interview a current PhD student about their journey and experiences. Chelsea and I spend some time at the end of the interview talking about this, and she has some great advice for current and prospective PhD students but also independent learners in the field. During this part of the discussion I wonder out loud if any listeners would be interested in forming a virtual paper reading club of some sort. I’m not sure yet exactly what this would look like, but please drop a comment in the show notes if you’re interested. I'm going to once again deploy the Nerd Alert for this episode; Chelsea and I really dig deep into these learning methods and techniques, and this conversation gets pretty technical at times, to the point that I had a tough time keeping up myself. The notes for this page can be found at twimlai.com/talk/29

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Sam Charrington
Reinforcement Learning Deep Dive with Pieter Abbeel - TWiML Talk #28

Jun 16, 2017 - 00:54:36

This week our guest is Pieter Abbeel, Assistant Professor at UC Berkeley, Research Scientist at OpenAI, and Cofounder of Gradescope. Pieter has an extensive background in AI research, going way back to his days as Andrew Ng’s first PhD student at Stanford. His research today is focused on deep learning for robotics. During this conversation, Pieter and I really dig into reinforcement learning, a technique for allowing robots (or AIs) to learn through their own trial and error. Nerd alert!! This conversation explores cutting edge research with one of the leading researchers in the field and, as a result, it gets pretty technical at times. I try to uplevel it when I can keep up myself, so hang in there. I promise that you’ll learn a ton if you keep with it. The notes for this show can be found at twimlai.com/talk/28

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Sam Charrington
Intelligent Autonomous Robots with Ilia Baranov - TWiML Talk #27

Jun 9, 2017 - 00:55:47

Our first guest in the Industrial AI series is Ilia Baranov, engineering manager at Clearpath Robotics. Ilia is responsible for setting the engineering direction for all of Clearpath’s research platforms. Ilia likes to describe his role at the company as “both enabling and preventing the robot revolution.” He’s a longtime contributor to the Open Source Robotics Community and ROS, an open source robotic operating system. He is the also the managing engineer of the PR2 support team at Clearpath and leads the technical demonstration group. In our conversation we cover a lot of ground, including what it really means to field autonomous robots, the use of autonomous robots in research and industrial environments, the different approaches and challenges to achieving autonomy, and much more! The notes for this show are available at twimlai.com/talk/27, and for more information on the Industrial AI Series, visit twimlai.com/IndustrialAI.

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Sam Charrington
Global AI Trends with Ben Lorica - TWiML Talk #26

Jun 2, 2017 - 00:57:47

This week I’ve invited my friend Ben Lorica onto the show. Ben is Chief Data Scientist for O’Reilly Media, and Program Director of Strata Data & the O'Reilly A.I. conference. Ben has worked on analytics and machine learning in the finance and retail industries, and serves as an advisor for nearly a dozen startups. In his role at O’Reilly he’s responsible for the content for 7 major conferences around the world each year. In the show we discuss all of that, touching on how publishers can take advantage of machine learning and data mining, how the role of “data scientist” is evolving and the emergence of the machine learning engineer, and a few of the hot technologies, trends and companies that he’s seeing arise around the world. The notes for this show can be found at twimlai.com/talk/26

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Sam Charrington
Offensive vs Defensive Data Science with Deep Varma - TWiML Talk #25

May 26, 2017 - 00:56:30

This week on the show my guest is Deep Varma, Vice President of Data Engineering at real estate startup Trulia. Deep has run data engineering teams in silicon valley for well over a decade, and is now responsible for the engineering efforts supporting Trulia’s Big Data Technology Platform, which encompasses everything from Data acquisition & management to Data Science & Algorithms. In the show we discuss all of that, with an emphasis on Trulia’s data engineering pipeline and their personalization platform, as well how they use computer vision, deep learning and natural language generation to deliver their product. Along the way, Deep offers great insights into what he calls offensive vs defensive data science, and the difference between data-driven decision making vs products. Another great interview, and i'm sure you’ll enjoy it. The notes for this show can be found at twimlai.com/talk/25 Subscribe! iTunes ➙ https://itunes.apple.com/us/podcast/this-week-in-machine-learning/id1116303051?mt=2 Soundcloud ➙ https://soundcloud.com/twiml Google Play ➙ http://bit.ly/2lrWlJZ Stitcher ➙ http://www.stitcher.com/s?fid=92079&refid=stpr RSS ➙ https://twimlai.com/feed Lets Connect! Twimlai.com ➙ https://twimlai.com/contact Twitter ➙ https://twitter.com/twimlai Facebook ➙ https://Facebook.com/Twimlai Medium ➙ https://medium.com/this-week-in-machine-learning-ai

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Sam Charrington
Reinforcement Learning: The Next Frontier of Gaming with Danny Lange - TWiML Talk #24

May 20, 2017 - 00:57:19

My guest on the show this week is Danny Lange, VP for Machine Learning & AI at video game technology developer Unity Technologies. Danny is well traveled in the world of ML and AI, and has had a hand in developing machine learning platforms at companies like Uber, Amazon and Microsoft. In this conversation we cover a bunch of topics, including How ML & AI are being used in gaming, the importance of reinforcement learning in the future of game development, the intersection between AI and AR/VR and the next steps in natural character interaction. The notes for this show can be found at twimlai.com/talk/24

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Sam Charrington
Integrating Psycholinguistics into AI with Dominique Simmons - TWiML Talk #23

May 12, 2017 - 01:02:16

I think you’re really going to enjoy today’s show. Our guest this week is Dominique Simmons, Applied research Scientist at AI tools vendor Dimensional Mechanics. Dominique brings an interesting background in Cognitive Psychology and psycholinguistics to her work and research in AI and, well, to this podcast. In our conversation, we cover the implications of cognitive psychology for neural networks and AI systems, and in particular how an understanding of human cognition impacts the development of AI models for media applications. We also discuss her research into multimodal training of AI models, and how our understanding of the human brain has influenced this work. We also explore the debate around the biological plausibility of machine learning and AI models. It was a great conversation.

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Sam Charrington
Deep Neural Nets for Visual Recognition with Matt Zeiler - TWiML Talk #22

May 4, 2017 - 00:24:19

Today we bring you our final interview from backstage at the NYU FutureLabs AI Summit. Our guest this week is Matt Zeiler. Matt graduated from the University of Toronto where he worked with deep learning researcher Geoffrey Hinton and went on to earn his PhD in machine learning at NYU, home of Yann Lecun. In 2013 Matt’s founded Clarifai, a startup whose cloud-based visual recognition system gives developers a way to integrate visual identification into their own products, and whose initial image classification algorithm achieved top 5 results in that year’s ImageNet competition. I caught up with Matt after his talk “From Research to the Real World”. Our conversation focused on the birth and growth of Clarifai, as well as the underlying deep neural network architectures that enable it. If you’ve been listening to the show for a while, you’ve heard me ask several guests how they go about evolving the architectures of their deep neural networks to enhance performance. Well, in this podcast Matt gives the most satisfying answer I’ve received to date by far. Check it out. I think you’ll enjoy it. The show notes can be found at twimlai.com/talk/22.

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Sam Charrington
Engineering the Future of AI with Ruchir Puri - TWiML Talk #21

Apr 27, 2017 - 00:25:06

Today we bring you the second of three interviews we did backstage from the NYU FutureLabs AI Summit, this time with Ruchir Puri. Ruchir is the Chief Architect at IBM Watson as well as an IBM Fellow. I caught up with Ruchir after his talk on “engineering the Future of AI for Businesses”. Our conversation focused on cognition and reasoning, and we explored what these concepts represent, how enterprises really want to consume them, and how IBM Watson seeks to deliver them. The show notes can be found at twimlai.com/talk/21.

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Sam Charrington
Selling AI to the Enterprise with Kathryn Hume - TWiML Talk #20

Apr 21, 2017 - 00:24:50

This week's guest is Kathryn Hume. Kathryn is the President of Fast Forward Labs, which is an independent machine intelligence research company that helps organizations accelerate their data science and machine intelligence capabilities. If Fast Forward Labs sounds familiar, that's because we had their founder, Hilary Mason on a few months ago. We’ll link to that in the show notes. My discussion with Kathryn focused on AI adoption within the enterprise. She shared several really interesting examples of the kinds of things she’s seeing enterprises do with machine learning and AI, and we discussed a few of the various challenges enterprises face and some of the lessons her company has learned in helping them. I really enjoyed our conversation and I know you will too! You can find the notes for todays show here: https://twimlai.com/talk/20

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Sam Charrington
From Particle Physics to Audio AI with Scott Stephenson - TWiML Talk #19

Apr 14, 2017 - 00:59:21

This week my guest is Scott Stephenson. Scott is co-Founder & CEO of Deepgram, which has developed an AI-based platform for indexing and searching audio and video. Scott and I cover a ton of interesting topics including applying machine learning techniques to particle physics, his time in a lab 2 miles below the surface of the earth, applying neural networks to audio, and the Deep Learning Framework Kur that his company open-sourced. The show notes can be found at twimlai.com/talk/19.

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Sam Charrington
(1/5) HelloVera - AI-Powered Customer Support - TWiML Talk #18

Apr 7, 2017 - 00:25:37

This week I'm on location at NYU/ffVC AI NexusLab startup accelerator, speaking with founders from the 5 companies in the program's inaugural batch. This interview is with HelloVera, a company applying artificial intelligence to the challenge of automating customer support experiences. The notes for this series can be found at https://twimlai.com/nexuslab. Thanks to Future Labs at NYU Tandon and ffVenture Capital for sponsoring the series!

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Sam Charrington
(2/5) Klustera - Location-Based Intelligence for Smarter Marketing - TWiML Talk #18

Apr 7, 2017 - 00:22:11

This week I'm on location at NYU/ffVC AI NexusLab startup accelerator, speaking with founders from the 5 companies in the program's inaugural batch. This interview is with Klustera, a company applying location-based intelligence and machine learning to help brands execute smarter marketing campaigns. The notes for this series can be found at twimlai.com/nexuslab. Thanks to Future Labs at NYU Tandon and ffVenture Capital for sponsoring the series!

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Sam Charrington
(3/5) Cambrian Intelligence - Using AI to Simplify the Programming of Robots - TWiML Talk #18

Apr 7, 2017 - 00:23:20

This week I'm on location at NYU/ffVC AI NexusLab startup accelerator, speaking with founders from the 5 companies in the program's inaugural batch. This interview is with Cambrian Intelligence, a company using AI to simplify the programming of industrial robots for the automotive industry. The notes for this series can be found at twimlai.com/nexuslab. Thanks to Future Labs at NYU Tandon and ffVenture Capital for sponsoring the series!

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Sam Charrington
(4/5) Behold.ai - Increasing Efficiency of Healthcare Insurance Billing with NLP - TWiML Talk #18

Apr 7, 2017 - 00:16:31

This week I'm on location at NYU/ffVC AI NexusLab startup accelerator, speaking with founders from the 5 companies in the program's inaugural batch. This interview is with Behold.ai, which uses computer vision and natural language processing techniques to bring efficiencies to the world of healthcare insurance billing. The notes for this series can be found at twimlai.com/nexuslab. Thanks to Future Labs at NYU Tandon and ffVenture Capital for sponsoring the series!

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Sam Charrington
(5/5) AlphaVertex - Creating a Worldwide Financial Knowledge Graph - TWiML Talk #18

Apr 7, 2017 - 00:26:14

This week I'm on location at NYU/ffVC AI NexusLab startup accelerator, speaking with founders from the 5 companies in the program's inaugural batch. This interview is with AlphaVertex, a FinTech startup creating a worldwide financial knowledge graph to help investors predict stock prices. The notes for this series can be found at twimlai.com/nexuslab. Thanks to Future Labs at NYU Tandon and ffVenture Capital for sponsoring the series!

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Sam Charrington
Interactive Machine Learning Systems with Alekh Agarwal - TWiML Talk #17

Mar 30, 2017 - 00:35:03

This week my guest is Alekh Agarwal. Alekh is a researcher with Microsoft Research whose research is focused on Interactive Machine Learning. In our discussion, Alekh and I discuss various aspects of this exciting area of research such as active learning, reinforcement learning, contextual bandits and more.

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Sam Charrington
Machine Learning in Cybersecurity with Evan Wright - TWiML Talk #16

Mar 24, 2017 - 01:05:31

This week my guest is Evan Wright, principal data scientist at cybersecurity startup Anomali. In my interview with Evan, he and I discussed about a number of topics surrounding the use of machine learning in cybersecurity. If Evan’s name sounds familiar, it’s because Evan was the winner of the O’Reilly Strata+Hadoop World ticket giveaway earlier this month. We met up at the conference last week and took advantage of the opportunity to record this show. Our conversation covers, among other topics, the three big problems in cybersecurity that ML can help out with, the challenges of acquiring ground truth in cybersecurity and some ways to accomplish it, and the use of decision trees, generative adversarial networks, and other algorithms in the field. The show notes can be found at twimlai.com/talk/16.

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Sam Charrington
Domain Knowledge in Machine Learning Models for Sustainability with Stefano Ermon - TWiML Talk #15

Mar 17, 2017 - 00:55:55

My guest this week is Stefano Ermon, Assistant Professor of Computer Science at Stanford University, and Fellow at Stanford’s Woods Institute for the Environment. Stefano and I met at the Re-Work Deep Learning Summit earlier this year, where he gave a presentation on Machine Learning for Sustainability. Stefano and I spoke about a wide range of topics, including the relationship between fundamental and applied machine learning research, incorporating domain knowledge in machine learning models, dimensionality reduction, and his interest in applying ML & AI to addressing sustainability issues such as poverty, food security and the environment. The show notes can be found at twimlai.com/talk/15.

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Sam Charrington
Scaling Deep Learning: Systems Challenges & More with Shubho Sengupta — TWiML Talk #14

Mar 10, 2017 - 01:13:58

This week my guest is Shubho Sengupta, Research Scientist at Baidu. I had the pleasure of meeting Shubho at the Rework Deep Learning Summit earlier this year, where he delivered a presentation on Systems Challenges for Deep Learning. We dig into this topic in the interview, and discuss a variety of issues including network architecture, productionalization, operationalization and hardware. The show notes can be found at twimlai.com/talk/14.

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Sam Charrington
Understanding Deep Neural Nets with Dr. James McCaffrey - TWiML Talk #13

Mar 3, 2017 - 01:18:34

My guest this week is Dr. James McCaffrey, research engineer at Microsoft Research. James and I cover a ton of ground in this conversation, including recurrent neural nets (RNNs), convolutional neural nets (CNNs), long short term memory (LSTM) networks, residual networks (ResNets), generative adversarial networks (GANs), and more. We also discuss neural network architecture and promising alternative approaches such as symbolic computation and particle swarm optimization. The show notes can be found at twimlai.com/talk/13.

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Sam Charrington
Brendan Frey - Reprogramming the Human Genome with AI - TWiML Talk #12

Feb 24, 2017 - 01:03:18

My guest this week is Brendan Frey, Professor of Engineering and Medicine at the University of Toronto and Co-Founder and CEO of the startup Deep Genomics. Brendan and I met at the Re-Work Deep Learning Summit in San Francisco last month, where he delivered a great presentation called “Reprogramming the Human Genome: Why AI is Needed.” In this podcast we discuss the application of AI to healthcare. In particular, we dig into how Brendan’s research lab and company are applying machine learning and deep learning to treating and preventing human genetic disorders. The show notes can be found at twimlai.com/talk/12

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Sam Charrington
Hilary Mason - Building AI Products - TWiML Talk #11

Jan 25, 2017 - 00:19:40

My guest this time is Hilary Mason. Hilary was one of the first “famous” data scientists. I remember hearing her speak back in 2011 at the Strange Loop conference in St. Louis. At the time she was Chief Scientist for bit.ly. Nowadays she’s running Fast Forward Labs, which helps organizations accelerate their data science and machine intelligence capabilities through a variety of research and consulting offerings. Hilary presented at the O'Reilly AI conference on “practical AI product development” and she shares a lot of wisdom on that topic in our discussion. The show notes can be found at twimlai.com/talk/11.

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Sam Charrington
Francisco Webber - Statistics vs Semantics for Natural Language Processing - TWiML Talk #10

Dec 3, 2016 - 00:49:23

My guest this time is Francisco Webber, founder and General Manager of artificial intelligence startup Cortical.io. Francisco presented at the O’Reilly AI conference on an approach to natural language understanding based on semantic representations of speech. His talk was called “AI is not a matter of strength but of intelligence.” My conversation with Francisco was a bit technical and abstract, but also super interesting. The show notes can be found at twimlai.com/talk/10.

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Sam Charrington
Pascale Fung - Emotional AI: Teaching Computers Empathy - TWiML Talk #9

Nov 8, 2016 - 00:34:50

My guest this time is Pascale Fung, professor of electrical & computer engineering at Hong Kong University of Science and Technology. Pascale delivered a presentation at the recent O'Reilly AI conference titled "How to make robots empathetic to human feelings in real time," and I caught up with her after her talk to discuss teaching computers to understand and respond to human emotions. We also spend some time talking about the (information) theoretical foundations of modern approaches to speech understanding. The notes for this show can be found at twimlai.com/talk/9.

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Sam Charrington
Diogo Almeida - Deep Learning: Modular in Theory, Inflexible in Practice - TWiML Talk #8

Oct 23, 2016 - 00:46:52

My guest this time is Diogo Almeida, senior data scientist at healthcare startup Enlitic. Diogo and I met at the O'Reilly AI conference, where he delivered a great presentation on in-the-trenches deep learning titled “Deep Learning: Modular in theory, inflexible in practice,” which we discuss in this interview. Diogo is also a past 1st place Kaggle competition winner, and we spend some time discussing the competition he competed in and the approach he took as well. The notes for this show can be found at twimlai.com/talk/8.

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Sam Charrington
Carlos Guestrin - Explaining the Predictions of Machine Learning Models - TWiML Talk #7

Oct 9, 2016 - 00:32:30

My guest this time is Carlos Guestrin, the Amazon professor of Machine Learning at the University of Washington. Carlos and I recorded this podcast at a conference, shortly after Apple's acquisition of his company Turi. Our focus for this podcast is the explainability of machine learning algorithms. In particular, we discuss some interesting new research published by his team at U of W. The notes for this show can be found at twimlai.com/talk/7.

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Sam Charrington
Angie Hugeback - Generating Training Data for Your ML Models - TWiML Talk #6

Sep 29, 2016 - 01:02:29

My guest this time is Angie Hugeback, who is principal data scientist at Spare5. Spare5 helps customers generate the high-quality labeled training datasets that are so crucial to developing accurate machine learning models. In this show, Angie and I cover a ton of the real-world practicalities of generating training datasets. We talk through the challenges faced by folks that need to label training data, and how to develop a cohesive system for achieving performing the various labeling tasks you’re likely to encounter. We discuss some of the ways that bias can creep into your training data and how to avoid that. And we explore the some of the popular 3rd party options that companies look at for scaling training data production, and how they differ. Spare5 has graciously sponsored this episode; you can learn more about them at spare5.com. The notes for this show can be found at twimlai.com/talk/6.

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Sam Charrington
Joshua Bloom - Machine Learning for the Stars & Productizing AI - TWiML Talk #5

Sep 22, 2016 - 01:30:06

My guest this time is Joshua Bloom. Josh is professor of astronomy at the University of California, Berkeley and co-founder and Chief Technology Officer of machine learning startup Wise.io. In this wide-ranging interview you’ll learn how Josh and his research group at Berkeley pioneered the use of machine learning for the analysis of images from robotic infrared telescopes. We discuss the founding of his company, Wise.io, which uses machine learning to help customers deliver better customer support. That wasn’t where the company started though, and you’ll hear why and how they evolved to serve this market. We talk about his company’s technology stack and data science pipeline in fair detail, and discuss some of the key technology decisions they’ve made in building their product. We also discuss some interesting open research challenges in machine learning and AI. The notes for this show can be found at twimlai.com/talk/5.

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Sam Charrington
Charles Isbell - Interactive AI, Plus Improving ML Education - TWiML Talk #4

Sep 10, 2016 - 01:08:29

My guest this time is Charles Isbell, Jr., Professor and Senior Associate Dean in the College of Computing at Georgia Institute of Technology. Charles and I go back a bit… in fact he’s the first AI researcher I ever met. His research focus is what he calls “interactive artificial intelligence,” a discipline of AI focused specifically on the interactions between AIs and humans. We explore what this means and some of the interesting research results in this field. One part of this discussion I found particularly interesting was the intersection between his AI research and marketing and behavioral economics. Beyond his research, Charles is well known in the ML and AI worlds for his popular Machine Learning course sequence on Udacity, which he teaches with Brown University professor Michael Littman, and for the Online Master’s of Science in Computer Science program that he helped launch at Georgia Tech. We also spend quite a bit of time talking about what’s really missing in machine learning education and how to make it more accessible. The notes for this show can be found at twimlai.com/talk/4.

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Sam Charrington
Xavier Amatriain - Engineering Practical Machine Learning Systems - TWiML Talk #3

Aug 29, 2016 - 00:57:20

My guest this time is Xavier Amatriain. Xavier is a former researcher who went on to lead the machine learning recommendations team at Netflix, and is now the vice president of engineering at Quora, the Q&A site. We spend quite a bit of time digging into each of these experiences in the interview. Here are just a few of the things we cover in our discussion: Why Netflix invested $1 million in the Netflix Prize, but didn’t use the winning solution; What goes into engineering practical machine learning systems; The problem Xavier has with the deep learning hype; And, what the heck is a multi-arm bandit and how can it help us. The notes for this show can be found at https://twimlai.com/talk/3.

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Sam Charrington
Siraj Raval - How to Build Confidence as an ML Developer - TWiML Talk #2

Aug 21, 2016 - 00:41:46

Siraj Raval is a machine learning hacker and teacher whose machine learning for hackers and fresh machine learning youtube series are fun, informative, high energy and practical ways to learn about a ton of machine learning and AI topics. I had a chance to catch up with Siraj in San Francisco recently, and we had a great discussion. Siraj has great advice on how to learn machine learning and build confidence as a machine learning developer, how to research and formulate projects, who to follow on Machine Learning twitter, and much more. The notes for this show can be found at https://twimlai.com/talk/2

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Sam Charrington
This Week in ML & AI – 8/12/16: Another huge machine learning acquisition + AI in the Olympics

Aug 15, 2016 - 00:23:36

This Week in Machine Learning & AI brings you the week’s most interesting and important stories from the world of machine learning and artificial intelligence. This week we discuss Intel’s latest deep learning acquisition, AI in the Olympics, and how you can win a free ticket to the O’Reilly AI Conference in New York City. Plus a bunch more on This Week in Machine Learning & AI. The notes for this show can be found at twimlai.com/13.

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Sam Charrington
This Week in ML & AI – 8/5/16: Apple Acquires Turi, the DARPA Hacker-Bot Challenge and More

Aug 6, 2016 - 00:24:55

This Week in Machine Learning & AI brings you the week’s most interesting and important stories from the world of machine learning and artificial intelligence. This week we look at Apple’s acquisition of machine learning startup Turi, DARPA’s autonomous hacker-bot challenge, and Comma.ai’s autonomous driving dataset. Plus, of course, tons more. Show notes for this episode can be found at twimlai.com/12.

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Sam Charrington
Clare Corthell - Open Source Data Science Masters, Hybrid AI, Algorithmic Ethics - TWiML Talk #1

Jul 31, 2016 - 00:49:02

This Week in Machine Learning & AI brings you the week’s most interesting and important stories from the world of machine learning and artificial intelligence. We try something new this week with an interview of Clare Corthell, Founding Partner of Luminant Data, recorded live at the Wrangle Conference. We cover her background and what she’s been up to lately, the Open Source Data Science Masters project that she created, getting beyond the beginner’s plateau in machine learning and data science, hybrid AI, the top 3 lessons from her time as a consulting data scientist, and, a recurring topic both here on This Week in Machine Learning and AI and also at the conference: Algorithmic Ethics. The notes for this show can be found at https://twimlai.com/11.

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Sam Charrington
This Week in ML & AI - 7/22/16: ML to Optimize Datacenters, Crazy New GPU from NVIDIA, Faster RNNs

Jul 24, 2016 - 00:25:19

This Week in Machine Learning & AI brings you the week’s most interesting and important stories from the world of machine learning and artificial intelligence. This week covers Google’s use of ML to cut data center power consumption, NVIDIA new ‘crazy, reckless’ GPU, and a new Layer Normalization technique that promises to reduce the training time for deep neural networks. Plus, a bunch more. Show notes for this episode can be found at twimlai.com/10.

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Sam Charrington
This Week in ML & AI - 7/15/16: A Wingman AI for Pokémon Go and Wide & Deep Learning at Google

Jul 17, 2016 - 00:30:22

This Week in Machine Learning & AI brings you the week’s most interesting and important stories from the world of machine learning and artificial intelligence. This week's show features a conversation about public datasets, an AI-powered Pokémon Go Wingman, a new deep learning app for your iPhone, Google research into Wide & Deep learning models, plus a whole lot more. Show notes for this episode can be found at twimlai.com/9.

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Sam Charrington
This Week in ML & AI - 7/8/16: A BS Meter for AI, Retrieval Models for Chatbots & Predatory Robots

Jul 10, 2016 - 00:29:28

This Week in Machine Learning & AI brings you the week’s most interesting and important stories from the world of machine learning and artificial intelligence. This week's show covers the White House’s AI Now workshop, tuning your AI BS meter, research on predatory robots, an AI that writes Python code, plus acquisitions, financing, technology updates and a bunch more. Show notes for this episode can be found at https://twimlai.com/8.

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Sam Charrington
This Week in ML & AI - 7/1/16: Fatal Tesla Autopilot Crash, EU Outlawing Machine Learning & CVPR

Jul 3, 2016 - 00:35:36

This Week in Machine Learning & AI brings you the week’s most interesting and important stories from the world of machine learning and artificial intelligence. This week's show covers the first fatal Tesla autopilot crash, a new EU law that could prohibit machine learning, the AI that shot down a human fighter pilot (in simulation), the 2016 CVPR conference, 10 hot AI startups, the business implications of machine learning, cool chatbot projects and if you can believe it, even more. Show notes for this episode can be found at https://twimlai.com/7.

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Sam Charrington
This Week in ML & AI - 6/24/16: Dueling Neural Networks at ICML, Plus Training a Robotic Housekeeper

Jun 25, 2016 - 00:25:40

This Week in Machine Learning & AI brings you the week’s most interesting and important stories from the world of machine learning and artificial intelligence. This week's show covers the International Conference on Machine Learning (ICML), new research on "dueling architectures" for reinforcement learning, AI safety for robots, plus top AI business deals, tech announcement, projects and more.

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Sam Charrington
This Week in Machine Learning & AI - 6/17/16: Apple's New ML APIs, IBM Brings Deep Learning Thunder

Jun 18, 2016 - 00:24:32

This Week in Machine Learning & AI brings you the week’s most interesting and important stories from the world of machine learning and artificial intelligence. This week’s podcast digs into Apple's ML and AI announcements at WWDC, looks at IBM's new Deep Thunder offering, and discusses exciting new deep learning research from MIT, OpenAI and Google. Show notes available at https://twimlai.com/5.

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Sam Charrington
This Week In Machine Learning & AI - 6/10/16: Self-Motivated AI, Plus A Kill-Switch for Rogue Bots

Jun 11, 2016 - 00:24:05

This Week in Machine Learning & AI brings you the week’s most interesting and important stories from the world of machine learning and artificial intelligence. This week’s podcast looks at new research on intrinsic motivation for AI systems, a kill-switch for intelligent agents, "knu" chips for machine learning, a screenplay made by a neural net, and more. Show notes and subscribe links at https://cloudpul.se/twiml/4.

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Sam Charrington
This Week In Machine Learning & AI - 6/3/16: Facebook's DeepText, ML & Art, Artificial Assistants

Jun 4, 2016 - 00:24:51

This Week in Machine Learning & AI brings you the week’s most interesting and important stories from the world of machine learning and artificial intelligence. This week’s podcast looks at Facebooks' new DeepText engine, creating music & art with deep learning and Google Magenta, how to build artificial assistants and bots, and applying economics to machine learning models. For show notes visit: https://cloudpul.se/posts/twiml-facebooks-deeptext-ml-art-artificial-assistants

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Sam Charrington
This Week In Machine Learning & AI - 5/27/16: The White House on AI & Aggressive Self-Driving Cars

May 28, 2016 - 00:25:53

This Week in Machine Learning & AI brings you the week's most interesting and important stories from the world of machine learning and artificial intelligence. This week's episode explores the White House workshops on AI, human bias in AI and machine learning models, a company working on machine learning for small datasets, plus the latest AI & ML news and a self-driving car that learned how to drive aggressively.

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Sam Charrington
This Week In Machine Learning & AI - 5/20/16: AI at Google I/O, Amazon's Deep Learning DSSTNE

May 21, 2016 - 00:19:29

This Week In Machine Learning & AI - May 20, 2016. Google I/O, deep learning hardware and an AI to save you from conference call hell.

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THE JOE ROGAN EXPERIENCE
#606 - Randall Carlson

Feb 4, 2015 - 3:09:16

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