The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

This week on the podcast we’re featuring a series of conversations from the AWS re:Invent conference in Las Vegas. I had a great time at this event getting caught up on the latest and greatest machine learning and AI products and services announced by AWS and its partners. Today we’re joined by Aaron Ames, Professor of Mechanical & Civil Engineering at Caltech. Aaron joined me before his talk at the Deep Learning Summit “Eye, Robot: Computer Vision and Autonomous Robotics” and I had a ton of questions for him. While he considers himself a “hardware guy”, we got into a great discussion centered around the intersection of Robotics and ML Inference. We cover a range of topics, including Boston Dynamics backflipping robot (If you haven't seen it, check out the show notes), Humanoid Robotics, His work on motion primitives and transitions and he even gives us a few predictions on the future of robotics.

This week on the podcast we’re featuring a series of conversations from the AWS re:Invent conference in Las Vegas. I had a great time at this event getting caught up on the latest and greatest machine learning and AI products and services announced by AWS and its partners. In this episode we’re joined by Chris Adzima, Senior Information Analyst for the Washington County Sheriff’s Department. While Chris is not a traditional data scientist, he comes to us with a very interesting use case using AWS’s Rekognition. Chris is using Rekognition to identify suspects in the Portland area by running their mugshots through the software. In our conversation, he details how he is using Rekognition, while giving us few use cases along the way. We discuss how bias affects the work he is doing, and how they try to remove it from their process, not only from a software developer standpoint, but from a law enforcement standpoint and what his next steps are with the Rekognition software. This was a pretty interesting discussion, i’m sure you’ll enjoy it!

This week on the podcast we’re featuring a series of conversations from the AWS re:Invent conference in Las Vegas. I had a great time at this event getting caught up on the latest and greatest machine learning and AI products and services announced by AWS and its partners. This time around we’re joined by Kristen Grauman, a professor in the department of computer science at UT Austin. Kristen specializes in Computer Vision and joined me leading up to her talk at the Deep Learning Summit “Learning where to look in video”. Kristen & I cover the details from her talk, like exploring how a vision system can learn how to move and where to look. Kristen considers how an embodied vision system can internalize the link between “how I move” and “what I see”, explore policies for learning to look around actively, and learn to mimic human videographer tendencies, automatically deciding where to look in unedited 360 degree video. The notes for this show can be found at twimlai.com/talk/85. For series details, visit twimlai.com/reinvent.

This week on the podcast we’re featuring a series of conversations from the AWS re:Invent conference in Las Vegas. I had a great time at this event getting caught up on the latest and greatest machine learning and AI products and services announced by AWS and its partners. In this episode, I’ll be speaking with Nikita Shamgunov, co-founder and CEO of MemSQL, a company offering a distributed, memory-optimized data warehouse of the same name. Nikita and I take a deep dive into some of the features of their recently released 6.0 version, which supports built-in vector operations like dot product and euclidean distance to enable machine learning use cases like real-time image recognition, visual search and predictive analytics for IoT. We also discuss how to architect enterprise machine learning solutions around the data warehouse by including components like data lakes and Spark. Finally, we touch on some of the performance advantages MemSQL has seen by implementing vector operations using Intel’s latest AVX2 and AVX512 instruction sets. Make sure you check out the show notes at twimlai.com/talk/84

This week on the podcast we’re featuring a series of conversations from the AWS re:Invent conference in Las Vegas. I had a great time at this event getting caught up on the latest and greatest machine learning and AI products and services announced by AWS and its partners. If you missed the news coming out of re:Invent and want to know more about what one of the biggest AI platform providers is up to, you’ll want to say tuned, because we’ll discuss many of their new offerings in this episode, a Roundtable discussion I held with Dave McCrory VP of Software Engineering at Wise.io at GE Digital and Lawrence Chung, engagement lead at ThingLogix. We cover all of AWS’ most important news, including the new SageMaker and DeepLens, their Rekognition and Transcription services, Alexa for Business, GreenGrass ML and more. This kind of discussion is something a little new for the show, and is a bit reminiscent of my days covering news here on the podcast, so I hope you enjoy it!

This week on the podcast we’re running a series of shows consisting of conversations with some of the impressive speakers from an event called the AI Summit in New York City. The theme of the conference, and the series, is AI in the Enterprise, and I think you’ll find it really interesting in that it includes a mix of both technical and case-study-oriented discussions. To close out our AI Summit New York Series, I speak with Sherif Mityas, head of Technology, Digital and Strategy at restaurant chain TGI Fridays. Sherif joins us to discuss how Fridays is utilizing conversational AI to enhance customer loyalty. Sherif wants Friday’s to be known as a tech company that happens to sell burgers and beer, and in this conversation we get an in-depth look at the technology landscape they’ve put in place to move the company in this direction. Sherif also shares some of the things on the horizon for Friday’s, as well as some of what they’ve learned along the way. Be sure to share your feedback or questions on the show notes page, which you’ll find at twimlai.com/talk/82.

This week on the podcast we’re running a series of shows consisting of conversations with some of the impressive speakers from an event called the AI Summit in New York City. The theme of the conference, and the series, is AI in the Enterprise, and I think you’ll find it really interesting in that it includes a mix of both technical and case-study-oriented discussions. Today’s show continues our discussion of enterprise AI, with a conversation with Thierry Derungs, Chief Digital Officer at BNP Paribas, a multinational bank headquartered in Paris. Thierry joined me to discuss how BNP uses AI and some of the opportunities that have arisen with the changing AI landscape. We also discuss the innovation process that BNP has used to introduce AI to the bank, via what they call innovation incubators or “factories”. The notes for this show can be found at twimlai.com/talk/81.

The show is part of a series that I’m really excited about, in part because I’ve been working to bring them to you for quite a while now. The focus of the series is a sampling of the interesting work being done over at OpenAI, the independent AI research lab founded by Elon Musk, Sam Altman and others. In this show I’m joined by Jonas Schneider, Robotics Technical Team Lead at OpenAI. This episode features Durk Kingma, a Research Scientist at OpenAI. Although Durk is probably best known for his pioneering work on variational autoencoders, he joined me this time to talk through his latest project on block sparse kernels, which OpenAI just published this week. Block sparsity is a property of certain neural network representations, and OpenAI’s work on developing block sparse kernels helps make it more computationally efficient to take advantage of them. In addition to covering block sparse kernels themselves and the background required to understand them, we also discuss why they’re important and walk through some examples of how they can be used. I’m happy to present another fine Nerd Alert show to close out this OpenAI Series, and I know you’ll enjoy it! To find the notes for this show, visit twimlai.com/talk/80 For more info on this series, visit twimlai.com/openai

This week on the podcast we’re running a series of shows consisting of conversations with some of the impressive speakers from an event called the AI Summit in New York City. The theme of the conference, and the series, is AI in the Enterprise, and I think you’ll find it really interesting in that it includes a mix of both technical and case-study-oriented discussions. Today I'm joined by Brian Gross, Head of Digital Innovation for the Mexico City-based airline AeroMexico. AeroMexico is using AI techniques like neural nets to build a chatbot that responds to its customer’s inquiries. In our conversation, Brian describes how he views the chatbot landscape, shares his thoughts on the platform requirements that established enterprises like AeroMexico have for chatbots, and describes how AeroMexico plans to stay ahead of the curve. Be sure post any feedback or questions you may have to the show notes page, which you’ll find at twimlai.com/talk/79. For more info on this series, visit twimlai.com/aisummit.

This week on the podcast we’re running a series of shows consisting of conversations with some of the impressive speakers from an event called the AI Summit in New York City. The theme of the conference, and the series, is AI in the Enterprise, and I think you’ll find it really interesting in that it includes a mix of both technical and case-study-oriented discussions. My guest this time around is Mazin Gilbert, vice president of advanced technology & architecture with AT&T. Mazin and I have a really interesting discussion on what’s really required to scale AI in the enterprise, and you’ll learn about a new open source project that AT&T is working on to allow any enterprise to do this. You already know by now that I geek out when it comes to talking about the intersection of machine learning and cloud computing, and this conversation is no exception. Be sure to let us know what you think by posting your comments or questions to the show notes page at twimlai.com/talk/78. For more info on this series, visit twimlai.com/aisummit