Discovering Exoplanets w/ Deep Learning with Chris Shallue - TWiML Talk #117

Discovering Exoplanets w/ Deep Learning with Chris Shallue - TWiML Talk #117

Earlier this week, I had a chance to speak with Chris Shallue, Senior Software Engineer on the Google Brain Team, about his project and paper on “Exploring Exoplanets with Deep Learning.” This is a great story. Chris, inspired by a book he was reading, reached out on a whim to a Harvard astrophysics researcher, kicking off a collaboration and side project eventually leading to the discovery of two new planets outside our solar system. In our conversation, we walk through the entire process Chris followed to find these two exoplanets, including how he researched the domain as an outsider, how he sourced and processed his dataset, and how he built and evolved his models. Finally, we discuss the results of his project and his plans for future work in this area. This podcast is being published in parallel with Google’s release of the source code and data that Chris developed and used, which we’ll link to below, so if what you hear inspires you to dig into this area, you’ve got a nice head start. This was a really interesting conversation, and I'm excited to share it with you! The notes for this show can be found at twimlai.com/talk/117 The corresponding blog post for this project can be found at https://research.googleblog.com/2018/03/open-sourcing-hunt-for-exoplanets.html

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Nexus Lab Cohort 2 - Second Mind - TWiML Talk #66

Nexus Lab Cohort 2 - Second Mind - TWiML Talk #66

The podcast you’re about to hear is the fourth of a series of shows recorded at the NYU Future Labs AI Summit last week in New York City. In this show, I speak with Kul Singh, CEO and Founder of Second Mind. Second Mind is building an integration platform for businesses that allows them to bring augmented intelligence to voice conversations. We talk to Kul about the concept behind Second Mind, and how the company combines ambient listening with a low-latency matching system to help users eliminate an estimated 2.5 hours of manual searches per day! The notes for this show can be found at twimlai.com/talk/66 For series information, visit twimlai.com/ainexuslab2

9 Nov 201721min

Nexus Lab Cohort 2 - Bite.ai - TWiML Talk #65

Nexus Lab Cohort 2 - Bite.ai - TWiML Talk #65

The podcast you’re about to hear is the second of a series of shows recorded at the NYU Future Labs AI Summit last week in New York City.In this episode, you’ll hear from Bite.ai, a startup founded by Vinay Anantharaman and Michal Wolski, founders who met working at Clarifai, another NYU Future Labs alumni, whose CEO Matt Zeiler I interviewed on TWiML Talk #22(Link on show notes page). Bite is using convolutional neural networks and other machine learning to help computers understand and reason about food. Their product is the app Bitesnap, which provides users with detailed nutritional information about the food they’re about to eat using just a photo and a serving size. We dive into the details of their app and service, the machine learning models and pipeline that enable it, and how they plan to compete with other apps targeting dieters, and more! The notes for this show can be found at twimlai.com/talk/65 For series information, visit twimlai.com/ainexuslab2.

8 Nov 201726min

Nexus Lab Cohort 2 - Bowtie - TWiML Talk #64

Nexus Lab Cohort 2 - Bowtie - TWiML Talk #64

The podcast you’re about to hear is the second of a series of shows recorded at the NYU Future Labs AI Summit last week in New York City. In this episode, I speak with Ron Fisher and Mike Wang, who, along with Vivek Sudarsan founded Bowtie Labs, a 24/7 AI-based receptionist designed to help businesses in the beauty, wellness, and fitness industries increase retail conversion rates. I’ve talked with a few startups in the conversational space recently and one common theme seems to be quickly outgrowing commercial conversational platforms. Ron and Mike shared their own experiences with decision, and shared some of the challenges they’re trying to overcome with their ML models, as well as some of the techniques they use to make their system as responsive as possible. The notes for this show can be found at twimlai.com/talk/64 For Series information, visit twimlai.com/ainexuslab2

7 Nov 201725min

AI Nexus Lab Cohort 2 - Mt. Cleverest - TWiML Talk #63

AI Nexus Lab Cohort 2 - Mt. Cleverest - TWiML Talk #63

The podcast you’re about to hear is the first of a series of shows recorded at the NYU Future Labs AI Summit last week in New York City. My guests this time around are James Villarrubia and Bernie Prat, CEO and COO respectively, of Mt. Cleverest, an online service for teachers and students, that can take any text via the web, and generate a quiz along with answers based on the content supplied. To do this, Bernie and James employ a pretty sophisticated natural language understanding pipeline, which we discuss in this interview. We also touch on the challenges they face in generating correct question answers, how they fine tune their ML models to improve those answers over time, and more. The notes for this show can be found at twimlai.com/talk/63 For Series information, visit twimlai.com/nexuslabs2

6 Nov 201732min

Learning to Learn, and other Opportunities in Machine Learning with Graham Taylor - TWiML Talk #62

Learning to Learn, and other Opportunities in Machine Learning with Graham Taylor - TWiML Talk #62

The podcast you’re about to hear is the third of a series of shows recorded at the Georgian Partners Portfolio Conference last week in Toronto. My guest this time is Graham Taylor, professor of engineering at the University of Guelph, who keynoted day two of the conference. Graham leads the Machine Learning Research Group at Guelph, and is affiliated with Toronto’s recently formed Vector Institute for Artificial Intelligence. Graham and I discussed a number of the most important trends and challenges in artificial intelligence, including the move from predictive to creative systems, the rise of human-in-the-loop AI, and how modern AI is accelerating with our ability to teach computers how to learn-to-learn. The notes for this show can be found at twimlai.com/talk/62. For series info, visit twimlai.com/GPPC2017

3 Nov 201737min

Building Conversational Application for Financial Services with Kenneth Conroy - TWiML Talk #61

Building Conversational Application for Financial Services with Kenneth Conroy - TWiML Talk #61

The podcast you’re about to hear is the second of a series of shows recorded at the Georgian Partners Portfolio Conference last week in Toronto. My guest for this interview is Kenneth Conroy, VP of data science at Vancouver, Canada-based Finn.ai, a company building a chatbot system for banks. Kenneth and I spoke about how Finn.AI built its core conversational platform. We spoke in depth about the requirements and challenges of conversational applications, and how and why they transitioned off of a commercial chatbot platform--in their case API.ai--and built their own custom platform based on deep learning, word2vec and other natural language understanding technologies. The notes for this show can be found at https://twimlai.com/talk/61

1 Nov 201737min

Fighting Fraud with Machine Learning at Shopify with Solmaz Shahalizadeh - TWiML Talk #60

Fighting Fraud with Machine Learning at Shopify with Solmaz Shahalizadeh - TWiML Talk #60

The podcast you’re about to hear is the first of a series of shows recorded at the Georgian Partners Portfolio Conference last week in Toronto. My guest for this show is Solmaz Shahalizadeh, Director of Merchant Services Algorithms at Shopify. Solmaz gave a great talk at the GPPC focused on her team’s experiences applying machine learning to fight fraud and improve merchant satisfaction. Solmaz and I dig into, step-by-step, the process they used to transition from a legacy, rules-based fraud detection system system to a more scalable, flexible one based on machine learning models. We discuss the importance of well-defined project scope; tips and traps when selecting features to train your models; and the various models, transformations and pipelines the Shopify team selected; and how they use PMML to make their Python models available to their Ruby-on-Rails web application. The notes for this show can be found at twimlai.com/talk/60 For Series info, visit twimlai.com/GPPC2017

30 Okt 201735min

Modeling Human Drivers for Autonomous Vehicles with Katie Driggs-Campbell - TWiML Talk #59

Modeling Human Drivers for Autonomous Vehicles with Katie Driggs-Campbell - TWiML Talk #59

We are back with our third show this week, episode 3 of our Autonomous Vehicles Series. My guest this time is Katie Driggs-Campbell, PostDoc in the Intelligent Systems Lab at Stanford University’s Department of Aeronautics and Astronautics. Katie joins us to discuss her research into human behavioral modeling and control systems for self-driving vehicles. Katie also gives us some insight into her process for collecting training data, how social nuances come into play for self-driving cars, and more. The notes for this show can be found at twimlai.com/talk/59 For Series info, visit twimlai.com/av2017

27 Okt 201733min

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