Transforming Oil & Gas with AI with Adi Bhashyam and Daniel Jeavons - TWIML Talk #279
Today we’re joined by return guest Daniel Jeavons, GM of Data Science at Shell, and Adi Bhashyam, GM of Data Science at C3, who we had the pleasure of speaking to at this years C3 Transform Conference. In our conversation, we discuss: • The progress that Dan and his team has made since our last conversation, including an overview of their data platform. • Adi gives us an overview of the evolution of C3 and their platform, along with a breakdown of a few Shell-specific use cases.
1 Heinä 201946min
Fast Radio Burst Pulse Detection with Gerry Zhang - TWIML Talk #278
Today we’re joined by Yunfan Gerry Zhang, a PhD student at UC Berkely, and an affiliate of Berkeley’s SETI research center. In our conversation, we discuss: • Gerry's research on applying machine learning techniques to astrophysics and astronomy. • His paper “Fast Radio Burst 121102 Pulse Detection and Periodicity: A Machine Learning Approach”. • We explore the types of data sources used for this project, challenges Gerry encountered along the way, the role of GANs and much more.
27 Kesä 201938min
Tracking CO2 Emissions with Machine Learning with Laurence Watson - TWIML Talk #277
Today we’re joined by Laurence Watson, Co-Founder and CTO of Plentiful Energy and a former data scientist at Carbon Tracker. In our conversation, we discuss: • Carbon Tracker's goals, and their report “Nowhere to hide: Using satellite imagery to estimate the utilisation of fossil fuel power plants”. • How they are using computer vision to process satellite images of coal plants, including how the images are labeled. •Various challenges with the scope and scale of this project.
24 Kesä 201941min
Topic Modeling for Customer Insights at USAA with William Fehlman - TWIML Talk #276
Today we’re joined by William Fehlman, director of data science at USAA, to discuss: • His work on topic modeling, which USAA uses in various scenarios, including member chat channels. • How their datasets are generated. • Explored methodologies of topic modeling, including latent semantic indexing, latent Dirichlet allocation, and non-negative matrix factorization. • We also explore how terms are represented via a document-term matrix, and how they are scored based on coherence.
20 Kesä 201944min
Phronesis of AI in Radiology with Judy Gichoya - TWIML Talk #275
Today we’re joined by Judy Gichoya an interventional radiology fellow at the Dotter Institute at Oregon Health and Science University. In our conversation, we discuss: • Judy's research on the paper “Phronesis of AI in Radiology: Superhuman meets Natural Stupidy,” reviewing the claims of “superhuman” AI performance in radiology. • Potential roles in which AI can have success in radiology, along with some of the different types of biases that can manifest themselves across multiple use c
18 Kesä 201943min
The Ethics of AI-Enabled Surveillance with Karen Levy - TWIML Talk #274
Today we’re joined by Karen Levy, assistant professor in the department of information science at Cornell University. Karen’s research focuses on how rules and technologies interact to regulate behavior, especially the legal, organizational, and social aspects of surveillance and monitoring. In our conversation, we discuss how data tracking and surveillance can be used in ways that can be abusive to various marginalized groups, including detailing her extensive research into truck driver surveillance.
14 Kesä 201943min
Supporting Rapid Model Development at Two Sigma with Matt Adereth & Scott Clark - TWIML Talk #273
Today we’re joined by Matt Adereth, managing director of investments at Two Sigma, and return guest Scott Clark, co-founder and CEO of SigOpt, to discuss: • The end to end modeling platform at Two Sigma, who it serves, and challenges faced in production and modeling. • How Two Sigma has attacked the experimentation challenge with their platform. • What motivates companies that aren’t already heavily invested in platforms, optimization or automation, to do so, and much more!
11 Kesä 201946min
Scaling Model Training with Kubernetes at Stripe with Kelley Rivoire - TWIML Talk #272
Today we’re joined by Kelley Rivoire, engineering manager working on machine learning infrastructure at Stripe. Kelley and I caught up at a recent Strata Data conference to discuss: • Her talk "Scaling model training: From flexible training APIs to resource management with Kubernetes." • Stripe’s machine learning infrastructure journey, including their start from a production focus. • Internal tools used at Stripe, including Railyard, an API built to manage model training at scale & more!
6 Kesä 201942min
