The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Sam Charrington
Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, computer science, data science and more.
Episodes
Mentioned books
Nov 6, 2018 • 39min
Facebook's FBLearner Platform with Aditya Kalro - TWiML Talk #197
In the kickoff episode of our AI Platforms series, we’re joined by Aditya Kalro, Engineering Manager at Facebook, to discuss their internal machine learning platform FBLearner Flow. FBLearner Flow is the workflow management platform at the heart of the Facebook ML engineering ecosystem. We discuss the history and development of the platform, as well as its functionality and its evolution from an initial focus on model training to supporting the entire ML lifecycle at Facebook.
Nov 1, 2018 • 44min
Geometric Statistics in Machine Learning w/ geomstats with Nina Miolane - TWiML Talk #196
In this episode we’re joined by Nina Miolane, researcher and lecturer at Stanford University. Nina and I spoke about her work in the field of geometric statistics in ML, specifically the application of Riemannian geometry, which is the study of curved surfaces, to ML. In our discussion we review the differences between Riemannian and Euclidean geometry in theory and her new Geomstats project, which is a python package that simplifies computations and statistics on manifolds with geometric structures.
Oct 29, 2018 • 1h 1min
Milestones in Neural Natural Language Processing with Sebastian Ruder - TWiML Talk #195
In this episode, we’re joined by Sebastian Ruder, PhD student studying NLP at National University of Ireland and Research Scientist at text analysis startup Aylien. We discuss recent milestones in neural NLP, including multi-task learning and pretrained language models. We also look at the use of attention-based models, Tree RNNs and LSTMs, and memory-based networks. Finally, Sebastian walks us through his ULMFit paper, which he co-authored with Jeremy Howard of fast.ai who I interviewed in episode 186.
Oct 25, 2018 • 51min
Natural Language Processing at StockTwits with Garrett Hoffman - TWiML Talk #194
In this episode, we’re joined by Garrett Hoffman, Director of Data Science at Stocktwits. Stocktwits is a social network for the investing community which has its roots in the use of the $cashtag on Twitter. In our conversation, we discuss applications such as Stocktwits’ own use of “social sentiment graphs” built on multilayer LSTM networks to gauge community sentiment about certain stocks in real time, as well as the more general use of natural language processing for generating trading ideas.
Oct 23, 2018 • 47min
Advanced Reinforcement Learning & Data Science for Social Impact with Vukosi Marivate - TWiML Talk #193
In the final episode of our Deep Learning Indaba series, we speak with Vukosi Marivate, Chair of Data Science at the University of Pretoria and a co-organizer of the Indaba.
My conversation with Vukosi falls into two distinct parts, his PhD research in reinforcement learning, and his current research, which falls under the banner of data science with social impact. We discuss several advanced RL scenarios, along with several applications he is currently exploring in areas like public safety and energy.
Oct 18, 2018 • 47min
AI Ethics, Strategic Decisioning and Game Theory with Osonde Osoba - TWiML Talk #192
In this episode of our Deep Learning Indaba Series, we’re joined by Osonde Osoba, Engineer at RAND Corporation.
Osonde and I spoke on the heels of the Indaba, where he presented on AI Ethics and Policy. We discuss his framework-based approach for evaluating ethical issues and how to build an intuition for where ethical flashpoints may exist in these discussions. We also discuss Osonde’s own model development research, including the application of machine learning to strategic decisions and game theor
Oct 16, 2018 • 1h 1min
Acoustic Word Embeddings for Low Resource Speech Processing with Herman Kamper - TWiML Talk #191
In this episode of our Deep Learning Indaba Series, we’re joined by Herman Kamper, lecturer at Stellenbosch University in SA and a co-organizer of the Indaba.
We discuss his work on limited- and zero-resource speech recognition, how those differ from regular speech recognition, and the tension between linguistic and statistical methods in this space. We also dive into the specifics of the methods being used and developed in Herman’s lab.
Oct 12, 2018 • 42min
Learning Representations for Visual Search with Naila Murray - TWiML Talk #190
In this episode of our Deep Learning Indaba series, we’re joined by Naila Murray, Senior Research Scientist and Group Lead in the computer vision group at Naver Labs Europe.
Naila presented at the Indaba on computer vision. In this discussion, we explore her work on visual attention, including why visual attention is important and the trajectory of work in the field over time. We also discuss her paper “Generalized Max Pooling,” and much more!
For the complete show notes, visit twimlai.com/tal
Oct 10, 2018 • 1h 4min
Evaluating Model Explainability Methods with Sara Hooker - TWiML Talk #189
In this, the first episode of the Deep Learning Indaba series, we’re joined by Sara Hooker, AI Resident at Google Brain. I spoke with Sara in the run-up to the Indaba about her work on interpretability in deep neural networks. We discuss what interpretability means and nuances like the distinction between interpreting model decisions vs model function. We also talk about the relationship between Google Brain and the rest of the Google AI landscape and the significance of the Google AI Lab in Accra, Ghana.
Oct 8, 2018 • 54min
Graph Analytic Systems with Zachary Hanif - TWiML Talk #188
In this, the final episode of our Strata Data Conference series, we’re joined by Zachary Hanif, Director of Machine Learning at Capital One’s Center for Machine Learning.
We start our discussion with a look at the role of graph analytics in the ML toolkit, including some important application areas for graph-based systems. Zach gives us an overview of the different ways to implement graph analytics, including what he calls graphical processing engines which excel at handling large datasets, & much m
