AI for Humanitarian Action with Justin Spelhaug - TWiML Talk #226
Today we're joined by Justin Spelhaug, General Manager of Technology for Social Impact at Microsoft. In our conversation, we discuss the company’s efforts in AI for Humanitarian Action, covering Microsoft’s overall approach to technology for social impact, how his group helps mission-driven organizations best leverage technologies like AI, and how AI is being used at places like the World Bank, Operation Smile, and Mission Measurement to create greater impact.
4 Feb 201958min
Teaching AI to Preschoolers with Randi Williams - TWiML Talk #225
Today, in the first episode of our Black in AI series, we’re joined by Randi Williams, PhD student at the MIT Media Lab. At the Black in AI workshop Randi presented her research on Popbots: A Early Childhood AI Curriculum, which is geared towards teaching preschoolers the fundamentals of artificial intelligence. In our conversation, we discuss the origins of the project, the three AI concepts that are taught in the program, and the goals that Randi hopes to accomplish with her work.
31 Jan 201943min
Holistic Optimization of the LinkedIn News Feed - TWiML Talk #224
Today we’re joined by Tim Jurka, Head of Feed AI at LinkedIn. In our conversation, Tim describes the holistic optimization of the feed and we discuss some of the interesting technical and business challenges associated with trying to do this. We talk through some of the specific techniques used at LinkedIn like Multi-arm Bandits and Content Embeddings, and also jump into a really interesting discussion about organizing for machine learning at scale.
28 Jan 201948min
AI at the Edge at Qualcomm with Gary Brotman - TWiML Talk #223
Today we’re joined by Gary Brotman, Senior Director of Product Management at Qualcomm Technologies, Inc. Gary, who got his start in AI through music, now leads strategy and product planning for the company’s AI and ML technologies, including those that make up the Qualcomm Snapdragon mobile platforms. In our conversation, we discuss AI on mobile devices and at the edge, including popular use cases, and explore some of the various acceleration technologies offered by Qualcomm and others that enable th
24 Jan 201951min
AI Innovation at CES - TWiML Talk #222
A few weeks ago, I made the trek to Las Vegas for the world’s biggest electronics conference, CES. In this special visual only episode, we’re going to check out some of the interesting examples of machine learning and AI that I found at the event. Check out the video at https://twimlai.com/ces2019, and be sure to hit the like and subscribe buttons and let us know how you like the show via a comment! For the show notes, visit https://twimlai.com/talk/222.
21 Jan 20192min
Self-Tuning Services via Real-Time Machine Learning with Vladimir Bychkovsky - TWiML Talk #221
Today we’re joined by Vladimir Bychkovsky, Engineering Manager at Facebook, to discuss Spiral, a system they’ve developed for self-tuning high-performance infrastructure services at scale, using real-time machine learning. In our conversation, we explore how the system works, how it was developed, and how infrastructure teams at Facebook can use it to replace hand-tuned parameters set using heuristics with services that automatically optimize themselves in minutes rather than in weeks.
17 Jan 201946min
Building a Recommender System from Scratch at 20th Century Fox with JJ Espinoza - TWiML Talk #220
Today we’re joined by JJ Espinoza, former Director of Data Science at 20th Century Fox. In this talk we dig into JJ and his team’s experience building and deploying a content recommendation system from the ground up. In our conversation, we explore the design of a couple of key components of their system, the first of which processes movie scripts to make recommendations about which movies the studio should make, and the second processes trailers to determine which should be recommended to users.
14 Jan 201934min
Legal and Policy Implications of Model Interpretability with Solon Barocas - TWiML Talk #219
Today we’re joined by Solon Barocas, Assistant Professor of Information Science at Cornell University. Solon and I caught up to discuss his work on model interpretability and the legal and policy implications of the use of machine learning models. In our conversation, we explore the gap between law, policy, and ML, and how to build the bridge between them, including formalizing ethical frameworks for machine learning. We also look at his paper ”The Intuitive Appeal of Explainable Machines.”
10 Jan 201946min
