In this episode we're joined by Chris Albon, Director of Machine Learning at the Wikimedia Foundation. Lukas and Chris talk about Wikimedia's approach to content moderation, what it's like to work in a place so transparent that even internal chats are pub

In this episode, Emily and Lukas dive into the problems with bigger and bigger language models, the difference between form and meaning, the limits of benchmarks, and why it's important to name the languages we study. Show notes (links to papers and trans

Jeff talks about building Facebook's early data team, founding Cloudera, and transitioning into biomedicine with Hammer Lab and Related Sciences.

Josh explains how astronomy and machine learning have informed each other, their current limitations, and where their intersection goes from here.

Xavier shares his experience deploying healthcare models, augmenting primary care with AI, the challenges of "ground truth" in medicine, and robustness in ML. --- Xavier Amatriain is co-founder and CTO of Curai, an ML-based primary care chat system. Pre

Spence shares his experience creating a product around human-in-the-loop machine translation, and explains how machine translation has evolved over the years. --- Spence Green is co-founder and CEO of Lilt, an AI-powered language translation platform. L

Roger and DJ share some of the history behind data science as we know it today, and reflect on their experiences working on California's COVID-19 response. --- Roger Magoulas is Senior Director of Data Strategy at Astronomer, where he works on data infr

Amelia and Filip give insights into the recommender systems powering Pandora, from developing models to balancing effectiveness and efficiency in production. --- Amelia Nybakke is a Software Engineer at Pandora. Her team is responsible for the productio

From Apache TVM to OctoML, Luis gives direct insight into the world of ML hardware optimization, and where systems optimization is heading. --- Luis Ceze is co-founder and CEO of OctoML, co-author of the Apache TVM Project, and Professor of Computer Sci

Matthew explains how combining machine learning and computational biology can provide mainstream medicine with better diagnostics and insights. --- Matthew Davis is Head of AI at Invitae, the largest and fastest growing genetic testing company in the wo