Fully Connected

Bringing ML practitioners together

Fully Connected is your home for curated tutorials, conversations with industry leaders, deep dives into the newest ML research, and a whole lot more.

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Stephan Fabel — Efficient Supercomputing with NVIDIA's Base Command Platform
Cayla Sharp, Angelica Pan
Chris Padwick — Smart Machines for More Sustainable Farming
Cayla Sharp, Angelica Pan
Kathryn Hume — Financial Models, ML, and 17th-Century Philosophy
Cayla Sharp, Angelica Pan
Sean and Greg — Biology and ML for Drug Discovery
Cayla Sharp, Angelica Pan
Chris, Shawn, and Lukas — The Weights & Biases Journey
Cayla Sharp, Angelica Pan
Pete Warden — Practical Applications of TinyML
Cayla Sharp, Angelica Pan
Pieter Abbeel — Robotics, Startups, and Robotics Startups
Cayla Sharp, Angelica Pan
Chris Albon — ML Models and Infrastructure at Wikimedia
Cayla Sharp, Angelica Pan
Emily M. Bender — Language Models and Linguistics
Cayla Sharp, Angelica Pan
Jeff Hammerbacher — From data science to biomedicine
Cayla Sharp, Angelica Pan
Josh Bloom — The Link Between Astronomy and ML
Cayla Sharp, Angelica Pan
Xavier Amatriain — Building AI-powered Primary Care
Cayla Sharp, Angelica Pan
Spence Green — Enterprise-scale Machine Translation
Cayla Sharp, Angelica Pan
Roger & DJ — The Rise of Big Data and CA's COVID-19 Response
Cayla Sharp, Angelica Pan
Amelia & Filip — How Pandora Deploys ML Models into Production
Cayla Sharp, Angelica Pan
Luis Ceze — Accelerating Machine Learning Systems
Cayla Sharp, Angelica Pan
Matthew Davis — Bringing Genetic Insights to Everyone
Cayla Sharp, Angelica Pan
Clément Delangue — The Power of the Open Source Community
Cayla Sharp, Angelica Pan
Wojciech Zaremba — What Could Make AI Conscious?
Cayla Sharp, Angelica Pan
Phil Brown — How IPUs are Advancing Machine Intelligence
Cayla Sharp, Angelica Pan
Alyssa Simpson Rochwerger — Responsible ML in the Real World
Cayla Sharp, Angelica Pan
Sean Taylor — Business Decision Problems
Cayla Sharp, Angelica Pan
Hamel Husain — Building Machine Learning Tools
Carey Phelps
Vicki Boykis — Machine Learning Across Industries
Carey Phelps
Peter Welinder — Deep Reinforcement Learning and Robotics
Carey Phelps
Rachael Tatman — Conversational AI and Linguistics
Carey Phelps
Brandon Rohrer — Machine Learning in Production for Robots
Carey Phelps
Nicolas Koumchatzky — Machine Learning in Production for Self-Driving Cars
Carey Phelps
Jack Clark — Building Trustworthy AI Systems
Carey Phelps
Angela & Danielle — Designing ML Models for Millions of Consumer Robots
Carey Phelps
Polly Fordyce — Microfluidic Platforms and Machine Learning
Cayla Sharp, Angelica Pan
Miles Brundage — Societal Impacts of Artificial Intelligence
Carey Phelps
Josh Tobin — Productionizing ML Models
Carey Phelps
Peter Skomoroch — Product Management for AI
Carey Phelps
Chip Huyen — ML Research and Production Pipelines
Carey Phelps
Anantha Kancherla — Building Level 5 Autonomous Vehicles
Carey Phelps
Bharath Ramsundar — Deep Learning for Molecules and Medicine Discovery
Carey Phelps
Jeremy Howard — The Story of fast.ai and Why Python Is Not the Future of ML
Carey Phelps
Suzana Ilić — Cultivating Machine Learning Communities
Carey Phelps
Anthony Goldbloom — How to Win Kaggle Competitions
Carey Phelps
Zack Chase Lipton — The Medical Machine Learning Landscape
Carey Phelps
Ines & Sofie — Building Industrial-Strength NLP Pipelines
Cayla Sharp
Daeil Kim — The Unreasonable Effectiveness of Synthetic Data
Cayla Sharp
Joaquin Candela — Definitions of Fairness
Cayla Sharp
Richard Socher — The Challenges of Making ML Work in the Real World
Carey Phelps
Adrien Gaidon — Advancing ML Research in Autonomous Vehicles
Cayla Sharp, Angelica Pan
Sean Gourley — NLP, National Defense, and Establishing Ground Truth
Cayla Sharp
Rosanne Liu — Conducting Fundamental ML Research as a Nonprofit
Cayla Sharp
Chris Anderson — Robocars, Drones, and WIRED Magazine
Cayla Sharp
Adrien Treuille — Building Blazingly Fast Tools That People Love
Cayla Sharp
Peter Norvig – Singularity Is in the Eye of the Beholder
Cayla Sharp
Daphne Koller — Digital Biology and the Next Epoch of Science
Cayla Sharp, Angelica Pan
Piero Molino — The Secret Behind Building Successful Open Source Projects
Cayla Sharp
Peter Wang — Anaconda, Python, and Scientific Computing
Cayla Sharp
Robert Nishihara — The State of Distributed Computing in ML
Cayla Sharp
Dave Selinger — AI and the Next Generation of Security Systems
Cayla Sharp, Lavanya Shukla
Dominik Moritz — Building Intuitive Data Visualization Tools
Cayla Sharp, Angelica Pan
Cade Metz — The Stories Behind the Rise of AI
Cayla Sharp, Angelica Pan, Lavanya Shukla
Tim & Heinrich — Democraticizing Reinforcement Learning Research
Cayla Sharp, Lavanya Shukla
Vladlen Koltun — The Power of Simulation and Abstraction
Cayla Sharp, Angelica Pan
Chris Mattmann — ML Applications on Earth, Mars, and Beyond
Cayla Sharp, Angelica Pan
Nimrod Shabtay — Deployment and Monitoring at Nanit
Cayla Sharp, Angelica Pan