Amazon Web Services (AWS) held a free virtual Machine Learning Summit on June 2, with the goal of bringing together customers, developers, and the science community to learn about advances in the practice of machine learning (ML).
Opening keynote
The event began with a keynote from from Swami Sivasubramanian, AWS vice president of machine learning; Bratin Saha, vice president of AWS Machine Learning Services; and Yoelle Maarek, vice president of research science, Alexa Shopping.
AWS ML Summit 2021 | Opening Keynote
Fireside chat
Next up was a fireside chat. Andrew Ng, founder and CEO of Landing AI, and Sivasubramanian discussed the future of ML, the skills that are fundamental for the next generation of ML practitioners, and how to bridge the proof-of-concept-to-production gap in ML.
AWS ML Summit 2021 | Fireside Chat
Breakout sessions
The Summit included four audience-focused tracks which ran throughout the day:
- Science of Machine Learning;
- Impact of Machine Learning;
- How Machine Learning Is Done; and
- Machine Learning — No Experience Required
Science of Machine Learning track fireside chat
The Science of Machine Learning track comprised six 30-minute presentations, and a fireside chat on deep learning and language with Amazon distinguished scientists Alex Smola and Bernhard Schölkopf, and Alexa AI senior principal scientist Dilek Hakkani-Tur.
Machine Learning track fireside chat replay: Causality, robustness, and natural language understanding in ML
Science of Machine Learning track session videos and interviews
Below are video replays from each of the speakers in the Science of Machine Learning track, along with links to interviews Amazon Science did with each of the speakers in the weeks before the summit. Click here to see the full list of ML Summit videos.
Marzia Polito replay: Building high-quality computer vision models using only a few examples
Michael Kearns replay: The ethical algorithm
Philip Resnik replay: Analyzing social media for suicide risk using natural language processing
Ryan Tibshirani replay: COVIDcast: An ecosystem for COVID-19 tracking and forecasting
Kathleen McKeown replay: Towards controllable language generation
George Karypis replay: Deep Graph Library: Deep Graph learning at scale
