re:Invent 2020 Liveblog: Machine Learning Keynote

This post was originally published on this site

Follow along as AWS Chief Evangelist Jeff Barr and Developer Advocates Martin Beeby and Steve Roberts liveblog the first-ever Machine Learning Keynote. Swami Sivasubramanian, VP of Amazon Machine Learning will share the latest developments and launches in Amazon ML/AI, as well as demos of new technology, and insights from customers. Join us here from 7:45-10 AM (PST), Tuesday, Dec. 8, 2020.

 Refresh your browser to follow along!


Martin Beeby  8:34 AM
Swami is now talking about the new SageMaker Data Wrangler to speed up data preparation.

Steve Roberts  8:32 AM
If you make something successful, customers will do more of it – the classic flywheel effect. Swami is highlighting Intuit, one of the early adopters of SageMaker, which has deployed over 50% more models this past year, saving costs and cutting expert review time.

Steve Roberts 8:30 AM
“The future of football together with AWS is very bright.”

Martin Beeby  8:28 AM
The NFL predicting and preventing injury using ML on AWS is a fantastic concept—reviewing data to improve helmet safety and reduce concussions, being just one example that Jennifer has given.

Steve Roberts  8:28 AM
It’s interesting, when we (as fans) talk about insights for sports such as the NFL or F1, we usually think about the on-screen insights to help us understand the game or race. But behind the scenes, there’s a huge amount of additional analysis going on around safety and the discussion we just had about biomechanical analysis around concussion is testament to that.

Steve Roberts  8:25 AM
The insights into games provided by ML has been a huge help to this expat Brit in understanding American Football – go Hawks! – and provides an even bigger benefit to player safety.

Jeff Barr  8:24 AM
Next Gen Stats is cool and impressive (even though I’m not much of a sports fan), but the focus on keeping players safe and healthy does it for me!

Martin Beeby  8:23 AM
Jennifer Langton now joins us; she is the SVP Player Health and Innovation at the NFL.

Jeff Barr  8:23 AM
Some great customer successes — better, faster, cheaper:

Steve Roberts  8:21 AM
Onto tenet #2 – provide the shortest path to success. We aim to do this by providing the tools to help satisfy the need for builders to explore quickly, which is a significant accelerator. In the last year, we’ve released 50 new features for SageMaker for example. This also helps lift the barriers to adoption in what was a complex and costly process.

Martin Beeby  8:20 AM
If you want to know more, here’s our news blog post from Julien Simon.

Jeff Barr  8:19 AM
Being able to train faster is not just for bragging rights. It encourages experimentation and helps builders to get models into production faster than ever before.

Martin Beeby 8:17 AM
Announcement: Managed data parallelism in Amazon SageMaker. Train 40% faster. It simplifies training on large datasets that might be as large as hundreds or thousands of gigabytes.

Martin Beeby  8:15 AM
Nice stat: 92% of cloud-based TensorFlow runs on AWS, 91% of cloud-based PyTorch runs on AWS.

Jeff Barr 8:14 AM
All of these instance types give customers a lot of choice and put a lot of training and inference power into their hands.

Steve Roberts  8:11 AM
We’re now discussing tenets, starting with firm foundations. Optimized frameworks and infrastructure for training and deployment. This gives builders the freedom to invent.

Martin Beeby  8:11 AM
Builders of all skill levels can unlock the power of machine learning.

Jeff Barr 8:10 AM
Since the beginning, AWS has focused on empowering developers and giving them the freedom to invent.

Jeff Barr 8:07 AM
Over 250 new features per year. This is what we mean when we talk about the “pace of innovation.”

Jeff Barr 8:06 AM
We have a very broad and very deep set of ML/AI offerings, growing in breadth all the time.

Steve Roberts 8:06 AM
Swami is describing how ML is no longer a niche offering. He’s mentioned Dominos using it to meet their goal of 10mins or less for pizza delivery, Roche to accelerate medical experiences, BMW processing 7PB of data with SageMaker, Nike for product recommendations and F1 to analyze over 550M data points on car design and simulations.

Martin Beeby 8:05 AM
Swami is explaining how we have seen incredible customer momentum around Machine Learning. They really have. Things have moved on so much in such a short period. He is explaining how companies like Nike, BMW, and Domino’s are all using ML on AWS.

Dr. Swamin Sivasubramanian on stage

Martin Beeby 8:01 AM
Things are starting here; on stage now, we have Dr. Swami Sivasubramanian, VP of Amazon Machine Learning.

Martin Beeby  7:59 AM
This music from Durante reminds me of that Werner Vogels saying: Dance like nobody’s watching, encrypt like everyone is.

Durante DJing

Martin Beeby  7:51 AM
Hi everyone. I am excited to be liveblogging the first-ever Machine Learning keynote here at AWS re:Invent. We expect Dr. Swami Sivasubramanian to take the stage shortly. I am blogging from my home office in Northampton, England, and looking forward to hearing about all the latest developments in Machine Learning at AWS.

 Durante standing outside at mixing tableMartin Beeby  7:47 AM
It looks like we have Durante providing the music today. That is some setup he has!

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.