Every year I think it will finally be the year that I can attend AWS re:Invent in person, but once again it looks like that's not in the cards for me (or many other Australians!) in 2021. In the spirit of living vicariously and imagining a world without global health crises or travel restrictions, I'll board an imaginary flight from Brisbane to Las Vegas!
Here are the 5 sessions at the top of my list for AWS re:Invent 2021, as an AI/ML Enthusiast!

Also before I get started - there are actually virtual tickets available to reinvent here which will allow you to virtually attend live keynotes and leadership sessions, but unfortunately we won't get to see the workshops or builders sessions. This list contains a mix of in-person and virtual events.

Brooke's Bookmarks · AWS re:Invent 2021

(Click links to skip to section)

1. Swami Sivasubramanian Keynote - KYN003
2. 15 years of AWS with Jeff Barr - BOA201
3. MLOps at Amazon: How to productionize ML workloads at scale - AMZ302
4. Machine learning at the edge with Amazon SageMaker - AIM410
5. Building better products for people of all identities - ABW002

Swami Sivasubramanian Keynote - KYN003

Date: Wednesday, December 1
Time: 8:30 AM - 10:30 AM
Session type: Keynote (Will be recorded!)
Description:

Join Swami Sivasubramanian, Vice President, Amazon Machine Learning, on an exploration of what it takes to put data in action with an end to end data strategy including the latest news on databases, analytics, and machine learning.

Keynote sessions like this are really worth attending for two main reasons - firstly, they'll cover the key takeaways and innovations that will be covered in more detail in other sessions, but also because it's so helpful to learn how a seasoned professional (like Swami!) will communicate this to broad audiences. This session is available with the virtual ticket and will be recorded so I recommend watching it twice. Watch once as you normally would (taking notes of the new solutions on offer) but then watch it again through the eyes of someone who is completely new to AI/ML. Swami Sivasubramanian has worked on so many different products at AWS, and I'm sure this will be a really well rounded session.

If you only have time to attend one session, this should be the one!

15 years of AWS with Jeff Barr - BOA201

Date: Monday, November 29
Time: 3:15 PM - 4:15 PM
Session type: Breakout Session
Session level: 200 - Intermediate
Description:

Amazon S3 and Amazon EC2 are turning 15 this year, and Jeff Barr, VP and Chief Evangelist at AWS, has been at Amazon even longer! In this breakout session, have a chat with him about how AWS was born, how the developer experience has evolved over the years, and how customers keep surprising us with their amazing projects. Along the way, Jeff also answers questions sent by the developer community and shares lessons on how to best build on AWS.

I met Jeff at an AWS Event in Melbourne a couple of years ago, and meeting Jeff and Aileen Gemma Smith that day really motivated me to get more involved in the AWS Community and public speaking in general. This isn't specifically an AI/ML focused session, but if you're able to attend, I'm sure this will be really valuable as Jeff has so much experience and so many great stories.

MLOps at Amazon: How to productionize ML workloads at scale - AMZ302

Date: Thursday, December 2
Time: 2:30 PM - 3:30 PM
Session type: Breakout Session
Session level: 300 - Advanced
Description:

Many organizations have started to optimize their ML workload deployments using MLOps mechanisms. Learn how this works in the real world and how Amazon enabled the automation and reusability of ML solutions across a number of different business workloads—from optimizing product search results on Amazon.com to running its transportation network and ensuring faster delivery times. In this session, discover how to reduce production-level ML infrastructure delivery time from weeks to hours (with specific data and examples from Amazon) and how these mechanisms enable data scientists to focus on innovation instead of infrastructure, allowing them to easily reuse or generate new ML solutions.

Gartner research shows only 53% of projects make it from artificial intelligence (AI) prototypes to production. This is something lots of organisations struggle with, and MLOps is really starting to gain awareness and traction in the Applied AI space.
This will be a challenging but informative session to attend, and absolutely worthwhile if you have been playing around with PoC models but you're not sure how to integrate them with MLOps standards. Learn this the right the first time, and putting models into prod (and maintaining them there!) will be so much easier in future.

Machine learning at the edge with Amazon SageMaker - AIM410

Date: Monday, November 29
Time: 11:30 AM - 12:30 PM
Session type: Chalk Talk
Session level: 400 - Expert
Description:

More ML models are being deployed on edge devices such as robots and smart cameras. In this chalk talk, dive into building computer vision (CV) applications at the edge for predictive maintenance, industrial IoT, and more. Learn how to operate and monitor multiple models across a fleet of devices. Also walk through the process to build and train CV models with Amazon SageMaker and how to package, deploy, and manage them with SageMaker Edge Manager. The chalk talk also covers edge device setup and MLOps lifecycle with over-the-air model updates and data capture to the cloud.

This is set to be another challenging but very helpful session! Deploying ML models on edge devices is one of those things that I know is perfectly possible, and I've seen colleagues complete, but I've never personally done it before. Diving into this process in more detail would be a really informative session, and will pay dividends in future.

Building better products for people of all identities - ABW002

Date: Monday, November 29
Time: 6:15 PM - 7:15 PM
Session type: Breakout Session
Speakers: Diya Wynn, Swami Sivasubramanian, Alex Morrison, Peter Hallinan
Description:

Join this session for a deep dive into inclusion in machine learning with a panel of AWS experts discussing the topic of responsible and inclusive machine learning. Learn to think and build responsibly and inclusively in AI/ML and how to mitigate bias in technology.

There's no point in spending so much time making a technically perfect solution, if that solution isn't inclusive! It's likely you'll find lots of new AI/ML products, solutions or use cases at re:Invent this year, and attending this panel session will make sure that your applications of these new ideas are responsible and inclusive. Everyone goes to re:Invent to learn how to build better products, and hopefully this session will ensure you build those products for everyone when you apply your new knowledge.

Did you have these sessions on your favourites list?
Did I forget something you're excited to see?
Register for AWS re:Invent 2021 here and leave a comment below with your top 5 sessions!

About the Author: Brooke Jamieson is the Head of Enablement - AI/ML and Data at Blackbook.ai, an Australian consulting firm specialising in AI, Automation, DataOps and Digital. Learn more about Blackbook.ai here and learn more about Brooke here.