AWS Innovate – AI/ML Edition Takeaways


The past 24th of February, I attended the AWS Innovate – AI/ML Edition, Technical Decision Maker Track; it was an exciting event, so I’d like to share some quick takeaways:

πŸ“Œ Scaling ML as a Journey; 7 fundamentals steps: Culture, Team Enablement, Data Strategy, PoC, Repeatability, Scale, Evolution.

πŸ“Œ S3 strong after-read-consistency: was introduced at last re:Invent, but now I had time to check it out properly. It’s an essential feature for migrations or Data Lakes to ensure having the latest version of documents or files.

πŸ“Œ New AWS AI Services such as Amazon Lookout for Vision: also introduced at last re:Invent; again, now I had the chance to try it. It seems very appropriate for industrial applications, such as finding defective parts.

πŸ“Œ The proper way to architect AWS ML Apps: ML Lens

πŸ“Œ Secure Machine Learning for Regulated Industries: I especially enjoyed this presentation, quite hand-on and lots of RL security practices for Sagemaker.

I’m still going through the other tracks, so expect a full post in the coming weeks.

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