AWS re:Invent 2018 — Machine Learning recap (Monday & Tuesday)

Keeping track of new service and feature launches at re:Invent is pretty challenging, so here’s a quick recap on what happened yesterday and today.

If you’re still trying to catch up with the pre-re:Invent launches, this post should help!
  • Machine Learning University: more than 30 self-service, self-paced digital courses with more than 45 hours of courses, videos, and labs for four key groups: developers, data scientists, data platform engineers, and business professionals. Each course starts with the fundamentals, and builds on those through real-world examples and labs, allowing developers to explore machine learning through some fun problems we have had to solve at Amazon.
  • C5N instances and P3DN instances: 100Gbit networking for both (why this matters), more of everything for the latter (GPU RAM, vCPUs, etc.).
  • Dynamic Training for Apache MXNet (more frameworks to follow): With Dynamic Training, practitioners running compute-intensive training jobs can benefit economies of scale, and reduce training costs by pulling in Spot Instances and Reserved Instances, and releasing them when they are interrupted, all without stopping the training job.
  • Amazon Translate custom terminology: the ability to customize Amazon Translate output to use company- and domain-specific vocabulary.
  • Amazon Comprehend Medical: a new natural language processing service that makes it easy to use Machine Learning to extract relevant medical information
  • Amazon Quicksight ML Insights (preview): (1) ML-powered anomaly detection to help customers uncover hidden insights by continuously analyzing across billions of data points (2) ML-powered forecasting and what-if analysis to predict key business metrics with point-and-click simplicity (3) Auto-narratives to help customers tell the story of their dashboard in a plain-language narrative.

More coming tomorrow :) Happy to answer questions! Please follow me on Twitter for more live news and content.

About the Author

Julien Simon is the Chief Evangelist at Arcee AI , specializing in Small Language Models and enterprise AI solutions. Recognized as the #1 AI Evangelist globally by AI Magazine in 2021, he brings over 30 years of technology leadership experience to his role.

With 650+ speaking engagements worldwide and 350+ technical blog posts, Julien is a leading voice in practical AI implementation, cost-effective AI solutions, and the democratization of artificial intelligence. His expertise spans open-source AI, Small Language Models, enterprise AI strategy, and edge computing optimization.

Previously serving as Principal Evangelist at AWS and Chief Evangelist at Hugging Face, Julien has authored books on Amazon SageMaker and contributed to the open-source AI ecosystem. His mission is to make AI accessible, understandable, and controllable for everyone.