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Review: AWS AI and Machine Learning stacks up

Recap of AWS re:Invent 2020

by This year the annual re:invent conference organized by AWS was virtual, free and three weeks long. During multiple keynotes and sessions, AWS announced new features, improvements and cloud services. Below is a review of the main announcements impacting compute, database, storage, networking, machine learning and development. Compute On the very first day of the conference, Amazon announced EC2 Mac instances for macOS, adding after many years a new operating system to EC2. This is mainly targeted at processes that only run on Mac OS, like building and testing applications for iOS, MacOS, tvOS and Safari. The first part of Andy Jassy s keynote was focused on announcements related to compute options and serverless technologies. AWS introduced new instance types on different processors and EC2 families, including Intel Xeon M5zn instances, Graviton2-powered C6gn instances, Intel-powered D3/D3en instances, memory-optimized R5b instances and AMD-powered G4ad GPU instances. See InfoQ

re:Invent 2020 Reveals a Step Change in Amazon s AI Strategy

AWS re:Invent 2020, held as a virtual event this year for more than 500,000 attendees, was once again a blitzkrieg of major announcements that collectively have the potential to reshape the course of enterprise technology over the next few years. Among the big news in several areas of AWS s cloud portfolio, artificial intelligence (AI) and machine learning took top billing, with the company actively courting new, more business-oriented audience for its solutions this year. Below, I take a look at some of the highlights and assess what they mean for the market and Amazon s strategy, which is starting to move into some important new directions.

Amazon SageMaker grows ever more powerful as machine learning models head for the edge

Amazon SageMaker helps lead machine learning models to the edge SHARE Machine learning has experienced an incredible increase in usage in the past couple of years. In 2017, deploying machine learning models was considered extremely difficult, something only major organizations had the resources to consider. Then, Amazon Web Services Inc. released the Amazon SageMaker machine learning service. “Customers saw it was much easier to do machine learning once they were using tools like SageMaker,” said Bratin Saha (pictured), vice president and general manager of machine learning services and Amazon AI at Amazon. “Machine learning was no longer niche; machine learning was no longer a fictional thing. It was something that was giving real business value.”

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