re:Invent Roundup 2020 with Swami Sivasubramanian

EPISODE 437
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About this Episode

Today we're kicking off our annual re:invent series joined by Swami Sivasubramanian, VP of Artificial Intelligence, at AWS. During re:Invent last week, Amazon made a ton of announcements on the machine learning front, including quite a few advancements to SageMaker. In this roundup conversation, we discuss the motivation for hosting the first-ever machine learning keynote at the conference, a bunch of details surrounding tools like Pipelines for workflow management, Clarify for bias detection, and JumpStart for easy to use algorithms and notebooks, and many more. We also discuss the emphasis placed on DevOps and MLOps tools in these announcements, and how the tools are all interconnected. Finally, we briefly touch on the announcement of the AWS feature store, but be sure to check back later this week for a more in-depth discussion on that particular release!
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Thanks to our sponsor Amazon Web Services

You know AWS as a cloud computing technology leader, but did you realize the company offers a broad array of services and infrastructure at all three layers of the machine learning technology stack? AWS has helped more than 100,000 customers of all sizes and across industries to innovate using ML and AI with industry-leading capabilities and they’re taking the same approach to make it easy, practical, and cost-effective for customers to use generative AI in their businesses. At the bottom layer of the ML stack, they’re making generative AI cost-efficient with Amazon EC2 Inf2 instances powered by AWS Inferentia2 chips. At the middle layer, they’re making generative AI app development easier with Amazon Bedrock, a managed service that makes pre-trained FMs easily accessible via an API. And at the top layer, Amazon CodeWhisperer is generally available now, with support for more than 10 programming languages.

To learn more about AWS ML and AI services, and how they’re helping customers accelerate their machine learning journeys, visit twimlai.com/go/awsml.

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