Serve 3,000 deep learning models on Amazon EKS with AWS Inferentia for under $50 an hour

Favorite More customers are finding the need to build larger, scalable, and more cost-effective machine learning (ML) inference pipelines in the cloud. Outside of these base prerequisites, the requirements of ML inference pipelines in production vary based on the business use case. A typical inference architecture for applications like recommendation

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Shared by AWS Machine Learning September 30, 2021

Deploy multiple machine learning models for inference on AWS Lambda and Amazon EFS

Favorite You can deploy machine learning (ML) models for real-time inference with large libraries or pre-trained models. Common use cases include sentiment analysis, image classification, and search applications. These ML jobs typically vary in duration and require instant scaling to meet peak demand. You want to process latency-sensitive inference requests

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Shared by AWS Machine Learning September 29, 2021

Virtu Financial enables its customers to apply advanced analytics and machine learning on trade and market data by provisioning Amazon SageMaker

Favorite This is a guest post by Erin Stanton, who currently runs the Global Client Support organization for Virtu Analytics.  Virtu Financial is a leading provider of financial services and products that uses cutting-edge technology to deliver liquidity to the global markets and innovative, transparent trading solutions to its clients.

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Shared by AWS Machine Learning September 29, 2021

How AI is making information more useful

Favorite Today, there’s more information accessible at people’s fingertips than at any point in human history. And advances in artificial intelligence will radically transform the way we use that information, with the ability to uncover new insights that can help us both in our daily lives and in the ways

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Shared by Google AI Technology September 29, 2021

The problem with "tacit/explicit"

Favorite  There is a real problem with the concept of tacit and explicit knowledge, namely the level of disagreement about what these terms really mean. Until this is fixed, these terms may be unusable. I blogged about this issue of the definitional minefield a year ago, and had an experience

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Shared by Nick Milton September 27, 2021