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Meeting Summary

ARC302-R - [REPEAT] Patterns for hosting ML models in low latency microservices

Session Description

Deploying deep learning models in a low latency microservices environment is challenging. However, without this, we wouldn't have many of the AI applications that we have today, such as voice response systems, fast image and video analytics, responsive visual search engines, and real-time predictions for business transactions, such as for ride-hailing apps. These challenges are due to the high amount of compute involved, latencies of models and costs, difficulties in deployment, A/B testing, and monitoring performance. In this session, we demonstrate Amazon Elastic Inference, Amazon SageMaker Neo and batch inference, AWS Inferentia, and AWS X-Ray, and we discuss how to use these services to overcome these challenges.

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Chalk Talk
Architecture
300 - Advanced
Please note that session information is subject to change.
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