AWS re:Invent 2020: How to choose the right instance type for ML inference

AWS offers a breadth and depth of machine learning (ML) infrastructure you can use through either a do-it-yourself approach or a fully managed approach with Amazon SageMaker. In this session, explore how to choose the proper instance for ML inference based on latency and throughput requirements, model size and complexity, framework choice, and portability. Join this session to compare and contrast compute-optimized CPU-only instances, such as Amazon EC2 C4 and C5; high-performance GPU instances, such as Amazon EC2 G4 and P3; cost-effective variable-size GPU acceleration with Amazon Elastic Inference; and highest performance/cost with Amazon EC2 Inf1 instances powered by custom-designed AWS Inferentia chips.

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[rafaelortega]

Very impressive demonstration. I would like to congratulate the speaker. It is the best presentation of this series I have seen.

[ravideena]

Images/sec. Is this OCR processing(Textract)? What is the use case