Optimizing Real-Time AI Inference with AWS SageMaker and AWS Lambda for Large-Scale Business Applications

Due to high performance and scalability requirements the real-time AI inference needed in today's massive business applications is simply vital. The author goes on to depict how he successfully improves the use of AWS SageMaker (Amazon Web Services managed service for building, training, and deploying machine learning models) in both model training and deployment by employing AWS Lambda (an event-driven serverless computing platform). With this method businesses can now achieve AI inference at a low cost and with low latency. The main direction is implementing such AWS' AI services as Transcribe, Recognition and Monkey Learn, but users may also employ some more light-weight processors like fg. Practical examples here show that across industries businesses can now achieve both mode inference and decision-making based on scalable AI. This paper presents guidance as to how to deploy AI inference pipelines on AWS by following cheaper and more efficient means.