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Real value, real time: Production AI with Amazon SageMaker and Tecton

AWS Machine Learning Blog

It seems straightforward at first for batch data, but the engineering gets even more complicated when you need to go from batch data to incorporating real-time and streaming data sources, and from batch inference to real-time serving. You can also find Tecton at AWS re:Invent.

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Accelerate disaster response with computer vision for satellite imagery using Amazon SageMaker and Amazon Augmented AI

AWS Machine Learning Blog

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. The solution is then able to make predictions on the rest of the training data, and route lower-confidence results for human review.

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LLMOps: What It Is, Why It Matters, and How to Implement It

The MLOps Blog

Data and workflow orchestration: Ensuring efficient data pipeline management and scalable workflows for LLM performance. Combine this with the serverless BentoCloud or an auto-scaling group on a cloud platform like AWS to ensure your resources match the demand. Caption : RAG system architecture.

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Generative AI for agriculture: How Agmatix is improving agriculture with Amazon Bedrock

AWS Machine Learning Blog

This post describes how Agmatix uses Amazon Bedrock and AWS fully featured services to enhance the research process and development of higher-yielding seeds and sustainable molecules for global agriculture. AWS generative AI services provide a solution In addition to other AWS services, Agmatix uses Amazon Bedrock to solve these challenges.

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