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CBRE and AWS perform natural language queries of structured data using Amazon Bedrock

AWS Machine Learning - AI

In this post, we describe how CBRE partnered with AWS Prototyping to develop a custom query environment allowing natural language query (NLQ) prompts by using Amazon Bedrock, AWS Lambda , Amazon Relational Database Service (Amazon RDS), and Amazon OpenSearch Service. A Lambda function with business logic invokes the primary Lambda function.

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Choice Hotels’ all-in cloud journey to sustainable business value

CIO

Kirkland, a founding member of SustainabilityIT.org, an organization to drive global sustainability through technology leadership, says Choice was the first hospitality company to make a strategic commitment to developing a cloud-native and sustainable platform on AWS.

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Cost-effective document classification using the Amazon Titan Multimodal Embeddings Model

AWS Machine Learning - AI

An Amazon S3 object notification event invokes the embedding AWS Lambda function. The Lambda function reads the document image and translates the image into embeddings by calling Amazon Bedrock and using the Amazon Titan Multimodal Embeddings model. The classification Lambda function receives the Amazon S3 object notification.

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Automating product description generation with Amazon Bedrock

AWS Machine Learning - AI

AWS Lambda – AWS Lambda provides serverless compute for processing. Amazon API Gateway passes the request to AWS Lambda through a proxy integration. When operating on product image inputs, AWS Lambda calls Amazon Rekognition to detect objects in the image. The response is passed back from AWS Lambda to Amazon API Gateway.

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Fundamentals of Data Engineering

Xebia

Architect for scalability. Architecture is leadership. – Werner Vogels, CTO of Amazon Web Services Some areas to keep an eye on while planning for failure: Availability Reliability Recovery Time Objective (RTO) Recovery Point Objective (RPO) Architect for Scalability Scalability in data systems encompasses two main capabilities.

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Shutterstock capitalizes on the cloud’s cutting edge

CIO

The expectation from developers is that they can go faster than they’ve ever gone before and that every part of the lifecycle around this data needs to be elastic, scalable,” he says. The customer hovered for two seconds and didn’t click that type of data. That is invaluable when optimizing your site.”

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The journey of PGA TOUR’s generative AI virtual assistant, from concept to development to prototype

AWS Machine Learning - AI

We use AWS Lambda as our orchestration function responsible for interacting with various data sources, LLMs and error correction based on the user query. The unified, scalable pipeline we developed allows the PGA TOUR to scale to their full history of data, some of which goes back to the 1800s.