Remove 2023 Remove AWS Remove K-nearest Neighbors
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AWS empowers sales teams using generative AI solution built on Amazon Bedrock

AWS Machine Learning Blog

At AWS, we are transforming our seller and customer journeys by using generative artificial intelligence (AI) across the sales lifecycle. It will be able to answer questions, generate content, and facilitate bidirectional interactions, all while continuously using internal AWS and external data to deliver timely, personalized insights.

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From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 2

AWS Machine Learning Blog

For a qualitative question like “What caused inflation in 2023?”, However, for a quantitative question such as “What was the average inflation in 2023?”, For instance, instead of saying “What caused inflation in 2023?”, the user could disambiguate by asking “What caused inflation in 2023 according to analysts?”,

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Talk to your slide deck using multimodal foundation models on Amazon Bedrock – Part 3

AWS Machine Learning Blog

Part 1 uses AWS services including Amazon Bedrock , Amazon SageMaker , and Amazon OpenSearch Serverless. We performed a k-nearest neighbor (k-NN) search to retrieve the most relevant embedding matching the question. You can do this by deleting the stacks using the AWS CloudFormation console. 13636-13645.

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Talk to your slide deck using multimodal foundation models hosted on Amazon Bedrock and Amazon SageMaker – Part 2

AWS Machine Learning Blog

We used AWS services including Amazon Bedrock , Amazon SageMaker , and Amazon OpenSearch Serverless in this solution. In this series, we use the slide deck Train and deploy Stable Diffusion using AWS Trainium & AWS Inferentia from the AWS Summit in Toronto, June 2023 to demonstrate the solution.

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Implement serverless semantic search of image and live video with Amazon Titan Multimodal Embeddings

AWS Machine Learning Blog

Kinesis Video Streams makes it straightforward to securely stream video from connected devices to AWS for analytics, machine learning (ML), playback, and other processing. Starting December 2023, you can use the Amazon Titan Multimodal Embeddings model for use cases like searching images by text, image, or a combination of text and image.

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Talk to your slide deck using multimodal foundation models hosted on Amazon Bedrock and Amazon SageMaker – Part 1

AWS Machine Learning Blog

and AWS services including Amazon Bedrock and Amazon SageMaker to perform similar generative tasks on multimodal data. In this post, we use the slide deck titled Train and deploy Stable Diffusion using AWS Trainium & AWS Inferentia from the AWS Summit in Toronto, June 2023, to demonstrate the solution.

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From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 1

AWS Machine Learning Blog

The AWS Generative AI Innovation Center (GenAIIC) is a team of AWS science and strategy experts who have deep knowledge of generative AI. They help AWS customers jumpstart their generative AI journey by building proofs of concept that use generative AI to bring business value.

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