AWS Machine Learning Blog

Category: Analytics

Introducing guardrails in Amazon Bedrock Knowledge Bases

Amazon Bedrock Knowledge Bases is a fully managed capability that helps you securely connect foundation models (FMs) in Amazon Bedrock to your company data using Retrieval Augmented Generation (RAG). This feature streamlines the entire RAG workflow, from ingestion to retrieval and prompt augmentation, eliminating the need for custom data source integrations and data flow management. […]

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Build an automated insight extraction framework for customer feedback analysis with Amazon Bedrock and Amazon QuickSight

In this post, we explore how to integrate LLMs into enterprise applications to harness their generative capabilities. We delve into the technical aspects of workflow implementation and provide code samples that you can quickly deploy or modify to suit your specific requirements. Whether you’re a developer seeking to incorporate LLMs into your existing systems or a business owner looking to take advantage of the power of NLP, this post can serve as a quick jumpstart.

Implement exact match with Amazon Lex QnAIntent

This post is a continuation of Creating Natural Conversations with Amazon Lex QnAIntent and Amazon Bedrock Knowledge Base. In summary, we explored new capabilities available through Amazon Lex QnAIntent, powered by Amazon Bedrock, that enable you to harness natural language understanding and your own knowledge repositories to provide real-time, conversational experiences. In many cases, Amazon […]

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

In today’s data-driven world, industries across various sectors are accumulating massive amounts of video data through cameras installed in their warehouses, clinics, roads, metro stations, stores, factories, or even private facilities. This video data holds immense potential for analysis and monitoring of incidents that may occur in these locations. From fire hazards to broken equipment, […]

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Enhance image search experiences with Amazon Personalize, Amazon OpenSearch Service, and Amazon Titan Multimodal Embeddings in Amazon Bedrock

A variety of different techniques have been used for returning images relevant to search queries. Historically, the idea of creating a joint embedding space to facilitate image captioning or text-to-image search has been of interest to machine learning (ML) practitioners and businesses for quite a while. Contrastive Language–Image Pre-training (CLIP) and Bootstrapping Language-Image Pre-training (BLIP) […]

How LotteON built dynamic A/B testing for their personalized recommendation system

This post is co-written with HyeKyung Yang, Jieun Lim, and SeungBum Shim from LotteON. LotteON is transforming itself into an online shopping platform that provides customers with an unprecedented shopping experience based on its in-store and online shopping expertise. Rather than simply selling the product, they create and let customers experience the product through their […]

Amazon SageMaker now integrates with Amazon DataZone to streamline machine learning governance

Unlock ML governance with SageMaker-DataZone integration: streamline infrastructure, collaborate, and govern data/ML assets.

How Veritone uses Amazon Bedrock, Amazon Rekognition, Amazon Transcribe, and information retrieval to update their video search pipeline

This post is co-written with Tim Camara, Senior Product Manager at Veritone. Veritone is an artificial intelligence (AI) company based in Irvine, California. Founded in 2014, Veritone empowers people with AI-powered software and solutions for various applications, including media processing, analytics, advertising, and more. It offers solutions for media transcription, facial recognition, content summarization, object […]

Amazon Q Business and Amazon Q in QuickSight empowers employees to be more data-driven and make better, faster decisions using company knowledge

Today, we announced the General Availability of Amazon Q, the most capable generative AI powered assistant for accelerating software development and leveraging companies’ internal data. “During the preview, early indications signaled Amazon Q could help our customers’ employees become more than 80% more productive at their jobs; and with the new features we’re planning on […]

Use everyday language to search and retrieve data with Mixtral 8x7B on Amazon SageMaker JumpStart

With the widespread adoption of generative artificial intelligence (AI) solutions, organizations are trying to use these technologies to make their teams more productive. One exciting use case is enabling natural language interactions with relational databases. Rather than writing complex SQL queries, you can describe in plain language what data you want to retrieve or manipulate. […]