Technical How-to

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Build conversational interfaces for structured data using Amazon Bedrock Knowledge Bases

Organizations manage extensive structured data in databases and data warehouses. Large language models (LLMs) have transformed natural language processing (NLP), yet converting conversational queries into structured data analysis remains complex. Data analysts must translate business questions into SQL queries, creating workflow bottlenecks. Amazon Bedrock Knowledge Bases enables direct natural language interactions with structured data sources. […]

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Build generative AI solutions with Amazon Bedrock

Generative AI is revolutionizing how businesses operate, interact with customers, and innovate. If you’re embarking on the journey to build a generative AI-powered solution, you might wonder how to navigate the complexities involved from selecting the right models to managing prompts and enforcing data privacy. In this post, we show you how to build generative

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Make videos accessible with automated audio descriptions using Amazon Nova

According to the World Health Organization, more than 2.2 billion people globally have vision impairment. For compliance with disability legislation, such as the Americans with Disabilities Act (ADA) in the United States, media in visual formats like television shows or movies are required to provide accessibility to visually impaired people. This often comes in the

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Accelerating Articul8’s domain-specific model development with Amazon SageMaker HyperPod

This post was co-written with Renato Nascimento, Felipe Viana, Andre Von Zuben from Articul8. Generative AI is reshaping industries, offering new efficiencies, automation, and innovation. However, generative AI requires powerful, scalable, and resilient infrastructures that optimize large-scale model training, providing rapid iteration and efficient compute utilization with purpose-built infrastructure and automated cluster management. In this

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How Gardenia Technologies helps customers create ESG disclosure reports 75% faster using agentic generative AI on Amazon Bedrock

This post was co-written with Federico Thibaud, Neil Holloway, Fraser Price, Christian Dunn, and Frederica Schrager from Gardenia Technologies “What gets measured gets managed” has become a guiding principle for organizations worldwide as they begin their sustainability and environmental, social, and governance (ESG) journeys. Companies are establishing baselines to track their progress, supported by an expanding framework of reporting standards,

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Automate customer support with Amazon Bedrock, LangGraph, and Mistral models

AI agents are transforming the landscape of customer support by bridging the gap between large language models (LLMs) and real-world applications. These intelligent, autonomous systems are poised to revolutionize customer service across industries, ushering in a new era of human-AI collaboration and problem-solving. By harnessing the power of LLMs and integrating them with specialized tools

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Build responsible AI applications with Amazon Bedrock Guardrails

As organizations embrace generative AI, they face critical challenges in making sure their applications align with their designed safeguards. Although foundation models (FMs) offer powerful capabilities, they can also introduce unique risks, such as generating harmful content, exposing sensitive information, being vulnerable to prompt injection attacks, and returning model hallucinations. Amazon Bedrock Guardrails has helped

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Stream multi-channel audio to Amazon Transcribe using the Web Audio API

Multi-channel transcription streaming is a feature of Amazon Transcribe that can be used in many cases with a web browser. Creating this stream source has it challenges, but with the JavaScript Web Audio API, you can connect and combine different audio sources like videos, audio files, or hardware like microphones to obtain transcripts. In this

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Build a serverless audio summarization solution with Amazon Bedrock and Whisper

Recordings of business meetings, interviews, and customer interactions have become essential for preserving important information. However, transcribing and summarizing these recordings manually is often time-consuming and labor-intensive. With the progress in generative AI and automatic speech recognition (ASR), automated solutions have emerged to make this process faster and more efficient. Protecting personally identifiable information (PII)

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Implement semantic video search using open source large vision models on Amazon SageMaker and Amazon OpenSearch Serverless

As companies and individual users deal with constantly growing amounts of video content, the ability to perform low-effort search to retrieve videos or video segments using natural language becomes increasingly valuable. Semantic video search offers a powerful solution to this problem, so users can search for relevant video content based on textual queries or descriptions.

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