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Evaluate the reliability of Retrieval Augmented Generation applications using Amazon Bedrock

Favorite Retrieval Augmented Generation (RAG) is a technique that enhances large language models (LLMs) by incorporating external knowledge sources. It allows LLMs to reference authoritative knowledge bases or internal repositories before generating responses, producing output tailored to specific domains or contexts while providing relevance, accuracy, and efficiency. RAG achieves this

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Shared by AWS Machine Learning June 20, 2024

Create natural conversations with Amazon Lex QnAIntent and Knowledge Bases for Amazon Bedrock

Favorite Customer service organizations today face an immense opportunity. As customer expectations grow, brands have a chance to creatively apply new innovations to transform the customer experience. Although meeting rising customer demands poses challenges, the latest breakthroughs in conversational artificial intelligence (AI) empowers companies to meet these expectations. Customers today

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Shared by AWS Machine Learning June 20, 2024

Deploy a Slack gateway for Amazon Bedrock

Favorite In today’s fast-paced digital world, streamlining workflows and boosting productivity are paramount. That’s why we’re thrilled to share an exciting integration that will take your team’s collaboration to new heights. Get ready to unlock the power of generative artificial intelligence (AI) and bring it directly into your Slack workspace.

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Shared by AWS Machine Learning June 19, 2024

Streamline financial workflows with generative AI for email automation

Favorite Many companies across all industries still rely on laborious, error-prone, manual procedures to handle documents, especially those that are sent to them by email. Despite the availability of technology that can digitize and automate document workflows through intelligent automation, businesses still mostly rely on labor-intensive manual document processing. This

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Shared by AWS Machine Learning June 18, 2024

Safeguard a generative AI travel agent with prompt engineering and Guardrails for Amazon Bedrock

Favorite In the rapidly evolving digital landscape, travel companies are exploring innovative approaches to enhance customer experiences. One promising solution is the integration of generative artificial intelligence (AI) to create virtual travel agents. These AI-powered assistants use large language models (LLMs) to engage in natural language conversations, providing personalized recommendations,

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Shared by AWS Machine Learning June 18, 2024

Use zero-shot large language models on Amazon Bedrock for custom named entity recognition

Favorite Name entity recognition (NER) is the process of extracting information of interest, called entities, from structured or unstructured text. Manually identifying all mentions of specific types of information in documents is extremely time-consuming and labor-intensive. Some examples include extracting players and positions in an NFL game summary, products mentioned

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Shared by AWS Machine Learning June 18, 2024

Improving air quality with generative AI

Favorite As of this writing, Ghana ranks as the 27th most polluted country in the world, facing significant challenges due to air pollution. Recognizing the crucial role of air quality monitoring, many African countries, including Ghana, are adopting low-cost air quality sensors. The Sensor Evaluation and Training Centre for West

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Shared by AWS Machine Learning June 18, 2024

Accelerate deep learning training and simplify orchestration with AWS Trainium and AWS Batch

Favorite In large language model (LLM) training, effective orchestration and compute resource management poses a significant challenge. Automation of resource provisioning, scaling, and workflow management is vital for optimizing resource usage and streamlining complex workflows, thereby achieving efficient deep learning training processes. Simplified orchestration enables researchers and practitioners to focus

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Shared by AWS Machine Learning June 17, 2024