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Tag: Amazon Comprehend

Techniques and approaches for monitoring large language models on AWS | Amazon Web Services

Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP), improving tasks such as language translation, text summarization, and sentiment analysis....

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Easily build semantic image search using Amazon Titan | Amazon Web Services

Digital publishers are continuously looking for ways to streamline and automate their media workflows to generate and publish new content as rapidly as they...

Simplify data prep for generative AI with Amazon SageMaker Data Wrangler | Amazon Web Services

Generative artificial intelligence (generative AI) models have demonstrated impressive capabilities in generating high-quality text, images, and other content. However, these models require massive amounts...

Build well-architected IDP solutions with a custom lens – Part 1: Operational excellence | Amazon Web Services

The IDP Well-Architected Lens is intended for all AWS customers who use AWS to run intelligent document processing (IDP) solutions and are searching for...

Build well-architected IDP solutions with a custom lens – Part 2: Security | Amazon Web Services

Building a production-ready solution in AWS involves a series of trade-offs between resources, time, customer expectation, and business outcome. The AWS Well-Architected Framework helps...

Build well-architected IDP solutions with a custom lens – Part 3: Reliability | Amazon Web Services

The IDP Well-Architected Custom Lens is intended for all AWS customers who use AWS to run intelligent document processing (IDP) solutions and are searching...

Build well-architected IDP solutions with a custom lens – Part 5: Cost optimization | Amazon Web Services

Building a production-ready solution in the cloud involves a series of trade-off between resources, time, customer expectation, and business outcome. The AWS Well-Architected Framework...

Build well-architected IDP solutions with a custom lens – Part 6: Sustainability | Amazon Web Services

An intelligent document processing (IDP) project typically combines optical character recognition (OCR) and natural language processing (NLP) to automatically read and understand documents. Customers...

Flag harmful content using Amazon Comprehend toxicity detection | Amazon Web Services

Online communities are driving user engagement across industries like gaming, social media, ecommerce, dating, and e-learning. Members of these online communities trust platform owners...

Build trust and safety for generative AI applications with Amazon Comprehend and LangChain | Amazon Web Services

We are witnessing a rapid increase in the adoption of large language models (LLM) that power generative AI applications across industries. LLMs are capable...

Use machine learning without writing a single line of code with Amazon SageMaker Canvas | Amazon Web Services

In the recent past, using machine learning (ML) to make predictions, especially for data in the form of text and images, required extensive ML...

How Reveal’s Logikcull used Amazon Comprehend to detect and redact PII from legal documents at scale | Amazon Web Services

Today, personally identifiable information (PII) is everywhere. PII is in emails, slack messages, videos, PDFs, and so on. It refers to any data or...

Deploy and fine-tune foundation models in Amazon SageMaker JumpStart with two lines of code | Amazon Web Services

We are excited to announce a simplified version of the Amazon SageMaker JumpStart SDK that makes it straightforward to build, train, and deploy foundation...

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