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Tag: Amazon Comprehend

Data governance in the age of generative AI | Amazon Web Services

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach....

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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...

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...

Unstructured data management and governance using AWS AI/ML and analytics services | Amazon Web Services

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have...

Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets | Amazon Web Services

Multi-modal data is a valuable component of the financial industry, encompassing market, economic, customer, news and social media, and risk data. Financial organizations generate,...

Build a classification pipeline with Amazon Comprehend custom classification (Part I) | Amazon Web Services

“Data locked away in text, audio, social media, and other unstructured sources can be a competitive advantage for firms that figure out how to...

Visualize an Amazon Comprehend analysis with a word cloud in Amazon QuickSight | Amazon Web Services

Searching for insights in a repository of free-form text documents can be like finding a needle in a haystack. A traditional approach might be...

Zero-shot and few-shot prompting for the BloomZ 176B foundation model with the simplified Amazon SageMaker JumpStart SDK | Amazon Web Services

Amazon SageMaker JumpStart is a machine learning (ML) hub offering algorithms, models, and ML solutions. With SageMaker JumpStart, ML practitioners can choose from a...

What is Enterprise AI?

Introduction to Enterprise AI Time is of the essence, and automation is the answer. Amidst the struggles of tedious and mundane tasks, human-led errors, haywire...

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