Generative Data Intelligence

Tag: AWS Professional Services

Create summaries of recordings using generative AI with Amazon Bedrock and Amazon Transcribe | Amazon Web Services

Meeting notes are a crucial part of collaboration, yet they often fall through the cracks. Between leading discussions, listening closely, and typing notes, it’s...

Create a web UI to interact with LLMs using Amazon SageMaker JumpStart | Amazon Web Services

The launch of ChatGPT and rise in popularity of generative AI have captured the imagination of customers who are curious about how they can...

Techniques for automatic summarization of documents using language models | Amazon Web Services

Summarization is the technique of condensing sizable information into a compact and meaningful form, and stands as a cornerstone of efficient communication in our...

Use custom metadata created by Amazon Comprehend to intelligently process insurance claims using Amazon Kendra | Amazon Web Services

Structured data, defined as data following a fixed pattern such as information stored in columns within databases, and unstructured data, which lacks a specific...

Accelerating AI/ML development at BMW Group with Amazon SageMaker Studio | Amazon Web Services

This post is co-written with Marc Neumann, Amor Steinberg and Marinus Krommenhoek from BMW Group. The BMW Group – headquartered in Munich, Germany –...

Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker | Amazon Web Services

This is a joint blog with AWS and Philips. Philips is a health technology company focused on improving people’s lives through meaningful innovation. Since...

Implement real-time personalized recommendations using Amazon Personalize | Amazon Web Services

At a basic level, Machine Learning (ML) technology learns from data to make predictions. Businesses use their data with an ML-powered personalization service to...

MAS Public Cloud Guidelines: A Deep Dive into its Impact on Cloud Security – Fintech Singapore

Amidst a rapidly digitalising world, accelerated further by the COVID-19 pandemic, cloud technology has become a pivotal cornerstone for businesses worldwide. Recently, the Monetary...

Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD | Amazon Web Services

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is...

Bundesliga Match Facts Shot Speed – Who fires the hardest shots in the Bundesliga? | Amazon Web Services

There’s a kind of magic that surrounds a soccer shot so powerful, it leaves spectators, players, and even commentators in a momentary state of...

Optimize pet profiles for Purina’s Petfinder application using Amazon Rekognition Custom Labels and AWS Step Functions | Amazon Web Services

Purina US, a subsidiary of Nestlé, has a long history of enabling people to more easily adopt pets through Petfinder, a digital marketplace of...

Robust time series forecasting with MLOps on Amazon SageMaker | Amazon Web Services

In the world of data-driven decision-making, time series forecasting is key in enabling businesses to use historical data patterns to anticipate future outcomes. Whether...

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