AWS Machine Learning Blog

DECEMBER 4, 2024

Businesses are under pressure to show return on investment (ROI) from AI use cases, whether predictive machine learning (ML) or generative AI. Only 54% of ML prototypes make it to production, and only 5% of generative AI use cases make it to production. This post is cowritten with Isaac Cameron and Alex Gnibus from Tecton.

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Flipboard

APRIL 23, 2025

National Laboratory has implemented an AI-driven document processing platform that integrates named entity recognition (NER) and large language models (LLMs) on Amazon SageMaker AI. In this post, we discuss how you can build an AI-powered document processing platform with open source NER and LLMs on SageMaker.

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AWS Machine Learning Blog

JANUARY 10, 2024

Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. In this post, we discuss how the AWS AI/ML team collaborated with the Merck Human Health IT MLOps team to build a solution that uses an automated workflow for ML model approval and promotion with human intervention in the middle.

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ML ML AWS Machine Learning 134

AWS Machine Learning Blog

MAY 23, 2023

A recent PwC CEO survey unveiled that 84% of Canadian CEOs agree that artificial intelligence (AI) will significantly change their business within the next 5 years, making this technology more critical than ever. The following diagram illustrates the workflow.

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Machine Learning Machine Learning AWS ML 102

Pickl AI

DECEMBER 4, 2023

Imagine this: we collect loads of data, right? Data Intelligence takes that data, adds a touch of AI and Machine Learning magic, and turns it into insights. It’s not just about having data; it’s about turning that data into real wisdom for better products and services. These insights?

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Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 52

AWS Machine Learning Blog

MARCH 5, 2025

In this post, we explain how BMW uses generative AI technology on AWS to help run these digital services with high availability. It requires checking many systems and teams, many of which might be failing, because theyre interdependent. It can be difficult to determine the root cause of issues in situations like this.

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