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AWS re:Invent 2024: Next-Gen Innovations in AI, Cloud & Data

Analytics Vidhya

The AWS re:Invent 2024 event was packed with exciting updates in cloud computing, AI, and machine learning. AWS showed just how committed they are to helping developers, businesses, and startups thrive with cutting-edge tools.

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Top 7 AWS Services for Machine Learning

Analytics Vidhya

Are you looking to build scalable and effective machine learning solutions? AWS offers a comprehensive suite of services designed to simplify every step of the ML lifecycle, from data collection to model monitoring. In this article, […] The post Top 7 AWS Services for Machine Learning appeared first on Analytics Vidhya.

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Enhanced observability for AWS Trainium and AWS Inferentia with Datadog

AWS Machine Learning Blog

Neuron is the SDK used to run deep learning workloads on Trainium and Inferentia based instances. AWS AI chips, Trainium and Inferentia, enable you to build and deploy generative AI models at higher performance and lower cost. To get started, see AWS Inferentia and AWS Trainium Monitoring.

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Unlocking the power of Model Context Protocol (MCP) on AWS

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If youre an AI-focused developer, technical decision-maker, or solution architect working with Amazon Web Services (AWS) and language models, youve likely encountered these obstacles firsthand. Why MCP matters for AWS users For AWS customers, MCP represents a particularly compelling opportunity. What is the MCP?

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Unlock Faster Machine Learning with Graviton

databricks

We are excited to announce that Graviton , the ARM-based CPU instance offered by AWS, is now supported on the Databricks ML Runtime.

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Using Amazon Q Business with AWS HealthScribe to gain insights from patient consultations

AWS Machine Learning Blog

With the advent of generative AI and machine learning, new opportunities for enhancement became available for different industries and processes. AWS HealthScribe combines speech recognition and generative AI trained specifically for healthcare documentation to accelerate clinical documentation and enhance the consultation experience.

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Discover how nonprofits can utilize no-code machine learning with Amazon SageMaker Canvas

Flipboard

Machine learning (ML) has emerged as a powerful tool to help nonprofits expedite manual processes, quickly unlock insights from data, and accelerate mission outcomesfrom personalizing marketing materials for donors to predicting member churn and donation patterns. This reduces operational overhead for your organization.