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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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Population Health Analytics with AWS HealthLake and QuickSight

Analytics Vidhya

Healthcare Data using AI Medical Interoperability and machine learning (ML) are two remarkable innovations that are disrupting the healthcare industry. Medical Interoperability along with AI & Machine Learning […].

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Building ML Model in AWS Sagemaker

Analytics Vidhya

Image: [link] Introduction Artificial Intelligence & Machine learning is the most exciting and disruptive area in the current era. AI/ML has become an integral part of research and innovations. The main objective of the AI system is to solve real-world problems where […].

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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning Blog

The emergence of generative AI has ushered in a new era of possibilities, enabling the creation of human-like text, images, code, and more. Solution overview For this solution, you deploy a demo application that provides a clean and intuitive UI for interacting with a generative AI model, as illustrated in the following screenshot.

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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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Transcribe, translate, and summarize live streams in your browser with AWS AI and generative AI services

AWS Machine Learning Blog

Recognizing this need, we have developed a Chrome extension that harnesses the power of AWS AI and generative AI services, including Amazon Bedrock , an AWS managed service to build and scale generative AI applications with foundation models (FMs). The user signs in by entering a user name and a password.

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How Rufus doubled their inference speed and handled Prime Day traffic with AWS AI chips and parallel decoding

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These inefficiencies are particularly pronounced during high-demand events like Amazon Prime Day, where systems like Rufusthe Amazon AI-powered shopping assistantmust handle massive scale while adhering to strict latency and throughput requirements. Lowering this latency improves perceived responsiveness and overall user experience.

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