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Tag: ML Models

How Axfood enables accelerated machine learning throughout the organization using Amazon SageMaker | Amazon Web Services

This is a guest post written by Axfood AB.  In this post, we share how Axfood, a...

Streamline diarization using AI as an assistive technology: ZOO Digitalā€™s story | Amazon Web Services

ZOO Digital provides end-to-end localization and media services to adapt original TV and movie content to different languages, regions, and cultures. It makes globalization...

Run ML inference on unplanned and spiky traffic using Amazon SageMaker multi-model endpoints | Amazon Web Services

Amazon SageMaker multi-model endpoints (MMEs) are a fully managed capability of SageMaker inference that allows you to deploy thousands of models on a single...

Detect anomalies in manufacturing data using Amazon SageMaker Canvas | Amazon Web Services

With the use of cloud computing, big data and machine learning (ML) tools like Amazon Athena or Amazon SageMaker have become available and useable...

How BigBasket improved AI-enabled checkout at their physical stores using Amazon SageMaker | Amazon Web Services

This post is co-written with Santosh Waddi and Nanda Kishore Thatikonda from BigBasket. BigBasket is Indiaā€™s largest...

Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access | Amazon Web Services

Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs...

How Booking.com modernized its ML experimentation framework with Amazon SageMaker | Amazon Web Services

This post is co-written with Kostia Kofman and Jenny Tokar from Booking.com. As a global leader in...

Deploy large language models for a healthtech use case on Amazon SageMaker | Amazon Web Services

In 2021, the pharmaceutical industry generated $550 billion in US revenue. Pharmaceutical companies sell a variety of different, often novel, drugs on the market,...

How HSR.health is limiting risks of disease spillover from animals to humans using Amazon SageMaker geospatial capabilities | Amazon Web Services

This is a guest post co-authored by Ajay K Gupta, Jean Felipe Teotonio and Paul A Churchyard from HSR.health. HSR.health is a geospatial health...

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs | Amazon Web Services

Generative artificial intelligence (AI) applications built around large language models (LLMs) have demonstrated the potential to create and accelerate economic value for businesses. Examples...

Researchers Map AI Threat Landscape, Risks

Many of the security problems of large language models (LLMs) boil down to a simple fact: The heart of all LLMs is a black...

Fine-tune and deploy Llama 2 models cost-effectively in Amazon SageMaker JumpStart with AWS Inferentia and AWS Trainium | Amazon Web Services

Today, weā€™re excited to announce the availability of Llama 2 inference and fine-tuning support on AWS Trainium and AWS Inferentia instances in Amazon SageMaker...

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