Detect industrial defects at low latency with computer vision at the edge with Amazon SageMaker Edge

Favorite Defect detection in manufacturing can benefit from machine learning (ML) and computer vision (CV) to reduce operational costs, improve time to market, and increase productivity, quality, and safety. According to McKinsey, the “benefits of defect detection and other Industry 4.0 applications are estimated to create a potential value of

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Shared by AWS Machine Learning October 23, 2021

Accelerate computer vision training using GPU preprocessing with NVIDIA DALI on Amazon SageMaker

Favorite AWS customers are increasingly training and fine-tuning large computer vision (CV) models with hundreds of terabytes of data and millions of parameters. For example, advanced driver assistance systems (ADAS) train perception models to detect pedestrians, road signs, vehicles, traffic lights, and other objects. Identity verification systems for the financial

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Shared by AWS Machine Learning October 21, 2021

Amazon SageMaker rated as top AI Service Cloud in analyst firm KuppingerCole’s evaluation of AI Service Clouds

Favorite As more European organizations move from experimentation to production for AI projects, the importance of running these projects on a scalable, secure, and cost-efficient platform becomes clear. Building AI solutions from scratch is often beyond the capabilities of many organizations, especially because it requires in-house AI expertise, which is

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Shared by AWS Machine Learning October 20, 2021

Choose the best AI accelerator and model compilation for computer vision inference with Amazon SageMaker

Favorite AWS customers are increasingly building applications that are enhanced with predictions from computer vision models. For example, a fitness application monitors the body posture of users while exercising in front of a camera and provides live feedback to the users as well as periodic insights. Similarly, an inventory inspection

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Shared by AWS Machine Learning October 20, 2021