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Low Code and No Code Platforms for AI and Computer Vision

Viso.ai

Low code and no code for AI Business benefits of platforms About us: At viso.ai, we power Viso Suite , the leading no-code/low-code computer vision platform. Our technology is used by leaders worldwide to rapidly develop, deploy and scale real-time computer vision systems. Get a demo for your organization.

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How Veriff decreased deployment time by 80% using Amazon SageMaker multi-model endpoints

AWS Machine Learning Blog

These models range from lightweight tree-based models to deep learning computer vision models, which need to run on GPUs to achieve low latency and improve the user experience. This approach was initially used for all company services, including microservices that run expensive computer vision ML models.

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Top 5 Generative AI Integration Companies to drive Customer Support in 2023

Chatbots Life

10CLOUDS Year Founded : 2009 HQ : Warsaw, Poland Team Size : 51–200 employees Clients : TrustStamp (Identity verification), Emergent Tech (G-Coin), AlephZero (Blockchain), Tapeke (BitCoin Software Development), Tagasauris (Crowdsourcing Software Development), CallerSmart. Elite Service Delivery partner of NVIDIA.

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Build an end-to-end MLOps pipeline for visual quality inspection at the edge – Part 1

AWS Machine Learning Blog

In this series, we walk you through the process of architecting and building an integrated end-to-end MLOps pipeline for a computer vision use case at the edge using SageMaker, AWS IoT Greengrass, and the AWS Cloud Development Kit (AWS CDK). So if you have a DevOps challenge or want to go for a run: let him know.

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Designing generative AI workloads for resilience

AWS Machine Learning Blog

She has a diverse background, having worked in many technical disciplines, including software development, agile leadership, and DevOps, and is an advocate for women in tech. He holds an MSEE from the University of Michigan, where he worked on computer vision for autonomous vehicles.

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Accelerate development of ML workflows with Amazon Q Developer in Amazon SageMaker Studio

AWS Machine Learning Blog

James’s work covers a wide range of ML use cases, with a primary interest in computer vision, deep learning, and scaling ML across the enterprise. Prior to joining AWS, James was an architect, developer, and technology leader for over 10 years, including 6 years in engineering and 4 years in marketing & advertising industries.

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Optimize pet profiles for Purina’s Petfinder application using Amazon Rekognition Custom Labels and AWS Step Functions

AWS Machine Learning Blog

The solution uses the following services: Amazon API Gateway is a fully managed service that makes it easy for developers to publish, maintain, monitor, and secure APIs at any scale. Amazon Rekognition offers pre-trained and customizable computer vision (CV) capabilities to extract information and insights from your images and videos.