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Building a Scalable ML Pipeline and API in AWS

Dzone - DevOps

With rapid progress in the fields of machine learning (ML) and artificial intelligence (AI), it is important to deploy the AI/ML model efficiently in production environments. The architecture downstream ensures scalability, cost efficiency, and real-time access to applications.

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How I replaced Xebia Leadership with Artificial Intelligence

Xebia

That’s right, folks; I replaced the Xebia leadership with artificial intelligence! The magic happens through a combination of Serverless, user input, a CloudFront distribution, a Lambda function, and the OpenAI API. The post How I replaced Xebia Leadership with Artificial Intelligence appeared first on Xebia.

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Revolutionizing data management: Trends driving security, scalability, and governance in 2025

CIO

Augmented data management with AI/ML Artificial Intelligence and Machine Learning transform traditional data management paradigms by automating labour-intensive processes and enabling smarter decision-making. These approaches facilitate multi-cloud and hybrid environments, enhancing performance and resilience.

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Unlocking the Power of Serverless AI/ML on AWS: Expert Strategies for Scalable and Secure Applications

Dzone - DevOps

Amazon Web Services (AWS) provides an expansive suite of tools to help developers build and manage serverless applications with ease. In this article, we delve into serverless AI/ML on AWS, exploring best practices, implementation strategies, and an example to illustrate these concepts in action.

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Amazon Bedrock Flows is now generally available with enhanced safety and traceability

AWS Machine Learning - AI

Reduced time and effort in testing and deploying AI workflows with SDK APIs and serverless infrastructure. We can also quickly integrate flows with our applications using the SDK APIs for serverless flow execution — without wasting time in deployment and infrastructure management.

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DataRobot Acquires Agnostic to Gain Distributed Covalent Platform for AI Apps

DevOps.com

DataRobot,a provider of a platform for building artificial intelligence (AI) applications, this week acquired Agnostic, a provider of an open source distributed computing platform, dubbed Covalent, that will be integrated with its machine learning operations (MLOps) framework.

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Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

AWS Machine Learning - AI

From deriving insights to powering generative artificial intelligence (AI) -driven applications, the ability to efficiently process and analyze large datasets is a vital capability. That’s where the new Amazon EMR Serverless application integration in Amazon SageMaker Studio can help.