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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. With machine learning, these processes can be refined over time and anomalies can be predicted before they arise.

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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 Serverless Technologies Can Achieve Optimal DevOps Practices

DevOps.com

However, although engineering resources may be slim, serverless offers new solutions to tackle the DevOps challenge. From improved IoT devices to cost-effective machine learning applications, the serverless ecosystem is […].

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Build a reverse image search engine with Amazon Titan Multimodal Embeddings in Amazon Bedrock and AWS managed services

AWS Machine Learning - AI

Exclusive to Amazon Bedrock, the Amazon Titan family of models incorporates 25 years of experience innovating with AI and machine learning at Amazon. Store embeddings : Ingest the generated embeddings into an OpenSearch Serverless vector index, which serves as the vector database for the solution. b64encode(resized_image).decode('utf-8')

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Building accessible tools for large-scale computation and machine learning

O'Reilly Media - Data

The O’Reilly Data Show Podcast: Eric Jonas on Pywren, scientific computation, and machine learning. Jonas and his collaborators are working on a related project, NumPyWren, a system for linear algebra built on a serverless architecture. Jonas is also affiliated with UC Berkeley’s RISE Lab.

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

AWS Machine Learning - AI

Traditionally, building frontend and backend applications has required knowledge of web development frameworks and infrastructure management, which can be daunting for those with expertise primarily in data science and machine learning.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

API Gateway is serverless and hence automatically scales with traffic. The advantage of using Application Load Balancer is that it can seamlessly route the request to virtually any managed, serverless or self-hosted component and can also scale well. It’s serverless so you don’t have to manage the infrastructure.