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

CIO

From data masking technologies that ensure unparalleled privacy to cloud-native innovations driving scalability, these trends highlight how enterprises can balance innovation with accountability. With machine learning, these processes can be refined over time and anomalies can be predicted before they arise.

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Top 11 LLM Tools That Ensure Smooth LLM Operations

Openxcell

LLM or large language models are deep learning models trained on vast amounts of linguistic data so they understand and respond in natural language (human-like texts). These encoders and decoders help the LLM model contextualize the input data and, based on that, generate appropriate responses.

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Techniques and approaches for monitoring large language models on AWS

AWS Machine Learning - AI

Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP), improving tasks such as language translation, text summarization, and sentiment analysis. Monitoring the performance and behavior of LLMs is a critical task for ensuring their safety and effectiveness.

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Achieve ~2x speed-up in LLM inference with Medusa-1 on Amazon SageMaker AI

AWS Machine Learning - AI

Large language models (LLMs) have revolutionized the field of natural language processing with their ability to understand and generate humanlike text. Researchers developed Medusa , a framework to speed up LLM inference by adding extra heads to predict multiple tokens simultaneously.

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Model customization, RAG, or both: A case study with Amazon Nova

AWS Machine Learning - AI

The introduction of Amazon Nova models represent a significant advancement in the field of AI, offering new opportunities for large language model (LLM) optimization. In this post, we demonstrate how to effectively perform model customization and RAG with Amazon Nova models as a baseline.

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Supercharge your auto scaling for generative AI inference – Introducing Container Caching in SageMaker Inference

AWS Machine Learning - AI

In this post, we explore the new Container Caching feature for SageMaker inference, addressing the challenges of deploying and scaling large language models (LLMs). You’ll learn about the key benefits of Container Caching, including faster scaling, improved resource utilization, and potential cost savings.

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How DPG Media uses Amazon Bedrock and Amazon Transcribe to enhance video metadata with AI-powered pipelines

AWS Machine Learning - AI

As DPG Media grows, they need a more scalable way of capturing metadata that enhances the consumer experience on online video services and aids in understanding key content characteristics. The following were some initial challenges in automation: Language diversity – The services host both Dutch and English shows.

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