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Fine-tune Meta Llama 3.1 models for generative AI inference using Amazon SageMaker JumpStart

Improve call center efficiency by leveraging batch inference for transcript summarization using Amazon Bedrock

A technical blogpost about the concept of 'Accident Forgiveness' in cloud billing, highlighting the implications and benefits for customers.

Enhance performance and accuracy by implementing custom chunking mechanism with Amazon Bedrock for efficient data extraction from PDF documents

Empower collaboration and reusability with Amazon SageMaker Canvas and Amazon DataZone for efficient data governance and ML model creation

Automate healthcare documentation using Amazon Bedrock and Amazon Transcribe with Live Meeting Assistant

Evaluate accuracy of Amazon Q Business using a comprehensive framework for generative AI solutions.

Automate customer review analysis using Amazon Bedrock for actionable insights and improved customer experience

Introducing Llama 3.1 with advanced capabilities and in-depth insights on its development process presented by Meta engineers at AI Infra @ Scale 2024

Run AI inference apps on Google Cloud Run with NVIDIA GPU support for enhanced performance and scalability

Cloud Run functions unifies event-driven programming in a serverless platform with fine-grained control and scalability.

Introducing delayed destruction for Secret Manager, a new way to protect your secrets