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Image and video prompt engineering for Amazon Nova Canvas and Amazon Nova Reel

AWS Machine Learning

This post dives deep into prompt engineering for both Nova Canvas and Nova Reel. For detailed setup instructions, including account requirements, model access, and necessary permissions, refer to Creative content generation with Amazon Nova. For best results, place camera movement descriptions at the start or end of your prompt.

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Governing the ML lifecycle at scale, Part 3: Setting up data governance at scale

AWS Machine Learning

The diagram shows several accounts and personas as part of the overall infrastructure. Challenges in data management Traditionally, managing and governing data across multiple systems involved tedious manual processes, custom scripts, and disconnected tools. The following diagram gives a high-level illustration of the use case.

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25 Indicators of Fraud on Inbound Calls

Callminer

Further, malicious callers can manipulate customer service agents and automated systems to change account information, transfer money and more. Some fraudsters build a rapport with a particular agent or retail associate over time before requesting that they send a financial sum to their bank account.

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Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

AWS Machine Learning

They provide comprehensive insights into the intended use cases, limitations, responsible AI design principles, and best practices for deployment and performance optimization of our AI services. To learn more about CoT and other prompt engineering techniques for Amazon Bedrock LLMs, see General guidelines for Amazon Bedrock LLM users.

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Migrating call accounting to the cloud? Here’s what to consider

Eptica

Date: Friday, October 15, 2021 Author: Trevor Davies, Head of Products, Enghouse Interactive Migrating call accounting to the cloud? In this new blog post Trevor Davis outlines the key considerations when choosing a cloud-based call accounting solution and how to pick the perfect partner. Here’s what to consider.

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Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning

Security – The solution uses AWS services and adheres to AWS Cloud Security best practices so your data remains within your AWS account. Implementation and best practices The solution is designed to be modular and flexible so you can customize it according to your specific requirements.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning

Building cloud infrastructure based on proven best practices promotes security, reliability and cost efficiency. We demonstrate how to harness the power of LLMs to build an intelligent, scalable system that analyzes architecture documents and generates insightful recommendations based on AWS Well-Architected best practices.