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Best practices for Amazon SageMaker HyperPod task governance

AWS Machine Learning

Administrators can use SageMaker HyperPod task governance to govern allocation of accelerated compute to teams and projects, and enforce policies that determine the priorities across different types of tasks. We also discuss common governance scenarios when administering and running generative AI development tasks.

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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

This streamlines the ML workflows, enables better visibility and governance, and accelerates the adoption of ML models across the organization. Before we dive into the details of the architecture for sharing models, let’s review what use case and model governance is and why it’s needed.

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

AWS Machine Learning

For now, we consider eight key dimensions of responsible AI: Fairness, explainability, privacy and security, safety, controllability, veracity and robustness, governance, and transparency. Regular evaluations allow you to adjust and steer the AI’s behavior based on feedback and performance metrics.

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What is PCI Compliance Call Recording & Transcription: Definition, Expert Tips & Best Practices

Callminer

Perhaps the strongest reason companies record and/or transcribe calls is that it’s often required by government entities. Expert PCI Compliance Tips & Best Practices. Below, we’ve rounded up 17 tips and best practices for PCI compliance from industry and regulatory experts. Expand your call recording practices.

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New Research: Customer Service Trends and Best Practices

GetFeedback

Given its significance, we conducted a global study to identify the latest customer service trends and best practices. The 5 customer service trends and best practices that caught our attention . Case Closed CSAT is the most valued metric among service teams. This article recaps our findings.

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

AWS Machine Learning

We also dive deeper into access patterns, governance, responsible AI, observability, and common solution designs like Retrieval Augmented Generation. Model monitoring – The model monitoring service allows tenants to evaluate model performance against predefined metrics.

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Generative AI operating models in enterprise organizations with Amazon Bedrock

AWS Machine Learning

Large organizations often have many business units with multiple lines of business (LOBs), with a central governing entity, and typically use AWS Organizations with an Amazon Web Services (AWS) multi-account strategy. Failure to scale the team can negate the governance benefits of a centralized approach.