How to accelerate AI and ML innovation with security and privacy

Learn how to use security and privacy to accelerate going to market with emerging AI/ML technologies such as generative AI. We will cover the fundamentals of security best practices, and explore the unique security and privacy challenges with generative AI/ML workloads. You will learn about fundamental security best practices and cybersecurity risk management frameworks such as NIST Cybersecurity Framework, NIST AI Risk Mitigation Framework (AI RMF), MITRE ATLAS, and how to combine native AWS security services with the native security and privacy features within Amazon Bedrock and Amazon SageMaker to secure and protect your intellectual property and data privacy.

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Deploying large generative AI models on SageMaker
Deploying large generative AI models on SageMaker

Discover the latest frameworks, sharding techniques, and deployment patterns that can help you scale your g...

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Securely build generative AI applications and control data with Amazon Bedrock
Securely build generative AI applications and control data with Amazon Bedrock

This presentation discusses the architectures, data flows, and security-related aspects of model fine-tunin...