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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

This is backed by our deep set of over 300 cloud security tools and the trust of our millions of customers, including the most security-sensitive organizations like government, healthcare, and financial services. With Security Lake, you can get a more complete understanding of your security data across your entire organization.

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Your guide to generative AI and ML at AWS re:Invent 2023

AWS Machine Learning

In this innovation talk, hear how the largest industries, from healthcare and financial services to automotive and media and entertainment, are using generative AI to drive outcomes for their customers. Additionally, SaaS providers need scalable and cost-effective ways to serve hundreds of models to their customers.

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Alida gains deeper understanding of customer feedback with Amazon Bedrock

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies, such as AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

Feedback 101
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Advanced RAG patterns on Amazon SageMaker

AWS Machine Learning

medium instance to demonstrate deploying LLMs via SageMaker JumpStart, which can be accessed through a SageMaker-generated API endpoint. You can request service quota increases through the console, AWS Command Line Interface (AWS CLI), or API to allow access to those additional resources. We use an ml.t3.medium

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Simplify iterative machine learning model development by adding features to existing feature groups in Amazon SageMaker Feature Store

AWS Machine Learning

In this post, we demonstrate how to add features to a feature group using the newly released UpdateFeatureGroup API. To update the feature group to add a new feature, we use the new Amazon SageMaker UpdateFeatureGroup API. We ingest the DataFrame into the feature group using the SageMaker SDK FeatureGroup.ingest API.

APIs 84
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Architect personalized generative AI SaaS applications on Amazon SageMaker

AWS Machine Learning

Hundreds of software as a service (SaaS) applications are being developed around these pre-trained models, which are either directly served to end-customers, or fine-tuned first on a per-customer basis to generate personal and unique content (such as avatars, stylized photo edits, video game assets, domain-specific text, and more).

SaaS 81