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

AWS Machine Learning

Generative artificial intelligence (AI) applications built around large language models (LLMs) have demonstrated the potential to create and accelerate economic value for businesses. Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications.

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The top 2024 customer success trends predicted by industry experts

ChurnZero

New technologies, best practices, and strategies, combined with an industry-wide drive for sustainable, profitable growth, have made CS teams the revenue-building stars of every SaaS organization. It’s an exciting time to be in customer success. On the other hand, economic headwinds continue to constrain CS budgets and headcounts.

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The detailed guide to the LAER model in Customer Success.

CustomerSuccessBox

Technology has radically changed the world. However, what has changed more radically is the way the technology is purchased and adopted by a customer. There are no longer significant upfront commitments but rather are made up of lower-cost subscriptions and value-added services. First, let’s clearly define and understand the LAER model.

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Advanced RAG patterns on Amazon SageMaker

AWS Machine Learning

These generative AI applications are not only used to automate existing business processes, but also have the ability to transform the experience for customers using these applications. The following diagram illustrates the architecture of this solution.