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Fear Not! A Security Model for GenAI

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Manage episode 437880847 series 3559949
内容由Eric Kavanagh提供。所有播客内容(包括剧集、图形和播客描述)均由 Eric Kavanagh 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

The Generative AI revolution is transforming how organizations operate, unlocking new use cases across industries and employee workflows. However, challenges such as security, legal compliance, and demonstrating return on investment (ROI) hinder widespread adoption. One approach for solving some of these issues uses a security orchestration layer, enabling organizations to confidently connect any data source with any generative AI model. This approach lets businesses leverage the power of GenAI while maintaining control and confidentiality.

Check out this episode of DMRadio to learn more as Host @eric_kavanagh interviews Oz Wasserman of Opsin. They'll discuss how retrieval-augmented generation (RAG) can be used to optimize the outputs of Large Language Models (LLMs). Combining contextual information with ongoing improvements in foundational models, RAG delivers superior results, ensuring organizations achieve tangible ROI with GenAI investments. Security features like role-based access control (RBAC), auditing, and anonymization can be used to safeguard data privacy and enhance security.

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Artwork
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Manage episode 437880847 series 3559949
内容由Eric Kavanagh提供。所有播客内容(包括剧集、图形和播客描述)均由 Eric Kavanagh 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

The Generative AI revolution is transforming how organizations operate, unlocking new use cases across industries and employee workflows. However, challenges such as security, legal compliance, and demonstrating return on investment (ROI) hinder widespread adoption. One approach for solving some of these issues uses a security orchestration layer, enabling organizations to confidently connect any data source with any generative AI model. This approach lets businesses leverage the power of GenAI while maintaining control and confidentiality.

Check out this episode of DMRadio to learn more as Host @eric_kavanagh interviews Oz Wasserman of Opsin. They'll discuss how retrieval-augmented generation (RAG) can be used to optimize the outputs of Large Language Models (LLMs). Combining contextual information with ongoing improvements in foundational models, RAG delivers superior results, ensuring organizations achieve tangible ROI with GenAI investments. Security features like role-based access control (RBAC), auditing, and anonymization can be used to safeguard data privacy and enhance security.

  continue reading

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