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High Performance Privacy Preserving ai (Nowopen) (in English)
Jayavanth Shenoy; Patrick Grinaway; Shriphani Palakodety (Author)
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Now Publishers
· Hardcover
High Performance Privacy Preserving ai (Nowopen) (in English) - Jayavanth Shenoy; Patrick Grinaway; Shriphani Palakodety
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Synopsis "High Performance Privacy Preserving ai (Nowopen) (in English)"
Artificial intelligence (AI) depends on data. In sensitive domains - such as healthcare, security, finance, and many more - there is therefore tension between unleashing the power of AI and maintaining the confidentiality and security of the relevant data.This book - intended for researchers in academia and R&D engineers in industry - explains how advances in three areas-AI, privacy-preserving techniques, and acceleration-allow us to achieve the dream of high performance privacy-preserving AI. It also discusses applications enabled by this emerging interplay.The book covers techniques, specifically secure multi-party computation and homomorphic encryption, that provide complexity theoretic security guarantees even with a single data point. These techniques have traditionally been too slow for real-world usage, and the challenge is heightened with the large sizes of today's state-of-the-art neural networks, including large language models (LLMs). This book does not cover techniques like differential privacy that only concern statistical anonymization of data points.
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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.
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