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Confidential computing is a technique for securing computer hardware and software from potential threats by protecting data in use, as covered in NVIDIA's Generative AI and LLMs course. It ensures that sensitive data, such as model weights or user inputs, remains encrypted during processing, using technologies like secure enclaves or trusted execution environments (e.g., NVIDIA H100 GPUs with confidential computing capabilities). This enhances the security of AI systems. Option B is incorrect, as it describes Trustworthy AI principles, not confidential computing. Option C is wrong, as aligning outputs with human beliefs is unrelated to security. Option D is inaccurate, as data integration is not the focus of confidential computing. The course notes: "Confidential computing secures AI systems by protecting data in use, leveraging trusted execution environments to safeguard sensitive information during processing." References: NVIDIA Building Transformer-Based Natural Language Processing Applications course; NVIDIA Introduction to Transformer-Based Natural Language Processing.
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