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Channel-Level Semantic Perturbations: Unlearnable Examples for Diverse Training Paradigms

arXiv cs.LG · 2d ago Cached

This paper systematically investigates unlearnable examples under diverse training paradigms, revealing that pretrained weights weaken existing methods, and proposes Shallow Semantic Camouflage (SSC) to maintain unlearnability by generating perturbations in a semantically valid subspace.

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Weights & Biases New Master Service Agreement Questions [D]

Reddit r/MachineLearning · 3d ago

Users are raising concerns about Weights & Biases' new Master Service Agreement, which grants the company broader rights to use customer data, including ML models, for product improvement and AI feature development.

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Surveillance Pricing: Exploiting Information Asymmetries

Hacker News Top · 2026-04-22 Cached

The article examines how corporations leverage personal data to implement surveillance pricing, reviving variable pricing in a more exploitative form than historical haggling.

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Introducing data residency in Asia

OpenAI Blog · 2025-05-07 Cached

OpenAI announces data residency options in Japan, India, Singapore, and South Korea for ChatGPT Enterprise, ChatGPT Edu, and API Platform, enabling organizations to meet local data sovereignty requirements. The feature builds on existing security measures including AES-256 encryption and no default model training on customer data.

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Introducing ChatGPT Enterprise

OpenAI Blog · 2023-08-28 Cached

OpenAI is launching ChatGPT Enterprise, offering enterprise-grade security and privacy, unlimited GPT-4 access, 32k context windows, advanced data analysis, and admin controls, with a guarantee that business data is not used for model training.

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New ways to manage your data in ChatGPT

OpenAI Blog · 2023-04-25 Cached

OpenAI introduces new data management features for ChatGPT, including the ability to disable chat history to prevent model training, a new ChatGPT Business subscription with stricter data policies, and an export tool for users to access their stored data.

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