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Private Cloud Compute Security Guide(security.apple.com)
382 points by djoldman | 198 comments
Apple Security Research documentation guide describing the security and privacy architecture of Private Cloud Compute for cloud-based AI processing.
Memory Integrity Enforcement(security.apple.com)
456 points by circuit | 212 comments
Apple Security Engineering and Architecture blog post introducing Memory Integrity Enforcement, a memory safety protection system for Apple devices.
iMessage with PQ3 Cryptographic Protocol(security.apple.com)
515 points by galad87 | 247 comments
Apple Security Research blog post introducing PQ3, a post-quantum cryptographic protocol for iMessage end-to-end encryption.
Related stories
Private Cloud Compute Security Guide(security.apple.com)
382 points by djoldman | 198 comments
Apple Security Research documentation guide describing the security and privacy architecture of Private Cloud Compute for cloud-based AI processing.
Open Source Implementation of Apple's Private Compute Cloud(github.com)
409 points by adam_gyroscope | 91 comments
GitHub repository for OpenPCC, an Apache-2.0 open-source framework for provably private AI inference modeled on Apple's Private Cloud Compute.
Phi-4: Microsoft's Newest Small Language Model Specializing in Complex Reasoning(techcommunity.microsoft.com)
399 points by lappa | 136 comments
Microsoft AI Platform Blog post announcing Phi-4, a small language model specializing in complex reasoning.
AI will make formal verification go mainstream(martin.kleppmann.com)
782 points by evankhoury | 394 comments
Martin Kleppmann blog post predicting that AI will bring formal verification with proof assistants like Rocq, Isabelle and Lean into mainstream software engineering.
Moving away from US cloud services(martijnhols.nl)
442 points by MartijnHols | 245 comments
Blog post by Martijn Hols on why and how he is moving away from US cloud services, citing EU privacy law conflicts with US surveillance laws.
AI models can provably hide arbitrary capabilities(arxiv.org)
252 points by sbulaev | 118 comments
An arXiv paper showing AI models can embed encrypted neural network backdoors that provably hide arbitrary capabilities from elicitation-based safety evaluations.











