A mathematician's year-long work on a Millennium Prize Problem was fed into an AI coding assistant, then OpenAI solved the same problem via the same route weeks later—raising a hard question about whether anonymization actually protects novel ideas that are inherently identifiable by their uniqueness. The real issue isn't whether data was stolen, but that the rarest, most valuable ideas can't be hidden inside training data no matter how many names you strip out.

• De-identification (removing names, emails, etc.) only works when your data blends into a crowd; unique research approaches are inherently re-identifiable because the method itself is the fingerprint.
• The same mechanism that makes LLMs powerful—compression of billions of human interactions—makes privacy impossible for anyone working on sparse, high-value problems; there's no technical fix that preserves both capabilities.
• The solution isn't avoiding these tools but controlling where your work lives: keep sensitive data local and bring the model to it rather than uploading your thinking into systems you don't control.

Apple filed new evidence from a forensic analysis of a MacBook belonging to former engineer Chang Liu, alleging he downloaded confidential Apple schematics and used them at OpenAI, then destroyed evidence when confronted. The filing supports Apple's push for expedited discovery in its lawsuit against OpenAI for alleged trade secret theft.

• Liu downloaded a confidential Apple circuit schematic and used it in his work at OpenAI, running simulations with it in an electrical engineering tool called LTspice
• Liu sent instructions to destroy evidence to an OpenAI colleague after learning of Apple's internal investigation, and the colleague confirmed compliance
• Apple argues feeding trade secrets into AI models creates "irreversible and continually propagating uses" of those secrets, making the breach harder to contain
• OpenAI had the MacBook available but chose not to inspect it, instead advancing theories that the data would disprove Apple's claims