Apple sues OpenAI, claiming it poached staff to steal trade secrets

Apple has filed a lawsuit against OpenAI, alleging the AI company orchestrated a scheme to steal trade secrets related to its consumer hardware designs. The suit claims OpenAI recruited former Apple employees to access proprietary information, specifically naming former Apple engineers Chang Liu and Tang Tan. The legal complaint alleges that during job interviews, these workers were allegedly solicited for Apple’s intellectual property. In one particularly damning piece of evidence, a text message from Liu to a colleague reportedly read, “LOL, I found out I can access the [network storage], so funny.”

The timing is awkward for the industry. The move shatters the recent détente between the two firms, who had previously explored partnerships integrating OpenAI’s models into Apple’s ecosystem. It also highlights a raw nerve in Silicon Valley’s AI arms race: the fight isn’t just about training data or algorithms, but about the physical hardware that will make ambient AI a reality. OpenAI has been signaling a pivot toward developing its own consumer devices, and Apple’s suit suggests the company believes that roadmap was accelerated by theft rather than innovation.

Beyond the OpenAI case, the world of donor conception is confronting its own reckoning with limits and identity. Ties van der Meer, a 47-year-old conceived via an anonymous sperm donor, doesn’t know how many siblings he has. He tracked down one, but others remain ghosts. Some donor-conceived people have discovered dozens or even hundreds of half-siblings. One person who found 25 said, “It does make you feel a bit mass-produced.” A European fertility group is now pushing for international caps on how many children a single donor can father, a proposal that tries to balance reproductive freedom with the psychological weight of finding out you’re one of a hundred.

I’m skeptical that international limits can hold up against a patchwork of regulations and the borderless nature of the fertility industry, but the conversation is long overdue. Elsewhere, researchers are trying to teach AI to understand the physical world through “world models,” a shift from manipulating language to understanding gravity, space, and causality. Meanwhile, a Nobel-winning chemist is leaving the US to lead an AI lab in China, chasing funding as the White House slashes science budgets. It’s a brain drain story that rarely gets the attention it deserves.