Key Notes
- In an August 31 court filing, Apple says forensic analysis of a MacBook belonging to ex-engineer Chang Liu (who left for OpenAI in January) shows he downloaded a confidential Apple power-converter circuit schematic in March and used it in an LTspice simulation while at OpenAI - two months after leaving.
- Messages cited by Apple show Liu describing an AI agent that "learned how to run LTspice, look at result, tune compensation parameter," cutting a task from a full day to about two hours; Apple argues feeding trade secrets into a learning AI system creates "irreversible and continually propagating" exposure.
- Apple also alleges Liu, after learning of an internal investigation, sent a colleague instructions for destroying evidence, which she reportedly agreed to follow; Apple wants expedited access to a linked Mac mini and other devices.
- These are Apple's allegations in an active, contested lawsuit - OpenAI denies wrongdoing and has moved to dismiss the case.
Apple filed new evidence in its ongoing trade secrets lawsuit against OpenAI on August 31, calling the findings from a forensic examination of a former engineer’s laptop “shocking.” The filing centers on Chang Liu, a former senior system electrical engineer at Apple who left the company for OpenAI in January and is named, along with OpenAI hardware chief Tang Tan, as a defendant in Apple’s suit, first filed in July.
Apple alleges that forensic analysis of a MacBook Liu had kept after leaving, and which his legal team turned over roughly six weeks after the lawsuit was filed, shows he downloaded a confidential Apple circuit schematic in March, two months after his departure, and used it to run a power-converter simulation in LTspice, an electrical engineering tool.
Apple’s filing states that “the ongoing forensic inspection of this MacBook has uncovered forensic evidence showing that this computer contains Apple trade secret information, including at least one specific ‘.asc’ file, and that this file has been used while Mr. Liu has been employed by OpenAI.” Apple says it separately learned of the schematic’s use because it first appeared on a Mac mini that later synced to the MacBook via iCloud, and the company is now seeking access to that device as well.
The most novel element concerns AI. Messages cited in Apple’s filing show Liu describing an AI agent he set up to automate the LTspice simulations, writing that “in the past hour,” his agent “learned how to run LTspice, look at result, tune compensation parameter.” He said a task that previously took a full day now took about two hours, including the time the agent spent learning the tool from scratch, prompting a colleague to reply, “Oh man! Why do they even need you then?” Apple’s lawyers argue this compounds the alleged harm: “Where trade secret information is fed into an AI agent or model that ‘learns’ from it, such ‘learning’ may create irreversible and continually propagating uses of the trade secret.” Apple also alleges Liu used a tool at OpenAI sharing a name with an internal Apple engineering application.
Apple’s filing includes a further allegation of evidence destruction. The company says that after Liu learned of Apple’s internal investigation into him, he sent a colleague, identified as Yu-Ting Peng, instructions for destroying forensic data Apple would need for its case, and that she confirmed she would comply.
Apple also says the defendants had the opportunity to inspect the laptop themselves before turning it over and declined, instead advancing arguments the device’s own data reportedly contradicts. Apple is using these findings to press the court for expedited discovery, including faster access to devices and depositions of OpenAI personnel, arguing “the full scope of [Liu’s] misconduct thus remains unknown.”
What’s Essential
These are allegations made by one party in active, contested litigation, not judicial findings or an admission from OpenAI, which has denied wrongdoing and moved to dismiss the case, calling Apple’s broader allegations “meritless.” The court has not ruled on the merits of these specific claims.
If Apple’s characterization holds up, the case raises a genuinely novel legal question with implications well beyond this dispute: what happens to a company’s ability to seek a remedy when proprietary information isn’t just copied but has been absorbed into an AI system’s outputs or learned patterns.
Apple’s argument that AI-assisted misuse creates propagating, hard-to-reverse harm is a claim other companies handling trade secret disputes involving AI tools are likely to watch closely, since courts have limited precedent addressing where a “return the stolen property” remedy fits when the property in question has been processed by a learning system.
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