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OpenAI Calls Apple Lawsuit Rotten to the Core

OpenAI Calls Apple Lawsuit Rotten to the Core

Big Tech

OpenAI filed a motion to dismiss Apple's trade secrets lawsuit, arguing the case is baseless and that Apple is using litigation to compensate for its own struggles retaining AI talent.

OpenAI asked a federal judge this week to throw out Apple’s trade secrets lawsuit against it, filing a 31-page motion that argues the case is meritless and accusing Apple of using litigation to paper over its own struggles retaining engineering talent and shipping competitive AI products. The filing, submitted in the Northern District of California, borrows a phrase directly from Apple’s own complaint to describe it: rotten to its core.

What Apple actually accused OpenAI of

Apple’s original lawsuit, filed last month, accused OpenAI and two named former Apple employees of running an organized effort to obtain confidential hardware blueprints and trade secrets, allegations tied to OpenAI’s expanding hardware division. That division grew substantially after OpenAI acquired io Products, the hardware startup co-founded by former longtime Apple design chief Jony Ive, a deal that gave OpenAI both hardware expertise and, in Apple’s telling, a direct incentive to recruit people who understood Apple’s confidential product development process. A central figure in Apple’s complaint is Chang Liu, a former Apple engineer now working at OpenAI, whom Apple accused of retaining confidential offboarding documentation rather than returning or destroying it as his prior employment agreement required. Apple separately filed a request for a preliminary injunction seeking to bar OpenAI and the named employees from accessing, using, or disclosing any of the disputed information while the underlying case proceeds.

How OpenAI is defending itself

OpenAI’s motion pushes back point by point. On the core theft allegation, the filing argues OpenAI has no use, need, or desire for Apple’s trade secrets because it is building something entirely different from anything Apple makes, an argument aimed less at any single piece of evidence than at undercutting Apple’s basic theory of motive. On the specific claim involving Chang Liu’s retained documents, OpenAI offers a competing explanation: it says Liu kept the offboarding paperwork specifically to help newly hired colleagues coming from Apple follow Apple’s own offboarding procedures correctly, so they would not accidentally retain confidential information, the opposite of Apple’s reading that the retention itself was evidence of an intent to evade confidentiality obligations. OpenAI also argues that its chief hardware officer, Tang Tan, acted within ordinary, industry-standard recruiting practices when interviewing prospective hires who happened to be Apple employees, rejecting Apple’s characterization of those conversations as a coordinated espionage effort.

The sharpest language in the filing is reserved for characterizing Apple’s motive for suing at all. OpenAI’s lawyers wrote that Apple built its reputation by paying close attention to the smallest details, and that this lawsuit does the opposite, calling it plainly filed without adequate investigation and built on selectively excerpted communications and ordinary conduct stripped of context. The filing goes on to argue that Apple should not be permitted to use what it calls a baseless and pretextual lawsuit to make up for its own shortcomings in the market for talent and in retaining employees, and for what OpenAI characterizes as Apple’s broader failure to integrate AI effectively into its own products, a pointed jab at Apple’s comparatively slower public AI roadmap relative to OpenAI, Google, and other competitors.

Why legal observers are skeptical it works

Motions to dismiss are a standard, expected first move in litigation like this, and few observers following the case expect this particular filing to end it outright. As one industry analysis put it, these are allegations and counter-allegations rather than findings of fact at this stage, and the real value of dueling filings like this one is mostly in how each side wants the court, and the public, to understand the same disputed set of events before any actual fact-finding happens. At least one commentator characterized OpenAI’s dismissal bid as its weakest play yet, arguing the filing appears to sidestep some of the more specific documentary evidence Apple has put forward rather than directly rebutting it. Whether that read holds up will depend heavily on what Apple’s opposition brief actually contains, which has not yet been filed publicly.

The timeline ahead

OpenAI faces a separate, court-ordered deadline of August 17 to formally respond to Apple’s preliminary injunction motion, a distinct filing from the motion to dismiss covered here. The presiding judge is scheduled to hear oral arguments on the dismissal motion on October 1, meaning the case will remain a live, developing story through the fall regardless of how this particular filing is ultimately resolved. The case is formally captioned Apple v. Liu, filed in the U.S. District Court for the Northern District of California, San Jose Division.

The dispute sits alongside a separate, unrelated legal fight in which a federal judge recently declined to dismiss an antitrust lawsuit brought by Elon Musk’s X Corp and xAI against both Apple and OpenAI, over Apple’s exclusive integration of ChatGPT into iOS. That case is proceeding toward further examination on its own track, but its existence underscores how thoroughly Apple and OpenAI’s relationship, one of partnership on iOS integration and open conflict over alleged trade secrets, has become entangled across multiple simultaneous legal fronts this year.

Why the talent framing matters beyond this one case

OpenAI’s decision to center its defense partly on Apple’s difficulty retaining engineering talent, rather than sticking purely to the narrower legal question of whether specific documents were misused, is a notable strategic choice. It reframes the dispute for anyone reading the public filings, not just the judge, as a broader story about which company engineers want to work for right now. That framing carries real risk for OpenAI too: courts generally do not treat a defendant’s characterization of a plaintiff’s competitive weaknesses as a legal defense on its own, so if the specific factual rebuttals around Liu’s documents and Tan’s recruiting conduct don’t hold up under scrutiny, the broader narrative framing won’t be enough to carry the motion regardless of how pointed the language is.

What a ruling either way would signal

The case sits at a genuinely unsettled intersection of trade secrets law and normal competitive hiring practice in a fast-moving industry where senior engineers routinely move between companies working on similar problems. If the court sides with OpenAI at the motion-to-dismiss stage, it would set a meaningful precedent for how much latitude AI companies have to recruit directly from competitors without facing trade-secrets liability simply because departing employees retained some work-related materials. If the case survives dismissal and proceeds toward the October 1 hearing and beyond, it becomes a genuine test of where the line sits between aggressive, industry-standard recruiting and actionable misappropriation, a question that has real stakes for every AI company currently competing for the same limited pool of specialized hardware and research talent.

See Computerworld’s analysis of the filing’s strengths and weaknesses.

This dispute follows our earlier coverage of Apple’s original lawsuit.

Up Next
ChatGPT Goes Unlimited for Free Users

ChatGPT Goes Unlimited for Free Users

ChatGPT

OpenAI removed ChatGPT's free-tier text chat limit and updated its default models, unifying instant and reasoning modes for paid users while giving free users unlimited access to GPT-5.6 Luna.

OpenAI removed the text chat limit on ChatGPT’s free tier this week, alongside a broader update that reworks which model powers the product for every paying and non-paying user. The changes land five weeks after OpenAI’s GPT-5.6 family reached general availability, and they arrive with a specific number attached to them: ChatGPT recently crossed one billion weekly users, a milestone OpenAI referenced directly when explaining the update.

What actually changed for each tier

Free and Go plan users are moving to GPT-5.6 Luna as their new default model, replacing GPT-5.5 Instant, and gaining unlimited text conversations without the rate limit that previously forced a wait once a session cap was reached. They are also getting a new Think button that triggers deeper reasoning for harder questions, subject to anti-abuse guardrails OpenAI did not detail publicly. Limits remain in place for everything outside plain text chat: file uploads, image generation, and voice all keep their existing caps.

Plus and Pro subscribers get a different change. Rather than switching between a separate Instant model and a separate reasoning model depending on the task, both are now handled by a single, updated GPT-5.6 Sol model, with a new slider letting users manually control how much computational effort ChatGPT puts into each response, from fast everyday answers up through more thorough analysis for coding, planning, and research. OpenAI says the goal was a model that delivers focused answers, adapts its level of detail to the question, and avoids unnecessary formatting regardless of how much reasoning effort it applies, eliminating what the company described internally as a jarring shift in tone that previously occurred when a conversation crossed from quick-answer mode into thinking mode. Notably, this update is scoped narrowly: the version of GPT-5.6 Sol used inside ChatGPT Work and Codex is explicitly unchanged, only the consumer chat experience is affected.

The accuracy numbers OpenAI is citing

OpenAI says internal testing across financial, medical, and legal prompts found factual errors dropped by roughly 62 percent with the new GPT-5.6 Luna and 68 percent with the updated GPT-5.6 Sol, compared against the prior GPT-5.5 Instant model. Those are OpenAI’s own internal figures rather than independently verified benchmark results, and the company has not published the specific test set or methodology behind them, so they’re worth treating as a company claim rather than a settled, externally reproduced number. Still, directionally they target exactly the failure mode that matters most for a model serving over a billion people weekly: confidently wrong answers on questions involving specific dates, numbers, sources, or rules, precisely the territory where AI hallucination tends to concentrate and where getting it wrong carries real consequences.

Why unlimited free access is a retention play, not a cost play

Removing the text-chat cap for free users is worth reading as a top-of-funnel and retention move rather than a cost-cutting one. It arrives after a year in which OpenAI has actually tightened usage limits in other parts of the product, and running an always-available free tier at over a billion weekly users is not a cheap decision from a compute-cost standpoint. The logic instead appears to be about keeping the free tier genuinely useful enough that people stay inside the ChatGPT ecosystem rather than bouncing to a competitor once they hit a wall mid-conversation, a friction point that has reportedly driven real churn toward rivals offering more generous free access.

The rollout itself is staggered. GPT-5.6 Luna became the default model for Free and Go users starting the week of the announcement, while the unlimited text-chat change and the new Think button followed roughly a week later. For Plus and Pro users, the updated GPT-5.6 Sol model and the new reasoning-effort slider began rolling out immediately across ChatGPT’s web, mobile, and desktop apps.

Part of a broader Sol, Terra, Luna naming shift

This update is a consumer-facing simplification pass rather than a new model generation. The underlying Sol, Terra, and Luna tier system was introduced in June, with Sol reaching general availability in July, and this week’s changes fold what had been a confusing choice, between separate Instant and Thinking modes, into a single model with adjustable effort instead. It also lands a month after OpenAI cut prices on the Luna and Terra tiers in late July, meaning the free and mid-tier models have now seen both a price cut and a capability upgrade within a matter of weeks, a combination that suggests OpenAI is prioritizing broad accessibility across its full user base rather than concentrating improvements only at the top of its subscription ladder.

How this compares to what rivals offer

The competitive backdrop matters here. Google’s Gemini already offers a genuinely capable free tier woven directly into Search, Gmail, and Docs, and Anthropic and xAI have both leaned on generous free access as part of their own growth strategies this year. A free tier that cuts a user off mid-conversation is a real point of friction in a market where switching to a competitor costs nothing but a new tab. Removing that friction for OpenAI’s largest, least monetized user segment is a defensive move as much as an offensive one: it protects the base ChatGPT has built rather than only trying to convert more of it to paid tiers.

The real cost this shifts, not eliminates

None of this makes free-tier inference free to run. OpenAI is absorbing real, ongoing compute cost to serve unlimited text conversations at a user base measured in the billions, a bet that only pays off if enough of those free users either convert to paid tiers over time or generate enough platform value, through engagement, data, and ecosystem lock-in, to justify the spend on their own. That calculation sits inside a much larger one: OpenAI’s overall infrastructure spending has scaled dramatically alongside its user growth this year, and a free tier this generous is only sustainable if the company’s broader unit economics continue trending the direction OpenAI’s public statements suggest they are.

What to actually watch next

The clearest signal of whether this update succeeds on its own terms will show up in two places over the coming weeks: whether OpenAI’s own accuracy claims hold up under independent testing once enough people have used the updated models at scale, and whether daily active usage among free-tier users actually increases now that the session-ending wall is gone. If the unlimited-access change meaningfully increases how often free users return, that’s a strong signal the friction really was costing OpenAI retention. If usage patterns stay roughly flat, it suggests the previous limits weren’t the binding constraint on engagement that this update assumes they were, and OpenAI absorbed a real, ongoing compute cost for a change that mostly benefits people who were already using the product heavily within the old limits anyway.

See Help Net Security’s original coverage for additional detail on the safety guardrails accompanying the rollout.