Ancient Greek sophist Protagoras famously said, “There are two sides to every question.” But OpenAI’s latest attempt at reality distortion seems determined to narrow this dispute to just one. In its motion to reject Apple’s complaint, the company does not meaningfully acknowledge the criticisms levelled against it, preferring instead to recast the case as a grievance over talent retention and product-market failure.

The filing

In case you missed the news, OpenAI filed a motion to the court to dismiss Apple’s recent lawsuit against it. In that filing, OpenAI argued that, “Apple should not be permitted to use a baseless and pretextual lawsuit to make up for its shortcomings in the market for talent and retaining its employees, and its failures to integrate AI into its products.”

The company’s dismissal claims Apple’s case was, “plainly filed without adequate investigation and built on selectively excerpted communications and ordinary conduct stripped of context,” adding, in a turn of phrase borrowed from Apple’s own complaint, that it is “rotten to its core.”

The narratives can change

As ever with litigation, these are allegations and counter-allegations rather than findings of fact. The value of the filings is that they show how each side wants the court, and the public, to understand the same disputed events. At the moment, we don’t yet know how Apple will respond to OpenAI’s response; it follows that company’s failed attempt to woo public opinion earlier in the week when it deployed what some see as a “cookie jar” defense, arguing that Apple’s secrets only slipped out because the figurative jar lid was open.

OpenAI likely hopes for more success with its latest attempt to defend itself against Apple’s claims it engaged in a coordinated attempt to obtain trade secrets through questionable recruitment practices.

Central to the company’s counter-argument are its attempts to recharacterize some of Apple’s claims. For example, Apple alleges that one former staffer, Chang Liu, downloaded confidential files after leaving the company. OpenAI argues that Liu was instead attempting to help ex-colleagues who asked him for assistance. This is a useful example of the Protagorean frame: both companies are trying to extract different meanings from the same event.

What the truth might be

The courts will need to decide which version of events is closer to the truth. What is already clear is that OpenAI has been actively involved in recruiting Apple staff, including the services of former Chief Design Officer Jony Ive, as it develops a product that, to a layman like me, sounds likely to compete with Apple hardware. OpenAI says those recruitments reflect Apple’s failure to retain its staff; Apple argues its competitor is using exfiltrated confidential information to guide its hiring. The court will need to decide that story as well.

Ultimately, I don’t expect OpenAI’s efforts to have the court reject Apple’s lawsuit to succeed. Apple is asking for discovery precisely so it can test whether its reading of this distorted reality is supported by OpenAI’s internal procedures and the available facts. One of OpenAI’s arguments seems to be that Apple has not researched the matter thoroughly enough; Apple is quite literally requesting discovery to do just that.

What happens next?

I don’t know what discovery might turn up, but it does amuse me to think Apple could build its own large language model to boost the discovery process and identify communication conduits that might otherwise be obscured in the evidence initially available to it. How high, and in what direction, do OpenAI’s claimed recruitment practices go, and who is implicated in them? That’s something we might find out in the coming months.

OpenAI’s Protagorean defense extends a little further, of course, as the company also said it had “no use, need or desire for Apple’s trade secrets” because it is building “something entirely new.” This may surprise Apple, which has already alleged that OpenAI contacted its manufacturing partners and sought access to secret manufacturing processes Apple developed with them.

Once again, it will be up to the courts to decide whether those events took place, or if OpenAI’s defense has substance. Given that this dispute centers on product design and involves the AI company’s growing army of former Apple design and development staff, I find the denial hard to accept. But courts tend to make their own decisions, for good, or for ill. 

Fight or settle

What happens next? I think this attempt to reject the original litigation will fail, which means the case will enter the discovery process before one of two outcomes becomes more likely: A bitter public battle that lasts for years and might well end up in the Supreme Court, or an out-of-court settlement shaped by which side gains the most compelling evidence.

Like any war, there are really only two options: one side fights until the other can no longer continue, or both sides find a way to settle. The path to settlement may begin by recognizing that two stories can be applied to the same facts, and that the version closest to the truth often sits somewhere between them. I’m not a lawyer and I don’t have insider insight into the practicalities of the case, but based on what has been revealed so far, the most plausible combined story may be that Apple’s own vulnerabilities helped create an environment OpenAI chose to exploit. If so, Apple’s legal team will be searching hard for evidence of intent.

I expect they’ll find it.

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Until recently, it was common for companies and organizations to engage in “tokenmaxxing” — that is, maximizing their use of AI. But with AI costs going up, companies are now looking to save money, a trend underscored by a recent Microsoft decision to limit AI use by its employees.

“As we ramp up our use of GitHub Copilot to achieve our goals, we all need to be mindful of how we consume tokens,” Microsoft Executive Vice President Jay Parikh wrote in an email to the company’s employees.

Starting now, each department at Microsoft will be allocated a certain pool of tokens, with usage then adjusted up or down as needed.

The change prompted concern among some employees. “It’s very telling that a company that has invested so much in AI and subsidized so much AI inference is now advising its own employees to cut back on spending,” an anonymous Microsoft employee said in a comment to 404 Media.

The memory crisis is getting worse for Apple, which is struggling to get enough memory chips together for its upcoming iPhone 18 Pro series smartphones. That’s according to tech journalist Tim Culpan.

As he details it, Apple and its assembly partners are still attempting to secure sufficient quantities of memory, and though they’re confident they can meet initial demand once the devices are introduced, they apparently remain concerned that wait times could rapidly extend as retail inventory evaporates.

Apple’s manufacturing process compounds the problem. The A20 processor is packaged with memory using a new TSMC process, meaning processors are reportedly piling up while manufacturers wait for memory chips. You should read Culpan’s report to get the full picture.

What’s the frequency?

You don’t need to read between the lines to see the challenge. Despite demand for TSMC’s new processors, Apple seems to have been able to secure the supply it needs. But when it comes to churning out the final packaged chips memory, supply constraints have created significant obstacles to producing in quantity.

This is bad for Apple, particularly as the challenge doesn’t appear to be confined to iPhones; customers are experiencing delays getting new Macs. “Many new orders are now not arriving until September,” Bloomberg’s Mark Gurman wrote earlier this week. 

It isn’t just Apple that will be impacted by the AI-driven memory drought. The scale of Apple’s orders is among the greatest in the industry, and if its product plans are feeling the pain, every other manufacturer will be feeling it as well.

Conscious uncoupling

This is certainly in tune with expectations voiced at the beginning of the year when Ranjit Atwal, senior director analyst at Gartner, warned: “This is the steepest contraction in device shipments witnessed in over a decade. Higher prices will narrow the range of devices available, prompting buyers to hold on to devices for longer, fundamentally altering upgrade cycles.”

Gartner in February predicted a 10.4% decline in global PC shipments and an 8.4% drop in smartphone shipments as a result. The analyst also predicted a 130% surge in combined memory and SSD storage prices by the end of this year, with steep product price increases to follow. Recent data from IDC, Gartner, Counterpoint, and Omdia confirm PC market declines, but only at around 4% (the estimates vary).

Today’s report from Culpan suggests we’ve not yet experienced the full extent of this decline — hinting that while the initial fall reflected price, the next impact will be defined by lack of supply. While this hurts big brands like Apple, smaller entities could be left high and dry. 

When the chips are down

It is interesting to reprise Atwal’s warning in February that, “the sub-$500 entry-level PC segment will disappear by 2028,” as this seems to be what’s happening. That’s something long-time Mac users like me find particularly ironic, given it was only this year Apple briefly offered up its superbly priced $499 MacBook Neo. The industry direction we’re seeing now suggests we’ll never see that again, though the success of that device gave Apple a phenomenal 28.7% increase in sales in its just-revealed June quarter.

Despite memory supply challenges, Apple seems to be faring fairly well, with market share increasing across its business. Counterpoint data reveals that Apple has achieved an astonishing 65% share of the premium smartphone market. In part, that’s because as an existing premium brand, Apple was able to better absorb rising memory costs through higher margins and reduced promotions. Realistically, this means we can expect an overall increase in iPhone prices when the new range is announced up to $300 more, Jeff Pu, of GF Securities, recently claimed. 

Building the moat

Once again, what’s sustainable but difficult for larger brands such as Apple is existential disaster for smaller players — and it’s only now a matter of time before we see some real blood. That’s particularly true in smart home and device markets, where manufacturers lack the margins to sustain higher memory prices while delivering products customers can afford. A recent Global Electronics Association report tells us 62% of electronics manufacturers are already experiencing constrained availability or extended lead times. It also tells us 82% expect rising prices, including 33% who cite a “significant increase.”

This is already being felt by consumer and business users, as networking equipment is experiencing significant shipping delays. So, while we may find ourselves waiting a month or more for an iPhone, the wait for new routers, external storage devices, and home automation systems could be even longer once available inventories disappear. 

This doesn’t appear to be a short-term challenge; a recent Digitimes report warns that vendors have already sold their entire allocation of memory capacity for 2027.

Don’t even get me started on the likely impact on the military and defense markets as high-performance memory, storage, and processor supplies become constrained. Just like declining river levels in Europe, lack of memory threatens severe disruption. With so much turbulence impacting the tech economy, all we need now is for one or more of theinvestor-supported AI companies that have helped create the memory shortages to default on loan payments.

Got to keep the customer satisfied

Eager to protect sales, Apple recently introduced the Apple Upgrade leasing service in the US. This should enable consumers to purchase new devices at prices more sustainable to them over time. Apple isn’t alone in taking such action, which will inevitably extend beyond America.

“OEMs are expanding financing, trade-in and buyback programs to improve affordability,” said Counterpoint’s Harshit Rastogi. “Samsung has also expanded its Galaxy Forever program to several markets to make flagship devices more accessible.” 

Such schemes are all well and good, of course. Consumers will embrace them in hopes of a better tomorrow. But the tech industry is not immune to the wider constellation of existential challenges impacting economic environments.

In the end, if Apple, the industry’s biggest buyer of advanced components, is struggling to secure memory, the rest of the electronics sector is likely to face even greater challenges. For consumers, the initial impacts will be longer waits and higher prices. But the longer term consequences could be slower innovation and increased consolidation across the industry.

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In an open letter, OpenAI this week turned to the court of public opinion in its existential war against Apple with a public notice in which the company refutes the iPhone maker’s claims concerning wholesale use of confidential information.

You can detect the depth of enmity between both firms in OpenAI’s opening lines to its letter, which begins: “Apple is one of the greatest companies of all time,” and then moves swiftly into defending itself against company’s claims, while attempting to characterize Apple’s complaints as weak.

What Apple claimed

As reported elsewhere, Apple filed suit against OpenAI in the US District Court for the Northern District of California on July 10. The litigation names OpenAI Foundation, OpenAI Group PBC, io Products, Chang Liu (former senior systems electrical engineer), and Tang Yew Tan (former vice president of product design for iPhone and Apple Watch, now OpenAI’s chief hardware officer), and alleges breach of intellectual property agreement and misappropriation of trade secrets under the Defend Trade Secrets Act. The company has since then filed preservation orders to protect evidence. 

Apple’s complaint is more detailed than that. Among many other things, it claims Tan allegedly directed job candidates still at Apple to bring “actual parts” to interviews for “show and tell” sessions. It also alleges Tan distributed an internal Apple document describing Apple’s own departure security protocols to new hires before they resigned. Liu is separately accused of failing to return an Apple laptop and using it to download confidential technical documents.

OpenAI’s rebuttal

Now, OpenAI argues Apple’s trade-secret lawsuit is based on factual errors, poor communication and misleading claims. It says Apple mistakenly contacted the wrong OpenAI lawyer after confusing two people with the same surname, falsely claimed a phone call had occurred, then acknowledged both mistakes without raising the allegations later included in the lawsuit. (Apple says it sent OpenAI a warning letter back in February with no response, which undercuts OpenAI’s “we offered to resolve this before litigation” statement.)

OpenAI argues that Chang Liu was responding to requests from Apple colleagues seeking help locating Apple files, reflecting Apple’s own access-management failures rather than misconduct. It also claims Tan consistently instructed OpenAI staff not to seek or use competitors’ confidential information. OpenAI maintains it neither possesses nor wants Apple’s trade secrets, offered to resolve concerns before litigation, and finally argues that Apple’s request for a preliminary injunction is unnecessary and unsupported.

What Apple might actually argue

Will Apple see it the same way? That seems unlikely, in part due to the extent of the claimed infractions. Apple will point to the hundreds of former Apple employees now at OpenAI, including former Chief Designer Jony Ive. In doing so, it will likely argue that the remit of the case is not defined by erroneous legal correspondence, though that is probably seen as an error. Instead, the substantial claims it’s likely to focus on are that OpenAI has been engaged in a multi-front attempt to accumulate information pertaining to Apple and its design processes through recruitment and the way it recruits.

It’s feasible both arguments have some validity. OpenAI might be right in pointing out weaknesses in Apple’s own approach to internal communications in terms of secrecy. And Apple is correct in pointing out that OpenAI moved to abuse those vulnerabilities, weaknesses in its approach that have only been identified during OpenAI’s campaign to grab secrets.

While the Apple lawyer’s error in approaching OpenAI might be an unforced error that helps the AI firm cast doubt on Apple’s claims, it doesn’t necessarily invalidate them — and both sides believe themselves to be justified. Deciding which company is in the right will be a matter of law and not of public opinion.

Which side does the smoking gun face?

To prove its position, OpenAI shared some correspondence. These communications do seem to show a failure at Apple to properly implement device management over employee accounts, including the claim that personal iMessage accounts are routinely used to share corporate correspondence. That may be true, and shouldn’t be – it’s an obvious weakness in corporate security.

At the same time, the correspondence also shows hints of job opportunities at OpenAI for and to a former colleague, which kind of proves part of Apple’s point in terms of steady employee poaching. “I can always give you some fun side projects,” one message said. 

Of course, interaction between former colleagues is inevitable,. But at the level of seniority here, it feels plausible this could be in breach of any off-ramping arrangements reached between Apple and its former employees. No doubt, courts will decide that – though it does underline Apple’s claims that OpenAI instructed former Apple staffers about how to leave without reaching such agreements.

“This isn’t Apple getting it wrong. It is OpenAI getting caught with its hand in the hardware cookie jar and then writing a blog post about how the jar was left unlocked,” US tech thought leader Brian Roemmele wrote on X.

Where happens next?

Ultimately, what comes next is up to Apple and OpenAI. The two companies might reach a deal out of court, or be forced into an agreement by the legal system. The existential nature of the rivalry suggests the latter, rather than former.

It is also very telling that OpenAI, which now has more than 400 former Apple employees on its teams, including many former designers, also claims: “Apple’s request for a preliminary injunction is both based on false information and completely unnecessary because we do not have, nor want, any of their trade secrets. We’re much more interested in building innovative products and technologies that push the frontier.”

While Apple hasn’t yet responded, it will be interesting to see whether whatever hardware OpenAI ships looks and behaves like any released or unreleased Apple products; the latter will now be able to bring details of its own historical project design decisions — and the people who made them — to court.

I think this case will play out over time. Perhaps the most interesting question is whether OpenAI has taken what it knows about Apple to create its own internal product design and development LLM models. Would that use be legitimate? It would, after all, not be the first time an AI company has trained its models on other people’s creative energy.

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Apple has had to introduce a quota on security researcher reports because its systems are being overwhelmed by low-quality warnings generated by AI. 

It’s a classic illustration of the rule of unintended consequences: a technology meant to help us has become a barrier to getting things done. After all, not only has AI driven the cost of consumer electronics higher, but it is also being used to identify and exploit security vulnerabilities — while also overwhelming security teams with low-grade reports, thus eroding their attention span.

The cost of good intentions

This is what’s happened at Apple, as security researchers use AI as a tool to identify new bugs. Perhaps the reports are well-intended. Hopefully, the researchers aren’t just motivated by the promise of easy bug bounties. Or maybe this is a cynical attempt to overwhelm platform security teams with low-grade bug reports — while holding back larger attacks for actual use by well-resourced state-backed actors.

We can’t know whether attackers really are trying to overwhelm active platform defenses before going in for the kill. But given that it’s an actively used military strategy, it’s pretty hard to ignore the possibility.

Apple’s response

So, what’s happening at Apple? The company has put some limits in place to bug reporting as things got out of hand. It introduced a quota cap and a 30-day cool-off period for submitted reports, though researchers who exceed the cap can request an extension.

This follows Apple’s recent decision to increase its top security bounty payout to $5 million for the most severe exploits. Apple has paid out more than $35 million to around 800 researchers since launching its bug bounty program.

A Financial Times report tells us the many of the reports were about identical bugs, some already resolved, some trivial, but in combination comprising a fog of war that made it harder and more time-consuming to identify the really big flaws. The situation became so febrile the company made the decision to put limits in place in June.

There is a little wriggle room to the approach: Apple has worked with the security community long enough to recognize some research teams. Those it trusts most can have their quota extended. Apple also deployed its own AI systems to triage incoming reports in an attempt to identify and remove AI-generated slop.

The company also uses internal systems from Anthropic and OpenAI to help identify and fix vulnerabilities; that led to an extensive collection of fixes in its most recent software patch.

The Times details an Italian company called Bynario, which identified a fairly nasty-sounding privilege escalation chain that lets attackers take complete control of a Mac. The company also reported a second bug, CVE-2026-43760, a macOS Screen Sharing flaw that allowed an authenticated VNC viewer to access protected data and create files with root privileges.

Unfortunately, the hard-working research team was unable to report the first bug, as it had filed more than 50 reports in just three weeks thanks to AI. In other words, it’s possible some security researchers right now are unable to file warnings of critical vulnerabilities to Apple because the system is overwhelmed by slop.

This is not just an Apple problem

What makes this far more problematic is that it isn’t just Apple that is affected – security teams on multiple platforms are grappling with the same problem. Rafe Pilling, a security expert at Sophos, told the FT that bug bounty programs across the industry have had to shift from finding vulnerabilities to validating reports of them “at machine speed.”

That follows comments from Jamf security expert Adam Boynton, who last week characterized AI use in security as, “an arms race between defenders and attackers who are both, increasingly, running the same kind of tools.”

When it comes to platform security, it is possible that AI has added a new dimension of complexity to an already complex environment. Hopefully, the real threats will continue to be swiftly identified as they emerge, rather than being wrongly characterized as AI slop.

When no one comes running

To understand how this works, try reading Aesop’s fable about a shepherd boy who raised the alarm so often that when the real wolf arrived, no one came to help and the young shepherd? He was eaten.

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