Image generation features found in Apple Creator Studio rely on Google Cloud servers, but users will be warned before prompts are sent to the third-party AI tool.

Apple Intelligence is powered by Apple Foundation Models found on your iPhone and in Apple’s Private Cloud Compute servers. Those are distinct features and models from the integrations that utilize third-party AI tools like Google Cloud and ChatGPT.

After updating to the latest Apple Creator Studio version, users are encountering a new pop-up, whether they are running iOS 26 or iOS 27. That pop-up warns that the user’s prompt will be sent to a Google Cloud server, but won’t be used for training.

The warning is similar to what would appear when user queries were being sent to ChatGPT in previous versions of Apple Intelligence.

To be perfectly clear: This is not a part of Apple Intelligence or Apple Foundation Models.

Apple Foundation Models, not Google

There has already been some confusion around this new warning and Apple’s work with Google to implement Gemini technology in the new Apple Foundation Models. The Apple Foundation Models and resulting Apple Intelligence and Siri AI upgrades do not use any Google services, Google Search, Gemini Assistant, or Google frameworks.

The Apple Foundation Models on your device and in Apple’s Private Cloud Compute servers are Apple technology all the way down. Yes, the new models were built with Gemini Frontier models and servers at the foundation, but nothing Google remains in the shipping models.

Apple is working to bring its most powerful Apple Foundation Models to Google servers with Nvidia GPUs, but via Private Cloud Compute. Those Google servers Apple uses for Private Cloud Compute are fully Apple’s in operation, just like iCloud servers are when using AWS.

When you go to generate a shape or image in Pages, Freeform, or any other Apple Creator Studio app that has these features, it is using Google Cloud. Users have the ability to accept the warning each time, or set it to always accept.

The only data being sent in these instances is the text you’ve typed in the prompt or image sent to edit. And even then, just like with OpenAI’s partnership, Google is unable to train on sent prompts or retain data from the interaction.

Third-party AI usage limits in Apple Creator Studio

The feature is wholly isolated to Apple Creator Studio, so if a user would prefer to avoid using Google Cloud, it is easy to do so. Although, those that do choose to use it can know that their data remains private for the interaction.

Apple Creator Studio use of AI

Since Apple Creator Studio AI features rely on external AI tools, there are limitations to what can be done. Apple shares the percentage of AI usage in app settings, and that usage gets reset each month.

OpenAI provides ChatGPT for slide generation, and users can generate about 50 presentations with 8-10 slides each with their allotment. Google Cloud can generate 50 images or 250 shapes with its monthly allotment.

Apple doesn’t specify how many tokens a user has nor how many an event expends. It’s up to the user to keep queries short to minimize use, and to monitor usage manually.

The support document defining these features reiterates that zero data is used for training models.

Good morning! Let’s play Connections, the NYT’s clever word game that challenges you to group answers in various categories. It can be tough, so read on if you need Connections hints.

What should you do once you’ve finished? Why, play some more word games of course. I’ve also got daily Strands hints and answers and Quordle hints and answers articles if you need help for those too, while Marc’s Wordle today page covers the original viral word game.

Strands is the NYT’s latest word game after the likes of Wordle, Spelling Bee and Connections – and it’s great fun. It can be difficult, though, so read on for my Strands hints.

Want more word-based fun? Then check out my NYT Connections today and Quordle today pages for hints and answers for those games, and Marc’s Wordle today page for the original viral word game.

With the latest iOS 27 developer beta, Apple is giving testers an early look at one of the upcoming improvements to its AI-powered Siri: the ability to adjust how quickly and expressively the AI assistant speaks. In iOS 27 beta 3, out today, Apple has enabled the voice controls for “Pace” and “Expressivity” that were previously labeled as “Coming soon” in the first developer beta releases.

The update is part of Apple’s broader effort to make Siri feel more natural and personal, as it rebuilds the assistant around generative AI. Like ChatGPT and others offering voice AI assistants, letting users customize how the AI sounds is an important aspect in helping connect people with the new technology.

However, ChatGPT’s voice-customization options allow users to go even further, as the ability to adjust the AI’s warmth and enthusiasm was rolled out in December 2025, alongside options to configure the base style and tone. The latter lets users adjust OpenAI’s assistant to be more friendly, professional, candid, or quirky, among other styles. This is reflected not only in how ChatGPT speaks, but also in how it presents information to the user.

Utah has quietly become the first US state to let an AI chatbot renew prescriptions without a doctor, according to the Associated Press. The programme, run by a company called Doctronic, launched in January and has set off a fierce medical debate.

Residents can skip the doctor’s office and refill prescriptions online through the chatbot. It asks about their medication and history, checks a national pharmacy database, and either renews the script or escalates to a human doctor.

The launch was possible only through a “regulatory sandbox” that lets Utah officials waive laws for promising AI. State and federal rules otherwise restrict prescribing to licensed medical professionals.

“We have crossed a threshold in terms of giving something that is not human a medical license, whether or not we want to call it that,” the University of Pennsylvania’s Dr Eric Bressman told the AP. He and others say they are not opposed to AI prescribing, but want it held to standards as rigorous as those for human doctors.

The board that got left out

Utah’s medical licensing board says it only learned of the programme when the January launch made the news. In an April letter, 11 members called for the pilot to be halted, citing the risks of auto-renewing drugs with side effects or interactions.

“We were essentially told: ‘Yes this is going on. And no, you don’t have a say in it’,” said Dr Alan Smith, a family physician who chairs the board but spoke for himself.

The state declined to suspend it, noting human doctors still review every refill in this first phase.

The programme is currently overseen by a five-member board of AI specialists, none of them doctors. Doctronic expects to move to fully automated refills soon.

Smith warns the risks are real, pointing out that Doctronic’s roughly 190 refillable medications include blood thinners, which turn dangerous if a patient develops internal bleeding. The American Medical Association has echoed the concern that “prescription renewals aren’t routine checkboxes”.

A regulatory vacuum by design

The case exposes a jurisdictional tangle, since medical technology is regulated federally while medical professionals are overseen by states. Doctronic frames its AI as part of state-regulated medical practice, though some experts argue it has crossed into FDA territory.

The company would not say whether it has sought FDA permission. The agency told the AP it has authorised no AI chatbots but wants to encourage innovation, a hands-off posture that fits a broader loosening of oversight on AI health tools.

Critics see history rhyming, with Bressman comparing the moment to the haphazard medicine of the early 20th century, before boards and benchmarks existed. The template for licensing AI medical services in other states comes from the Cicero Institute, a pro-AI think tank founded by Palantir co-founder Joe Lonsdale.

The stakes are not abstract, as safety researchers have warned that medical chatbots can sound authoritative while dispensing dangerous advice. Others caution that removing humans from care can undermine the very outcomes it promises.

Rivals are scrambling to map those failure modes too. Meta went as far as posing as teenagers to test how competing chatbots handle sensitive topics.

Doctronic plans peer-reviewed studies later this year, though its only published paper so far was written by its own scientists and not independently reviewed. As one Utah law professor put it, companies risk letting the technology race beyond the evidence, and betraying public trust in the process.

A federal judge has refused to overturn a jury’s finding that Elon Musk defrauded Twitter investors during his $44bn takeover of the platform in 2022. US District Judge Charles Breyer denied Musk’s motion to set aside the verdict in most respects on Monday.

A San Francisco jury ruled in March that two of Musk’s May 2022 tweets about the deal and Twitter’s spam bot numbers were materially false or misleading. Investors say the resulting losses could support damages of up to $2.6bn.

“Buyer’s remorse is not an exception to the securities laws,” Breyer wrote, adding that the laws are “in their essence, about trust”. The judge found substantial evidence that Musk’s 13 May tweet, claiming the deal was on hold pending bot data, was literally untrue.

Breyer cited testimony from one of Musk’s own bankers, who said the tweet surprised her and that Musk never actually put the deal on hold. A jury could infer Musk had a motive to escape the deal and used bots as a pretext, the judge wrote.

He did hand Musk one narrow win, agreeing there was too little evidence that a separate 17 May tweet caused investors a market loss. Musk’s lawyers did not immediately respond to requests for comment.

The bot pretext, four years on

The case traces back to Musk’s chaotic pursuit of Twitter, when he agreed to buy the company, then tried to walk away citing spam accounts. Twitter sued to force the deal through, and Musk ultimately closed at $54.20 a share before renaming the platform X.

Investors sued in October 2022, arguing Musk deliberately talked the stock down to renegotiate or exit. The jury agreed he misled the market, though it rejected the broader claim that he ran a deliberate scheme.

Breyer also swatted down Musk’s more colourful arguments, including a claim that jurors mocked him by writing “$4.20” in blue ink on the verdict form. The number references cannabis, the judge noted, and the jury had actually cleared Musk on two claims.

Another legal front for a busy defendant

The ruling adds to a crowded docket for Musk, who recently settled a separate SEC case over his late disclosure of an initial Twitter stake for $1.5m. His “funding secured” Tesla saga first drew SEC fraud charges back in 2018.

He is also fighting Sam Altman in a high-stakes trial over OpenAI, all while steering the newly public SpaceX. The tweets that built his mythology keep generating legal bills.

Prejudgment interest, which Breyer also granted, could push the final figure higher still. For a man now worth more than a trillion dollars, the sum is survivable, but the finding that he defrauded investors is harder to shrug off.

from the here-to-build-an-encyclopedia dept

In Larry Sanger’s recent failed attempt to start a “WikiProject Intellectual Diversity”, he tried to recruit his followers to help him change Wikipedia’s rules around representation of viewpoints, religions, parties, and nationalities (a version of his earlier “Nine Theses”). The draft WikiProject was not itself a bannable offense, but his approach broke rules that were designed to foster fair discussions. Wikipedia’s rules really already support creation of balanced and robust articles about controversial topics – it just takes a huge amount of careful research, patience, and cooperation, and there’s no shortcut for that work.

In the first several months of Wikipedia, Sanger’s seriousness about its potential encouraged me to take up the challenge of helping write an encyclopedia that represents the sum of human knowledge. 25 years later, I remain an active editor dedicated to the Wikimedia movement for free and open knowledge, which is basically a fun and oddly serious hobby.

I edit a lot of moderately controversial articles that have glaring gaps in core principles of verifiability and neutral point of view. Many of Wikipedia’s most popular articles, like about politics and philosophy, are very informative and comprehensive, but second-tier articles don’t consistently get robust attention from editors. For example, I’ve recently repaired bias and disinformation in articles about AI regulation, LGBTQ rights in Nigeria, politicians in the Balkans, wealthy businessmen outside the US, influential religious organizations, and people accused of sexual harassment. I routinely fix articles that downplay negative information or present a controversial topic in a flattering way, in the style of Jeffrey Epstein’s ineffective project to get consultants to sanitize his article.

The good thing is that Wikipedia’s established rules already provide robust strategies to improve verifiability and balance in articles. Its principles expect editors to be cooperative and willing to cite a reliable source for nearly every sentence. You have to be up for changing your mind when somebody finds multiple reliable sources that disprove something you assumed, or at least up for slinking away to another article. To help counter bias and conflicts of interest, I apply elaborately layered guidance for evaluating and weighing sources – often citing academic journal articles and books, but not always, because the guidance recognizes that reliability is contextual. The “due weight” policy, part of the neutral point of view policy, pushes editors to search for more and better sources when something gets disputed, which results in a stronger article. I’ve learned that the best way to resolve a content dispute is to cite the best sources, reference the most relevant rules, present evidence calmly, and escalate one step at a time through the dispute resolution forums. Dispute resolution typically uses Wikipedia’s informal decision-making process, which reflects that Wikipedia is a decentralized asynchronous volunteer project, not an adjudicatory body. Wikipedia’s processes already work pretty well, they just take a lot of skill and patience, because collaboration is hard work.

Sanger was banned for off-Wikipedia canvassing and for not being on Wikipedia to build an encyclopedia, but to be clear, trying to start WikiProject Intellectual Diversity was not in itself a bannable offense. Canvassing is against the rules specifically to protect public and open processes that support the development of balanced articles. The canvassing guidelines discourage editors from trying to rig decision-making processes by selectively inviting participants who will take their side. The rules favor public discussions on Wikipedia so that all editors have an equal opportunity to participate. And since all Wikipedia edits are publicly tracked, editors can analyze each other’s contributions to detect biases and conflicts of interest. External invitations both selectively invite participation and prevent editors from exercising oversight. Volunteer administrators routinely block or even ban editors for inappropriate canvassing because this behavior compromises efforts to build a balanced encyclopedia.

Sanger’s recent advocacy reminds me of the pattern that researcher and Wikipedia editor Molly White described in January 2025: “right-wing voices attacking Wikipedia as part of an intensifying campaign against free and open access information.” In October, the Washington Post described Sanger as “fueling the right’s campaign” against Wikipedia. Among other incidents last year, House Republicans demanded disclosure of editor information over coverage of the Israel-Palestine conflict. Sanger’s call to prohibit anonymity for the most dedicated volunteer administrators, one of his Nine Theses, is another one of his takes that would undermine intellectual freedom in the project, in line with the leaked Heritage Foundation plan to dox editors.

My work to counter gaps, bias, and spam in Wikipedia articles gives me proof every day that the project is imperfect. Every active editor has critiques of Wikipedia, the Wikimedia Foundation, and the Wikimedia movement, and we debate issues and improvements at length. Wikipedia would benefit from additional contributors from any viewpoint or background who want to help build an encyclopedia. But improving Wikipedia requires intellectual honesty, cooperation, and willingness to apply established principles and rules even while critiquing them, not bad-faith publicity stunts.

Filed Under: canvassing, diversity, encyclopedia, larry sanger, wikipedia

Companies: wikimedia foundation, wikipedia