daring-rss

To put it in Steven Sinofsky’s terms, gatekeeping is a fundamental aspect of Apple’s brand promise with iOS.

Last week I mentioned Apple’s prohibition on JITs — just-in-time compilers — in the context of their rejection of UTM SE, an open source PC emulator. Apple’s prohibition on JITs, on security grounds, is a side issue regarding UTM SE, because UTM SE is the version of UTM that doesn’t use a JIT. But because it doesn’t a JIT, it’s so slow that the UTM team doesn’t consider it worth fighting with Apple regarding its rejection.

On that no-JITs prohibition, though, it’s worth noting that Apple even disables its own trusted JIT in WebKit when you enable Lockdown Mode, which Apple now describes as “an optional, extreme protection that’s designed for the very few individuals who, because of who they are or what they do, might be personally targeted by some of the most sophisticated digital threats. Most people are never targeted by attacks of this nature.” Apple previously described Lockdown Mode as protection for those targeted by “private companies developing state-sponsored mercenary spyware”, but has recently dropped the “state-sponsored” language.

Here’s how Apple describes Lockdown Mode’s effect on web browsing:

Web browsing – Certain complex web technologies are blocked, which
might cause some websites to load more slowly or not operate
correctly. In addition, web fonts might not be displayed, and
images might be replaced with a missing image icon.

JavaScriptCore’s JIT interpreter is one of those “complex web technologies”. Alexis Lours did some benchmarking two years ago, when iOS 16 was in beta, to gauge the effect of disabling the JIT on JavaScript performance (and he also determined a long list of other WebKit features that get disabled in Lockdown Mode, a list I wish Apple would publish and keep up to date). Lours ran several benchmarks but I suspect Speedometer is most relevant to real-world usage:

Speedometer aims to benchmark real world applications by emulating
page action on multiple frameworks. This should allow us to get a
decent idea of the performance drop in JavaScript heavy
frameworks.

A 65% drop in performance, while this is still a heavy hit on
performance, compared to a 95% drop, this shifts the value from a
no-go to a compromise worth considering for people seeking the
extra privacy.

This brings me to BrowserEngineKit, a new framework Apple created specifically for compliance with the EU’s DMA, which requires gatekeeping platforms to allow for third-party browser engines. Apple has permitted third-party browsers on iOS for over a decade, but requires all browsers to use the system’s WebKit rendering engine. One take on Apple’s longstanding prohibition against third-party rendering engines is that they’re protecting their own interests with Safari. More or less that they’re just being dicks about it. But there really is a security angle to it. JavaScript engines run much faster with JIT compilation, but JITs inherently pose security challenges. There’s a whole section in the BrowserEngineKit docs specifically about JIT compilation.

As I see it Apple had three choices, broadly speaking, for complying with the third-party browser engine mandate in the DMA:

Disallow third-party browser engines from using JITs. This would clearly be deemed malicious by anyone who actually wants to see Chromium or Gecko-based browsers on iOS. JavaScript execution would be somewhere between 65 to 90 percent slower compared to WebKit.

Allow third-party browser engines in the EU to just use JIT compilation freely without restrictions. This would open iOS devices running such browsers to security vulnerabilities. The message to users would be, effectively, “If you use one of these browsers you’re on your own.”

Create something like BrowserEngineKit, which adds complexity in the name of allowing for JIT compilation (and other potentially insecure technologies) in a safer way, and limit the use of BrowserEngineKit only to trusted web browser developers.

Apple went with choice 3, and I doubt they gave serious consideration to anything else. Disallowing third-party rendering engines from using JITs wasn’t going to fly, and allowing them to run willy-nilly would be insecure. The use of BrowserEngineKit also requires a special entitlement:

Apple will provide authorized developers access to technologies
within the system that enable critical functionality and help
developers offer high-performance modern browser engines. These
technologies include just-in-time compilation, multiprocess
support, and more.

However, as browser engines are constantly exposed to untrusted
and potentially malicious content and have visibility of sensitive
user data, they are one of the most common attack vectors for bad
actors. To help keep users safe online, Apple will only authorize
developers to implement alternative browser engines after meeting
specific criteria and who commit to a number of ongoing privacy
and security requirements, including timely security updates to
address emerging threats and vulnerabilities.

BrowserEngineKit isn’t easy, but I genuinely don’t think any good solution would be. Browsers don’t need a special entitlement or complex framework to run on MacOS, true, but iOS is not MacOS. To put it in Steven Sinofsky’s terms, gatekeeping is a fundamental aspect of Apple’s brand promise with iOS.

Read More 

Apple is focusing on what it can do that no one else can on Apple devices, and not really even trying to compete against ChatGPT *et al* for world-knowledge context. They’re focusing on unique differentiation, and eschewing commoditization.

An oft-told story is that back in 2009 — two years after Dropbox debuted, two years before Apple unveiled iCloud — Steve Jobs invited Dropbox cofounders Drew Houston and Arash Ferdowsi to Cupertino to pitch them on selling the company to Apple. Dropbox, Jobs told them, was “a feature, not a product”.

It’s easy today to forget just how revolutionary a product Dropbox was. A simple installation on your Mac and boom, you had a folder that synced between every Mac you used — automatically, reliably, and quickly. At the time Dropbox had a big sign in its headquarters that read, simply, “It Just Works”, and they delivered on that ideal — at a time when no other sync service did. Jobs, of course, was trying to convince Houston and Ferdowsi to sell, but that doesn’t mean he was wrong that, ultimately, it was a feature, not a product. A tremendously useful feature, but a feature nonetheless.

Leading up to WWDC last week, I’d been thinking that this same description applies, in spades, to LLM generative AI. Fantastically useful, downright amazing at times, but features. Not products. Or at least not broadly universal products. Chatbots are products, of course. People pay for access to the best of them, or for extended use of them. But people pay for Dropbox too.

Chatbots can be useful. There are people doing amazing work through them. But they’re akin to the terminal and command-line tools. Most people just don’t think like that.

What Apple unveiled last week with Apple Intelligence wasn’t so much new products, but new features — a slew of them — for existing products, powered by generative AI.

Safari? Better now, with generative AI page summaries. Messages? More fun, with Genmoji. Notes and Mail and Pages (and any other app that uses the system text frameworks)? Better now, with proofreading and rewriting tools built-in. Photos? Even better recommendations for memories, and automatic categorization of photos into smart collections. Siri? That frustrating, dumb-as-a-rock son of a bitch, Siri? Maybe, actually, pretty useful and kind of smart now. These aren’t new apps or new products. They’re the most used, most important apps Apple makes, the core apps that define the Apple platforms ecosystem, and Apple is using generative AI to make them better and more useful — without, in any way, rendering them unfamiliar.1

We had a lot of questions about Apple’s generative AI strategy heading into WWDC. Now that we have the answers, it all looks very obvious, and mostly straightforward. First, their models are almost entirely based on personal context, by way of an on-device semantic index. In broad strokes, this on-device semantic index can be thought of as a next-generation Spotlight. Apple is focusing on what it can do that no one else can on Apple devices, and not really even trying to compete against ChatGPT et al for world-knowledge context. They’re focusing on unique differentiation, and eschewing commoditization.

Second, they’re doing both on-device processing, for smaller/simpler tasks, and cloud processing (under the name Private Cloud Compute) for more complex tasks. All of this is entirely Apple’s own work: the models, the servers (based on Apple silicon), the entire software stack running on the servers, and the data centers where the servers reside. This is an enormous amount of work, and seemingly puts the lie to reports that Apple executives only even became interested in generative AI 18 months ago. And if they did accomplish all this in just 18 months that’s a remarkable achievement.

Anyone can make a chatbot. (And, seemingly, everyone is — searching for “chatbot” in the App Store is about as useful as searching for “game”.) Apple, conspicuously, has not made one. Benedict Evans keenly observes:

To begin, then: Apple has built an LLM with no chatbot. Apple has
built its own foundation models, which (on the benchmarks
it published) are comparable to anything else on the market, but
there’s nowhere that you can plug a raw prompt directly into the
model and get a raw output back – there are always sets of buttons
and options shaping what you ask, and that’s presented to the user
in different ways for different features. In most of these
features, there’s no visible bot at all. You don’t ask a question
and get a response: instead, your emails are prioritised, or you
press ‘summarise’ and a summary appears. You can type a request
into Siri (and Siri itself is only one of the many features using
Apple’s models), but even then you don’t get raw model output
back: you get GUI. The LLM is abstracted away as an API call.

Instead Apple is doing what no one else can do: integrating generative AI into the frameworks in iOS and MacOS used by developers to create native apps. Apps built on the system APIs and frameworks will gain generative AI features for free, both in the sense that the features come automatically when the app is running on a device that meets the minimum specs to qualify for Apple Intelligences, and in the sense that Apple’s isn’t charging developers or users to utilize these features.

Apple’s keynote presentation was exceedingly well-structured and paced. But nevertheless it was widely misunderstood, I suspect because expectations were so wrong. Those who believed going in that Apple was far behind the state of the art in generative AI technology wrongly saw the keynote’s coda — the announcement of a partnership with OpenAI to integrate their latest model, ChatGPT-4o, as an optional “world knowledge” layer sitting atop Apple’s own homegrown Apple Intelligence — as an indication that most or even all of the cool features Apple revealed were in fact powered by OpenAI. Quite the opposite. Almost nothing Apple showed in the keynote was from ChatGPT.

What I see as the main takeaways:

Apple continues to build machine learning and generative AI features across its core platforms, iOS and MacOS. They’ve been adding such features for years, and announced many new ones this year. Nothing Apple announced in the entire first hour of the keynote was part of “Apple Intelligence”. Math Notes (freeform handwritten or typed mathematics, in Apple Notes and the Calculator app, which is finally coming to iPadOS) is coming to all devices running iOS 18 and MacOS 15 Sequoia. Smart Script — the new personalized handwriting feature when using Apple Pencil, which aims to improve the legibility of your handwriting as you write, and simulates your handwriting when pasting text or generating answers in Math Notes — is coming to all iPads with an A14 or better chip. Inbox categorization and smart message summaries are coming to Apple Mail on all devices. Safari web page summaries are coming to all devices. Better background clipping (“greenscreening”) for videoconferencing. None of these features are under the “Apple Intelligence” umbrella. They’re for everyone with devices eligible for this year’s OS releases.

The minimum device specs for Apple Intelligence are understandable, but regrettable, particularly the fact that the only current iPhones that are eligible are the iPhone 15 Pro and Pro Max. Even the only-nine-month-old iPhone 15 models don’t make the cut. When I asked John Giannandrea (along with Craig Federighi and Greg Joswiak) about this on stage at The Talk Show Live last week, his answer was simple: lesser devices aren’t fast enough to provide a good experience. That’s the Apple way: better not to offer the feature at all than offer it with a bad (slow) experience. A-series chips before last year’s A17 Pro don’t have enough RAM and don’t have powerful enough Neural Engines. But by the time Apple Intelligence features actually become available — even in beta form (they are not enabled in the current developer OS betas) — the iPhone 15 Pro will surely be joined by all iPhone 16 models, both Pro and non-pro. Apple Intelligence is skating to where the puck is going to be in a few years, not where it is now.

Surely Apple is also being persnickety with the device requirements to lessen the load on its cloud compute servers. And if this pushes more people to upgrade to a new iPhone this year, I doubt Tim Cook is going to see that as a problem.

One question I’ve been asked repeatedly is why devices that don’t qualify for Apple Intelligence can’t just do everything via Private Cloud Compute. Everyone understands that if a device isn’t fast or powerful enough for on-device processing, that’s that. But why can’t older iPhones (or in the case of the non-pro iPhones 15, new iPhones with two-year-old chips) simply use Private Cloud Compute for everything? From what I gather, that just isn’t how Apple Intelligence is designed to work. The models that run on-device are entirely different models than the ones that run in the cloud, and one of those on-device models is the heuristic that determines which tasks can execute with on-device processing and which require Private Cloud Compute or ChatGPT. But, see also the previous item in this list — surely Apple has scaling concerns as well. As things stand, with only devices using M-series chips or the A17 or later eligible, Apple is going to be on the hook for an enormous amount of server-side computation with Private Cloud Compute. They’d be on the hook for multiples of that scale if they enabled Apple Intelligence for older iPhones, with those older iPhones doing none of the processing on-device. The on-device processing component of Apple Intelligence isn’t just nice-to-have, it’s a keystone to the entire thing.

Apple could have skipped, or simply delayed announcing until the fall, the entire OpenAI partnership, and they still would have had an impressive array of generative AI features with broad, practical appeal. And clearly they would have gotten a lot more credit for their achievements in the aftermath of the keynote. I remain skeptical that integrating ChatGPT (and any future world-knowledge LLM chatbot partners) at the OS level will bring any significant practical advantage to users versus just using the chatbot apps from the makers of those LLMs. But perhaps removing a few steps, and eliminating the need to choose, download, and sign up for a third-party chatbot, will expose such features to many more users than who are using them currently. But I can’t help but feel that integrating these third-party chatbots in the OSes is at least as much a services-revenue play as a user-experience play.

The most unheralded aspect of Apple Intelligence is that the data centers Apple is building for Private Cloud Compute are not only carbon neutral, but are operating entirely on renewable energy sources. That’s extraordinary, and I believe unique in the entire industry. But it’s gone largely un-remarked-upon — because Apple itself did not mention this during the WWDC keynote. Craig Federighi first mentioned it in a post-keynote interview with Justine Ezarik, and he reiterated on stage with me at The Talk Show Live From WWDC. In hindsight, I wish I’d asked, on stage, why Apple did not even mention this during the keynote, let alone trumpet it. I suspect the real answer is that Apple felt like they couldn’t brag about their own data centers running entirely on renewable energy during the same event in which they announced a partnership with OpenAI, whose data centers can make no such claims. OpenAI’s carbon footprint is a secret, and experts suspect it’s bad. It’s unseemly to throw your own partner under the bus, but that takes Apple Intelligence’s proclaimed carbon neutrality off the table as a marketing point. Yet another reason why I feel Apple might have been better off not announcing this partnership last week.

If you don’t want or don’t trust Apple Intelligence (or just not yet), you’ll be able to turn it off. And you’ll have to opt-in to using the integrated ChatGPT feature, and, each time Apple Intelligence decides to send you to ChatGPT to handle a task, you’ll have to explicitly allow it. As currently designed, no one is going to accidentally interact with, let alone expose personal information to, ChatGPT. If anything I suspect the more common complaint will come from people who wish to use ChatGPT without confirmation each time. At present there’s no “Always allow” option, but some people are going to want one.

At a technical level Apple is using indirection to anonymize devices from ChatGPT. OpenAI will never see your IP address or precise location. At a policy level, OpenAI has agreed not to store user data, nor use data for training purposes, unless users have signed into a ChatGPT account. If you want to use Apple Intelligence but not ChatGPT, you can. If you want to use ChatGPT anonymously, you can. And if you do want ChatGPT to keep a history of your interactions, you can do that too, by signing in to your account. Users are entirely in control, as they should be.

VisionOS 2 is not getting any Apple Intelligence features, despite the fact that the Vision Pro has an M2 chip. One reason is that VisionOS remains a dripping-wet new platform — Apple is still busy building the fundamentals, like rearranging and organizing apps in the Home view. VisionOS 2 isn’t even getting features like Math Notes, which, as I mentioned above, isn’t even under the Apple Intelligence umbrella. But another reason is that, according to well-informed little birdies, Vision Pro is already making significant use of the M2’s Neural Engine to supplement the R1 chip for real-time processing purposes — occlusion and object detection, things like that. With M-series-equipped Macs and iPads, the Neural Engine is basically sitting there, fully available for Apple Intelligence features. With the Vision Pro, it’s already being used.

“Apple Intelligence” is not one thing or one model. Or even two models — local and cloud. It’s an umbrella for dozens of models, some of them very specific. One of the best, potentially, is a new model that will allow Siri to answer technical support questions about Apple products and services. This model has been trained on Apple’s own copious Knowledge Base of support documentation. You can’t say “no reads the documentation” any more — Siri is reading it. Apple’s platforms are so rich and deep, but most users’ knowledge of them is shallow; getting correct answers from Siri to specific how-to questions could be a game-changer. AI-generated slop is polluting web search results for technical help; Apple is using targeted AI trained on its own documentation to avoid the need to search the web in the first place. Technical documentation isn’t sexy, but exposing it all through natural language queries could be one of the sleeper hits of this year’s announcements.

Xcode is the one product where Apple was clearly behind on generative AI features. It was behind on LLM-backed code completion/suggestion/help last year. Apple introduced two generative AI features in Xcode 16, and they exemplify the local/cloud distinction in Apple Intelligence in general. Predictive code completion runs locally, on your Mac. Swift Assist is more profound, answering natural language questions and providing entire solutions in working Swift code, and runs entirely in Private Cloud Compute.

Take It All With a Grain of Salt

Lastly, it is essential to note that we haven’t been able to try any of these Apple Intelligence features yet. None of them are yet available in the developer OS betas, and none are slated to be available, even in beta, until “later this summer”. I witnessed multiple live demos of some of these features last week, during press briefings at Apple Park after the keynote. Demos I witnessed included the writing tools (“make this email sound more professional”) and Xcode code completion and Swift Assist. But those demos were conducted by Apple employees; we in the media were not able to try them ourselves.

It all looks very impressive, and almost all these features seem very practical. But it’s all very, very early. None of it counts as real until we’re able to use it ourselves. We don’t know how well it works. We don’t know how will it scales.

If generative AI weren’t seen as essential — both in terms of consumer marketing and investor confidence — I think much, if not most, of what Apple unveiled in “Apple Intelligence” wouldn’t even have been announced until next year’s WWDC, not last week’s WWDC. Again, none of the features in “Apple Intelligence” are even available in beta yet, and I think all or most of them will be available only under a “beta” label until next year.

It’s good to see Apple hustling, though. I continue to believe it’s incorrect to see Apple as “behind”, overall, on generative AI. But clearly they are feeling tremendous competitive pressure on this front, which is good for them, and great for us.

Read More 

My thanks to Kolide by 1Password for sponsoring last week at DF. The September 2023 MGM hack is one of the most notorious ransomware attacks in recent years. Journalists and cybersecurity experts rushed to report on the broken slot machines, angry hotel guests, and the fateful phishing call to MGM’s help desk that started it all.

But while it’s true that MGM’s help desk needed better ways of verifying employee identity, there’s another factor that should have stopped the hackers in their tracks. That’s where you should focus your attention. In fact, if you just focus your vision, you’ll find you’re already staring at the security story the pros have been missing.

It’s the device you’re reading this on.

To read more about what they learned after researching the MGM hack — like how hacker groups get their names, the worrying gaps in MGM’s security, and why device trust is the real core of the story — check out the Kolide by 1Password blog.

 ★ 

My thanks to Kolide by 1Password for sponsoring last week at DF. The September 2023 MGM hack is one of the most notorious ransomware attacks in recent years. Journalists and cybersecurity experts rushed to report on the broken slot machines, angry hotel guests, and the fateful phishing call to MGM’s help desk that started it all.

But while it’s true that MGM’s help desk needed better ways of verifying employee identity, there’s another factor that should have stopped the hackers in their tracks. That’s where you should focus your attention. In fact, if you just focus your vision, you’ll find you’re already staring at the security story the pros have been missing.

It’s the device you’re reading this on.

To read more about what they learned after researching the MGM hack — like how hacker groups get their names, the worrying gaps in MGM’s security, and why device trust is the real core of the story — check out the Kolide by 1Password blog.

Read More 

The whole point of the public web is that it’s there to learn from — even if the learner isn’t human. Is there a single LLM that was *not* trained on the public web? To my knowledge there is not, and a model that is ignorant of all information available on the public web would be, well, pretty ignorant of the world.

Yesterday, quoting Anthropic’s announcement of their impressive new model, Claude 3.5 Sonnet, I wrote:

Also, from the bottom of the post, this interesting nugget:

One of the core constitutional principles that guides our AI model
development is privacy. We do not train our generative models on
user-submitted data unless a user gives us explicit permission to
do so. To date we have not used any customer or user-submitted
data to train our generative models.

Even Apple can’t say that.

It now seems clear that I misread Anthropic’s statement. I wrongly interpreted “user-submitted data” as including everything on the public web. That’s not true. Here is Anthropic’s FAQ on training data:

Large language models such as Claude need to be “trained” on text
so that they can learn the patterns and connections between words.
This training is important so that the model performs effectively
and safely.

While it is not our intention to “train” our models on personal
data specifically, training data for our large language models,
like others, can include web-based data that may contain publicly
available personal data. We train our models using data from three
sources:

Publicly available information via the Internet
Datasets that we license from third party businesses
Data that our users or crowd workers provide

We take steps to minimize the privacy impact on individuals
through the training process. We operate under strict policies and
guidelines for instance that we do not access password protected
pages or bypass CAPTCHA controls. We undertake due diligence on
the data that we license. And we encourage our users not to use
our products and services to process personal data. Additionally,
our models are trained to respect privacy: one of our
constitutional “principles” at the heart of Claude, based on the
Universal Declaration of Human Rights, is to choose the response
that is most respectful of everyone’s privacy, independence,
reputation, family, property rights, and rights of association.

Here is Apple, from its announcement last week of their on-device and server foundation models:

We train our foundation models on licensed data, including data
selected to enhance specific features, as well as publicly
available data collected by our web-crawler, AppleBot. Web
publishers have the option to opt out of the use of their
web content for Apple Intelligence training with a data usage
control.

We never use our users’ private personal data or user interactions
when training our foundation models, and we apply filters to
remove personally identifiable information like social security
and credit card numbers that are publicly available on the
Internet. We also filter profanity and other low-quality content
to prevent its inclusion in the training corpus. In addition to
filtering, we perform data extraction, deduplication, and the
application of a model-based classifier to identify high quality
documents.

This puts Apple in the same boat as Anthropic in terms of using public pages on the web as training sources. Some writers and creators object to this — including Federico Viticci, whose piece on MacStories I linked to with my “Even Apple can’t say that” comment yesterday. Dan Moren wrote a good introduction to blocking these crawling bots with robots.txt directives.

The best argument against Apple’s use of public web pages for model training is that they trained first, but only after announcing Apple Intelligence last week issued the instructions for blocking Applebot for AI training purposes. Apple should clarify whether they plan to re-index the public data they used for training before Apple Intelligence ships in beta this summer. Clearly, a website that bans Applebot-Extended shouldn’t have its data in Apple’s training corpus simply because Applebot crawled it before Apple Intelligence was even announced. It’s fair for public data to be excluded on an opt-out basis, rather than included on an opt-in one, but Apple trained its models on the public web before they allowed for opting out.

But other than that chicken/egg opt-out issue, I don’t object to this. The whole point of the public web is that it’s there to learn from — even if the learner isn’t human. Is there a single LLM that was not trained on the public web? To my knowledge there is not, and a model that is ignorant of all information available on the public web would be, well, pretty ignorant of the world. To me the standards for LLMs should be similar to those we hold people to. You’re free to learn from anything I publish, but not free to plagiarize it. If you quote it, attribute and link to the source. That’s my standard for AI bots as well. So at the moment, my robots.txt file bans just one: Perplexity.

Read More 

“Honor thy father and thy mother”, the exception that proves the rule.

Sara Cline, reporting for the AP:

The legislation that Republican Gov. Jeff Landry signed into law
on Wednesday requires a poster-sized display of the Ten
Commandments in “large, easily readable font” in all public
classrooms, from kindergarten to state-funded universities.

“If you want to respect the rule of law, you’ve got to start from
the original lawgiver, which was Moses” who got the commandments
from God, Landry said.

Opponents questioned the law’s constitutionality and vowed to
challenge it in court. Proponents said the measure is not solely
religious, but that it has historical significance. In the
language of the law, the Ten Commandments are “foundational
documents of our state and national government.”

Former president and convicted felon Donald Trump, on his floundering social network, approves:

I LOVE THE TEN COMMANDMENTS IN PUBLIC SCHOOLS, PRIVATE SCHOOLS,
AND MANY OTHER PLACES, FOR THAT MATTER. READ IT — HOW CAN WE, AS
A NATION, GO WRONG??? THIS MAY BE, IN FACT, THE FIRST MAJOR STEP
IN THE REVIVAL OF RELIGION, WHICH IS DESPERATELY NEEDED, IN OUR
COUNTRY. BRING BACK TTC!!! MAGA2024

Here is the Protestant version of the Ten Commandments required by the Louisiana law (the Catholic version doesn’t qualify):

1. Thou shalt have no other gods before me.

The Independent, in March: “Trump Compares Himself to Jesus Christ — Again”.

2. Thou shalt not make to thyself any graven images.

The Guardian: “Trump Used His Charity’s Money to Pay for Portrait of Himself”.

3. Thou shalt not take the Name of the Lord thy God in vain.

Politico, 2019: “‘Using the Lord’s Name in Vain’: Evangelicals Chafe at Trump’s Blasphemy”. (Trump crowing, “They’ll be hit so goddamn hard,” while bragging about bombing Islamic State militants. And Trump recounting his warning to a wealthy businessman: “If you don’t support me, you’re going to be so goddamn poor.”)

4. Remember the Sabbath day, to keep it holy.

People magazine, 2022: “Donald Trump spent the Easter weekend enjoying two of his favorite activities, sources say: golf and greeting adoring guests at his Mar-a-Lago resort. On Saturday and Sunday morning, the former president played rounds of golf with members at Trump International Golf Club in West Palm Beach, Florida, a source tells People. ‘He is no longer president,’ says one insider, ‘so he doesn’t have to go to church.’”

5. Honor thy father and thy mother, that thy days may be long
upon the land which the Lord thy God giveth thee.

Trump speaks highly of his father — from whom he inherited his handsome visage and enviable mane — so he’s clear on this one. Quite the man to honor, too. The Washington Post: “Trump’s father, Fred Trump, was arrested twice: in 1927 during a Ku Klux Klan riot, and in 1976 over code violations at a building he owned in Maryland.” The New York Times: “The Justice Department undertook its own investigation and, in 1973, sued Trump Management for discriminating against blacks. Both Fred Trump, the company’s chairman, and Donald Trump, its president, were named as defendants. It was front-page news, and for Donald, amounted to his debut in the public eye.”

6. Thou shalt not kill.

Trump, 2016: “You know what else they say about my people? The polls, they say I have the most loyal people. Did you ever see that? Where I could stand in the middle of Fifth Avenue and shoot somebody and I wouldn’t lose any voters, OK? It’s like incredible.”

7. Thou shalt not commit adultery.

I mean come on.

8. Thou shalt not steal.

Trump University: “The lawsuits centered around allegations that Trump University defrauded its students by using misleading marketing practices and engaging in aggressive sales tactics. The company and the lawsuits against it received renewed interest due to Trump’s candidacy in the 2016 presidential election. Despite repeatedly insisting he would not settle, Trump settled all three lawsuits in November 2016 for a total of $25 million after being elected president.”

9. Thou shalt not bear false witness against thy neighbor.

CNN: “Former President Donald Trump has spent months spreading lies about the 2020 election, which he himself is now calling “THE BIG LIE” as he continues to claim that a massive conspiracy robbed him of a second term.”

10. Thou shalt not covet thy neighbor’s house.

The Vera Coking house: “In 1993, Donald Trump bought several lots around his Atlantic City casino and hotel, intending to build a parking lot designed for limousines. Coking, who had lived in her house at that time for 32 years, refused to sell. As a result, the city condemned her house, using the power of eminent domain. She was offered $251,000, a quarter of what she was offered by Guccione 10 years earlier.”

Read More 

This is not spite. Spite would be saying these features will never come to the EU while the DMA remains in place. But a delayed rollout is the only rational response to the DMA: extreme caution in the face of the law’s by-design uncertainty and severe penalties.

Ian Betteridge:

So, Apple, which bits of the DMA does Apple Intelligence violate?
Because unless you can actually tell us – which case we clearly
have a bit of a problem with some of the claims you’ve made about
how it works — or you’re talking bullshit, and just trying to get
some leverage with the EU. Which is it Tim?

I absolutely guarantee that people are going to swallow this “well
you can’t make Apple Intelligence work thanks to the DMA!!” line
without actually asking any questions about what it violates,
because “well Apple said it and they don’t lie evah”

That’s Apple’s entire point. They don’t know. It’s uncertain by design. EC proponents keep telling me it’s a feature, not a bug, that unlike the US, it’s the spirit, not letter, of the law that matters in the EU. So it doesn’t matter if there’s not a word in the DMA that disallows the Core Technology Fee; European Commissioners have decided it goes against the spirit of the DMA, so they’re going to charge and fine Apple.

Outgoing competition chief Margrethe Vestager (her 10-year term expires in November) gave a 20-minute interview to CNBC’s Silvia Amaro this week, in which she threatened Apple repeatedly, starting around the 13:00 mark.

Vestager: We have a number of Apple issues; I find them very serious. I was very surprised that we would have such suspicions of Apple being non-compliant. They are very important because a lot of good business happens through the App Store, happens through payment mechanisms, so of course, even though you know I can say this is not what was expected of such a company, of course we will enforce exactly with the same top priority as with any other business. […]

Vestager: What I see with the Digital Markets Act is that we get closer and closer to the business model. The changes that the DMA is demanding, they are changes that will touch the business model.

Amaro: Breakups even?

Vestager: Well, it remains to be seen. But if you have to carry a second app store, that will make a dent in your own app store. If you cannot promote your own services, but need to give room for competitors, rightfully, legitimately so, of course that will potentially, sort of, take away some of your own profits. So of course this will be a very difficult enforcement task, but even so much more rewarding, because the potential for the competitors of Big Tech — they are really, really big — and this is why enforcement of the DMA is a top priority.

Amaro: The reason why I am also bringing up Apple is because companies such as Spotify have also raised issues with the new changes that Apple has put forward, that ultimately the bill they will face now is the same or even bigger than what was in place before. And this is why I want to bring up the issue again of whether the DMA is actually leading to ultimate changes for the Big Tech? Or are they still hiding here, in between some of the … well, within the law?

Vestager: Well, I think that you cannot judge the DMA before we’ve had the cases, and before we finalize them, because we have a toolbox of fines, of doubling fines, of potential breakup of companies — so we have a very strong toolbox to punish.

So how is Apple (or Meta, or Google) supposed to launch new features, integrating its own new services deeply within and between its own platforms, while under repeated threats of massive fines, fines that are far out of proportion to the revenue Apple generates in the EU itself, and even — laughably, admittedly — being “broken up”? When Vestager is very clear that Apple will only be deemed compliant with the DMA if it adversely affects Apple’s profit? And when it’s the unwritten “spirit” of the DMA, not the letter of its ambiguous rules, that matters?

This isn’t about privacy or the fact that Apple Intelligence models were trained on data scraped from the public web. Such factors might play a role in Apple Intelligence’s compliance, but not iPhone Mirroring or the new SharePlay screen sharing. This is about the DMA’s restrictions on designated gatekeepers launching their own integrated services and features.

Under repeated threats of fines up to $40–80 billion dollars (10–20 percent of worldwide revenue), it would be recklessly irresponsible for Apple, or any other designated “gatekeeper”, to launch any new services or integrated features in the EU without absolutely certainty that those features are compliant with the DMA. And the nature of the European Commission is that they do not issue such assurances in advance. This is not spite. Spite would be saying these features will never come to the EU while the DMA remains in place. But a delayed rollout is the only rational response to the DMA: extreme caution in the face of the law’s by-design uncertainty and severe penalties.

Fortunately, because Apple is delaying Apple Intelligence and these other new features in the EU, all of the thriving EU-based smartphone and OS makers can jump in and compete on merit now, without Apple the gatekeeping bully in their way. As Vestager reiterates throughout the interview, competition is the European Commission’s north star.

Read More 

The whole 8-minute clip is excellent and worth your time, but do not miss the second half, starting with a sharp question from Alex Rodriguez at the 4:30 mark. Reggie describes, in heartfelt detail, the abject racism he faced as a minor league player as recently as the 1960s. Restaurants he couldn’t eat at. Hotels he couldn’t stay at. Threats to burn to the ground the apartment building where he was sleeping. The pain, over five decades later, remains searing.

Kudos to Fox Sports for airing this. We can’t celebrate progress without honestly facing the dark past. (Kudos too, for putting a box of Reggie Bars at the desk. Respect.)

 ★ 

The whole 8-minute clip is excellent and worth your time, but do not miss the second half, starting with a sharp question from Alex Rodriguez at the 4:30 mark. Reggie describes, in heartfelt detail, the abject racism he faced as a minor league player as recently as the 1960s. Restaurants he couldn’t eat at. Hotels he couldn’t stay at. Threats to burn to the ground the apartment building where he was sleeping. The pain, over five decades later, remains searing.

Kudos to Fox Sports for airing this. We can’t celebrate progress without honestly facing the dark past. (Kudos too, for putting a box of Reggie Bars at the desk. Respect.)

Read More 

The Financial Times:

Apple blamed complexities in making the system compatible with EU
rules that have forced it to make key parts of its iOS software
and App Store services interoperable with third parties.

“Due to the regulatory uncertainties brought about by the Digital
Markets Act,” Apple said on Friday, “we do not believe that we
will be able to roll out three of these features — iPhone
Mirroring, SharePlay Screen Sharing enhancements, and Apple
Intelligence — to our EU users this year.”

Kudos to Apple for breaking this news to the Financial Times, of all outlets. Poetry in media relations. Here’s the full on-the-record statement, provided to me by an Apple spokesperson:

Two weeks ago, Apple unveiled hundreds of new features that we are
excited to bring to our users around the world. We are highly
motivated to make these technologies accessible to all users.
However, due to the regulatory uncertainties brought about by the
Digital Markets Act (DMA), we do not believe that we will be able
to roll out three of these features — iPhone Mirroring, SharePlay
Screen Sharing enhancements, and Apple Intelligence — to our EU
users this year.

Specifically, we are concerned that the interoperability
requirements of the DMA could force us to compromise the
integrity of our products in ways that risk user privacy and data
security. We are committed to collaborating with the European
Commission in an attempt to find a solution that would enable us
to deliver these features to our EU customers without
compromising their safety.

None of these features are available yet in the developer beta OS releases, but it is my understanding that the first two — iPhone Mirroring and the new SharePlay Screen Sharing enhancements (where you’ll be able to see and doodle on the screens of others, like, say, if you’re providing remote how-to help to a friend or family member) — will be the next developer betas, coming early next week. Apple Intelligence won’t even enter beta until later this summer. But in the meantime, even in beta, none of these features will be available within the EU.

The Mac is not considered a “gatekeeping” platform in the EU, but the iPhone and iPad are, and the iPhone Mirroring and screen sharing features obviously involve those platforms. I think Apple could try to thread a needle here and release Apple Intelligence only on the Mac in the EU, but given how inscrutable the European Commission’s interpretation of the DMA is — where gatekeepers are expected to somehow suss out the “spirit of the law” regardless of what the letter of the law says — I don’t see how Apple can be blamed for pausing the rollout in the EU, no matter the platform.

The EU’s self-induced slide into a technological backwater continues.

 ★ 

The Financial Times:

Apple blamed complexities in making the system compatible with EU
rules that have forced it to make key parts of its iOS software
and App Store services interoperable with third parties.

“Due to the regulatory uncertainties brought about by the Digital
Markets Act,” Apple said on Friday, “we do not believe that we
will be able to roll out three of these features — iPhone
Mirroring, SharePlay Screen Sharing enhancements, and Apple
Intelligence — to our EU users this year.”

Kudos to Apple for breaking this news to the Financial Times, of all outlets. Poetry in media relations. Here’s the full on-the-record statement, provided to me by an Apple spokesperson:

Two weeks ago, Apple unveiled hundreds of new features that we are
excited to bring to our users around the world. We are highly
motivated to make these technologies accessible to all users.
However, due to the regulatory uncertainties brought about by the
Digital Markets Act (DMA), we do not believe that we will be able
to roll out three of these features — iPhone Mirroring, SharePlay
Screen Sharing enhancements, and Apple Intelligence — to our EU
users this year.

Specifically, we are concerned that the interoperability
requirements of the DMA could force us to compromise the
integrity of our products in ways that risk user privacy and data
security. We are committed to collaborating with the European
Commission in an attempt to find a solution that would enable us
to deliver these features to our EU customers without
compromising their safety.

None of these features are available yet in the developer beta OS releases, but it is my understanding that the first two — iPhone Mirroring and the new SharePlay Screen Sharing enhancements (where you’ll be able to see and doodle on the screens of others, like, say, if you’re providing remote how-to help to a friend or family member) — will be the next developer betas, coming early next week. Apple Intelligence won’t even enter beta until later this summer. But in the meantime, even in beta, none of these features will be available within the EU.

The Mac is not considered a “gatekeeping” platform in the EU, but the iPhone and iPad are, and the iPhone Mirroring and screen sharing features obviously involve those platforms. I think Apple could try to thread a needle here and release Apple Intelligence only on the Mac in the EU, but given how inscrutable the European Commission’s interpretation of the DMA is — where gatekeepers are expected to somehow suss out the “spirit of the law” regardless of what the letter of the law says — I don’t see how Apple can be blamed for pausing the rollout in the EU, no matter the platform.

The EU’s self-induced slide into a technological backwater continues.

Read More 

Matt Levine, in his Money Stuff column:

OpenAI was founded to build artificial general
intelligence safely, free of outside commercial pressures. And now
every once in a while it shoots out a new AI firm whose
mission is to build artificial general intelligence safely, free
of the commercial pressures at OpenAI.

 ★ 

Matt Levine, in his Money Stuff column:

OpenAI was founded to build artificial general
intelligence safely, free of outside commercial pressures. And now
every once in a while it shoots out a new AI firm whose
mission is to build artificial general intelligence safely, free
of the commercial pressures at OpenAI.

Read More 

Anthropic:

Claude 3.5 Sonnet sets new industry benchmarks for graduate-level
reasoning (GPQA), undergraduate-level knowledge (MMLU), and coding
proficiency (HumanEval). It shows marked improvement in grasping
nuance, humor, and complex instructions, and is exceptional at
writing high-quality content with a natural, relatable tone.

Claude 3.5 Sonnet operates at twice the speed of Claude 3 Opus.
This performance boost, combined with cost-effective pricing,
makes Claude 3.5 Sonnet ideal for complex tasks such as
context-sensitive customer support and orchestrating multi-step
workflows.

In an internal agentic coding evaluation, Claude 3.5 Sonnet
solved 64% of problems, outperforming Claude 3 Opus which solved
38%. Our evaluation tests the model’s ability to fix a bug or add
functionality to an open source codebase, given a natural language
description of the desired improvement. When instructed and
provided with the relevant tools, Claude 3.5 Sonnet can
independently write, edit, and execute code with sophisticated
reasoning and troubleshooting capabilities. It handles code
translations with ease, making it particularly effective for
updating legacy applications and migrating codebases.

I’ll take them with a grain of self-promoting salt, but the evaluation tests presented by Anthropic position Claude 3.5 Sonnet as equal to or better than ChatGPT-4o. Again: I don’t think there’s a moat in this game.

 ★ 

Anthropic:

Claude 3.5 Sonnet sets new industry benchmarks for graduate-level
reasoning (GPQA), undergraduate-level knowledge (MMLU), and coding
proficiency (HumanEval). It shows marked improvement in grasping
nuance, humor, and complex instructions, and is exceptional at
writing high-quality content with a natural, relatable tone.

Claude 3.5 Sonnet operates at twice the speed of Claude 3 Opus.
This performance boost, combined with cost-effective pricing,
makes Claude 3.5 Sonnet ideal for complex tasks such as
context-sensitive customer support and orchestrating multi-step
workflows.

In an internal agentic coding evaluation, Claude 3.5 Sonnet
solved 64% of problems, outperforming Claude 3 Opus which solved
38%. Our evaluation tests the model’s ability to fix a bug or add
functionality to an open source codebase, given a natural language
description of the desired improvement. When instructed and
provided with the relevant tools, Claude 3.5 Sonnet can
independently write, edit, and execute code with sophisticated
reasoning and troubleshooting capabilities. It handles code
translations with ease, making it particularly effective for
updating legacy applications and migrating codebases.

I’ll take them with a grain of self-promoting salt, but the evaluation tests presented by Anthropic position Claude 3.5 Sonnet as equal to or better than ChatGPT-4o. Again: I don’t think there’s a moat in this game.

Read More