When you think back to the heady days of last week, it’s hard to ignore that the introduction of Apple Intelligence on Monday now means the company formerly known as “behind on AI” just overtook Microsoft to bring home the world’s biggest and most trusted platform for generative AI (genAI).

The reason it’s hard to ignore is because it is true. Sure, Microsoft Copilot does lots of things already and once you can actually spend cash on Surface devices that run Copilot, Microsoft will be a powerful AI platform.  But Apple will be, too. (You can understand why Microsoft was unhappy about Apple’s deal with OpenAI.)

Mac, mobile, tablet, cloud

But I’d argue that Apple might be more powerful, because Apple Intelligence (the name Apple has given its own genAI models, served up both on device and in the cloud) will run on PCs (Macs), tablets, and mobile devices. 

I imagine it will in the future be supported on visionOS, and suspect it is only a viable usage case away from running on any other Apple device equipped with a capable processor. 

Millions of users on day one

Once Apple Intelligence is released, it will be available on hundreds of millions of devices on day one. Those devices won’t need to be new, either — those are the ones that are already being used. Apple says any Mac or iPad running an M1 or later chip will run it. It also says any iPhone 15 Pro series model will be able to handle it.

That’s a huge market, and no one needs to spend a dime to get into it. Those who do plan to upgrade or want to invest in exploring what’s available have plenty to look forward to on the journey to fall when the upgrade ships.

After all, if you squint, you can just about see M4 Macs appearing at the top of that nearby hill now the iPad Pro has that chip. We also think new iPhones are very likely to be already rolling off production lines, and both the iPad Air and iPad Pro already host compatible chips.  So, if you’re in the market for new hardware, it’s on the way, but tens of millions of people won’t need to upgrade to try Apple’s new genAI shiny.

Competitors are gasping

When it comes to Apple Silicon — the fire horse on which AI rides in the newly rebirthed Apple universe — take note that it has taken competitors, even those working with Arm reference designs, literally years to even begin to catch up with the computational power and energy efficiency Apple’s designers achieved. 

With a road map to M4 and beyond already in place, Apple is quite evidently telling us that when it comes to processors the speed argument is done, dusted, and won. And don’t get me started on privacy after the Microsoft Recall farce.

The power of consent

We can see Apple becoming the world’s leading provider of genAI-wielding devices for the mass market. Not only that, but because it is building a system that is private by design, consumers get the best of both worlds: complete data privacy for some tasks and the option of using AI from other vendors for other tasks, if they choose to do so.

That’s an alluring combination of privacy and consent, and that choice — that sense of personal AI-boosted empowerment — is coming to literally hundreds of millions of devices in real time. (Though that number is dented by the fact that we believe only US devices will get these features in the first draft, which is a shame.)

Consumers don’t have to use AI, but they will be happy that they can.

But it’s also about making 

Apple Intelligence can handle a huge number of tasks. Boosted by developers working with their own AI models and App Intents, the number of tasks it can do will only grow. 

I mentioned that developers will be able to use their own AI models in apps. What do you think they will build those models on? Well, they are Apple developers and will very likely build them using a Mac. 

That won’t just be because you need a Mac to build Apple apps, but also part because the M-series chips inside Apple’s computers demonstrate excellent training performance using most AI training tools. That’s why developers building AI models for other platforms also use Macs.

Now, I don’t know if the MacBook Pro is the most popular system on which to build AI models among data scientists — you have to be cautious about cause and effect — but I think it’s probably close.

Controlling the means of production

You see, Apple doesn’t just build fantastic machines to build AI models on, but now also offers a vast global ecosystem of devices on which to run those AI models.

Ever since the genAI bubble blew up, Apple has flexed its innovative power to jump from somewhere at the back to head of the pack when it comes to the technology. It is not the first time it has made a leap like that — it didn’t build the first music player, smart mobile device, netbook (it skipped them for tablets), or music streaming service, either.

But despite the impressive way in which Apple has jumped from zero to hero, the inconvenient question remains: Are humans ready for AI and the gigantic leaps in machine intelligence it will bring? Particularly when you look ahead to when we will run AI on quantum processors, as we eventually will — what have we unleashed?

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Adobe will change language in the terms of use for its software, as it seeks to clarify its position on content ownership and the use of customer data to train generative AI (genAI) models. 

The move comes in response to a customer backlash over an update to Adobe’s terms of use for Creative Cloud and Document Cloud software earlier this month. Some customers had interpreted the language to mean Adobe would gain access to their work for training purposes. 

The updated terms include several changes, including a statement that Adobe “may access your content through both automated and manual methods, such as for content review.”

Subscribers were required to re-accept the updated terms or lose access to Adobe’s apps and services. 

Customers raised concerns over Adobe’s ability to view and access content, highlighting concerns aboutcontent protected by a non-disclosure agreement.

Adobe attempted to explain the changes to its terms in a blog post June 6, stating the intention was to clarify updates to its moderation processes. Adobe said that it does not train its Firefly genAI model on customer content, and will “never assume ownerships of a customer’s work.”

On Monday, the company published another post, this time acknowledging the need to clarify the language in its terms of service after customer pushback. Adobe said it would consult with customers before changes are made on June 18. 

Adobe said that while its stance around the use of customer content is unchanged, it should have “modernized” and updated the terms of use sooner to explain legal language more clearly to customers. 

“Our updated Terms of Use, which we will be releasing next week, will be more precise, will be limited to only the activities we know we need to do now and in the immediate future, and uses more plain language and examples to help customers understand what they mean and why we have them,” Adobe said in the latest  blog post. 

While nine out of 10 IT professionals say they want to implement generative artificial intelligence (genAI) in their organization, more than half have integration, security and privacy concerns, according to a recent survey released Wednesday by Solarwinds, an infrastructure management software firm.

The SolarWinds 2024 IT Trends report, AI: Friend or Foe? found that very few IT pros are confident in their organization’s readiness to integrate genAI. The company surveyed about 7,000 IT professionals online regarding their views of the fast-evolving technology, and despite a near-unanimous desire to adopt genAI and other AI-based tools, less than half of respondents feel their infrastructure can work with the new technology.

Only 43% said they are confident that their company’s databases can meet the increased needs of AI, and even fewer (38%) trust the quality of data or training used in developing the technology. “Because of this, today’s IT teams see AI as an advisor (33%) and a sidekick (20%) rather than a solo decision-maker,” SolarWind said in its report.

Privacy and security worries were cited as the top barriers to genAI integration, and IT pros specifically called for increased government regulations to address security (72%) and privacy (64%) issues. When asked about challenges with AI, 41% said they’ve had negative experiences; of those, privacy concerns (48%) and security risks (43%) were most often cited.

More than half of respondents also believe government regulation should play a role in combating misinformation. “To ensure successful and secure AI adoption, IT pros recognize that organizations must develop thorough policies on ethics, data privacy, and compliance, pointing to ethical considerations and concerns about job displacement as other significant barriers to AI adoption,” the report said.

SolarWinds found that more than a third of organizations still lack ethics, privacy and compliance policies in place to guide proper genAI implementation. “While talk of AI has dominated the industry, IT leaders and teams recognize the outsize risks of the still-developing technology, heightened by the rush to build AI quickly rather than smartly,” said Krishna Sai, senior vice president, technology and engineering, at SolarWinds.

Indeed, leading security experts are predicting hackers will increasingly target genAI systems and attempt to poison them by corrupting data or the models themselves. Earlier this year, the US National Institute of Standards and Technology (NIST) published a paper warning that “poisoning attacks are very powerful and can cause either an availability violation or an integrity violation.

“In particular, availability poisoning attacks cause indiscriminate degradation of the machine learning model on all samples, while targeted and backdoor poisoning attacks are stealthier and induce integrity violations on a small set of target samples,” NIST said.

Overall, the IT industry’s sentiment reflects “cautious optimism about AI despite the obstacles,” SolarWinds reported. Almost half of IT professionals (46%) want their company to move faster in implementing the technology, despite costs, challenges, and concerns, but only 43% are confident that their company’s databases can meet the increased needs of AI. Moreover, even fewer (38%) trust the quality of data or training used in developing AI technologies.

IT pros cited AIOps (Artificial Intelligence for IT Operations) as the technology that will have the most significant positive impact on their role (31%), ranking above large language models and machine learning. More than a third of respondents (38%) said their companies already use AI to make IT operations more efficient and effective.  

Apple Intelligence is the big buzz at WWDC. But when it comes to AI and the cloud, if you aren’t a huge enterprise or well-funded government, privacy and data security have always been a challenge when using any cloud service. With the introduction of Private Cloud Compute (PCC), Apple just did cloud services right — and put a real competitive moat in place.

Apple seems to have solved the problem of offering cloud services without undermining user privacy or adding additional layers of insecurity. It had to do so, as Apple needed to create a cloud infrastructure on which to run generative AI (genAI) models that need more processing power than its devices could supply while also protecting user privacy. 

While you can also use ChatGPT with Apple Intelligence, you do not need to (and OpenAI has promised not to store your data under the Apple deal, I think); PCC helps you run Apple’s own GenAI models instead.

The Apple achievement explained

“You should not have to hand over all the details of your life to be warehoused and analyzed in someone’s AI cloud,” Apple Senior Vice President of Software Engineering Craig Federighi said when announcing the service Monday at WWDC.

To achieve this, Apple has poured what I imagine is more or less a nation-state level security budget into creating a highly secure cloud-based system that provides the computational power some problems will require to be resolved.

The introduction comes at a time when providers are rolling out a range of trusted cloud and data sovereignty solutions to answer similar challenges across enterprise IT; Apple’s Private Cloud Compute service represents the best attempt yet to provide trusted cloud access to the mass market. It comes as security experts warn against unconstrained use of cloud-based genAI services in the absence of a privacy guarantee. 

(Remarkably, Elon Musk’s first reaction on hearing of Apple Intelligence was to label it a security threat, when that is precisely what it has been built not to be — you don’t have to use OpenAI at all, and I expect device management tools will be able to close off access to doing so. Perhaps a PCC-style service will eventually form part of the ecosystem for autonomous vehicles that are actually safe?)

What is Private Cloud Compute?

Private Cloud Compute consists of a network of renewable-energy powered Apple Silicon servers Apple is deploying across US data centers. These servers run Apple’s own genAI models remotely when a query demands more computational power than is available on an Apple device. (We don’t expect some of the newly introduced Apple Intelligence services to be available outside the US until 2025, likely reflecting the time it will take to deploy servers locally to support them.)

The idea is that while many Apple Intelligence tasks will run quite happily at the edge, on your device, some queries will require more computational power — and that’s where the PCC kicks in. 

But what about the data you share when making a query? Apple says you don’t need to worry, promising that the information you provide isn’t accessible to anyone other than the user, not even to Apple. 

This has been achieved through a combination of hardware, software, and an all-new operating system. The latter has been specially tailored to support Large Language Model (LLM) workloads, while presenting a very limited potential attack surface. 

This is the power of what is at core server-side Unix, coupled with Apple’s own proprietary system security software and a range of on-device, on-system hardened and highly secure components.

How does this all fit together?

The hardware itself is built around Apple Silicon, which means the company has been able to protect the servers with built-in security protections such as Secure Enclave and Secure Boot. These systems are also protected by iOS security tools, such as Code Signing and sandboxing.

To provide additional protection, Apple has closed down traditional tools such as remote shells and replaced them with purpose-built proprietary tools. There is also something Apple calls Swift on Server on which the company’s cloud services exist. The use of Swift, Apple says, ensures memory safety, which helps further limit any attack surface.

This is what happens when you make an Apple Intelligence request:

• Your device figures out if it can process the request itself.
• If it needs more computational power, it will get help from PCC.
• In doing so, the request is routed through an Oblivious HTTP (OHTTP) relay operated by an independent third party, which helps conceal the IP address from which the request came.
• It will only send data relevant to your task to the PCC servers.
• Your data is not stored at any point, including in server metrics or error logs; is not accessible; and is destroyed once the request is fulfilled.
• That also means no data retention (unlike any other cloud provider), no privileged access, and masked user identity.

Where Apple really seems to have made big steps is in how it protects its users against being targeted. Attackers cannot compromise data that belongs to a specific Private Cloud user without compromising the entire PCC system. That doesn’t just extend to remote attacks, but also to attempts made on site, such as when an attacker has gained access to the data center. This makes it impossible to grab database credentials to mount an attack.

What about the hardware?

Apple has also made the entire system open to independent security and privacy review — indeed, unless the server identifies itself as being open to such review, the information will not be transmitted — so no spoof PCC for you. 

The company didn’t stop there. “We supplement the built-in protections of Apple Silicon with a hardened supply chain for PCC hardware, so that performing a hardware attack at scale would be both prohibitively expensive and likely to be discovered,” the company said. “Private Cloud Compute hardware security starts at manufacturing, where we inventory and perform high-resolution imaging of the components of the PCC node before each server is sealed and its tamper switch is activated.”

What that means: Apple has put protections in place to maintain server security that extend all the way from the factory where those servers are made. That’s a huge step on its own account.

What about Apple’s genAI software?

Apple also maintained a focus on user security while developing the tools it makes available within Apple Intelligence. These follow what it calls its “Responsible AI principles,” as explained on the company site. These are:

• “Empower users with intelligent tools: We identify areas where AI can be used responsibly to create tools for addressing specific user needs. We respect how our users choose to use these tools to accomplish their goals.
• “Represent our users: We build deeply personal products with the goal of representing users around the globe authentically. We work continuously to avoid perpetuating stereotypes and systemic biases across our AI tools and models.
• “Design with care: We take precautions at every stage of our process, including design, model training, feature development, and quality evaluation to identify how our AI tools may be misused or lead to potential harm. We will continuously and proactively improve our AI tools with the help of user feedback.
• “Protect privacy: We protect our users’ privacy with powerful on-device processing and groundbreaking infrastructure like Private Cloud Compute. We do not use our users’ private personal data or user interactions when training our foundation models.”

Apple has also thought about whose data it uses to train its models and promises that its Apple Intelligence LLMs are trained on licensed data, “as well as publicly available data collected by our web-crawler, AppleBot.” (If you don’t want your content crawled by AppleBot for use in training models you can opt out, as explained here.)

While researchers will kick Apple’s systems around, it looks very much like the company has crafted a highly secure approach to genAI from the device used to request a service all the way to the cloud, with software and hardware protections in place every step of the way. 

What Apple has achieved

There is a lot more to consider — take a look at this white paper — but Apple has achieved something potentially very good here: an ecosystem that provides private genAI services, and can be extended over time. 

I’m seeing positive reaction from across the security community to Apple’s news.

“If you gave an excellent team a huge pile of money and told them to build the best ‘private’ cloud in the world, it would probably look like this,” Johns Hopkins cryptography lecturer Mathew Green said. He also warned that the right to opt out of using Apple Intelligence should be more visible and suggested that the impact of Apple’s move will effectively lead toward more use of cloud services.

 “We believe this is the most advanced security architecture ever deployed for cloud AI compute at scale,” said Apple Head of Security Engineering and Architecture Ivan Krstić

Is that really the case? Perhaps. Apple has promised that additional transparency to confirm its security promise is on the way. Though I do wonder how this service will gel with those bandit nations (such as the UK) that legislate for pretty much constant data surveillance in order to protect nothing much at all.

But in terms of end user protection and a fully figured out system to support cloud services, Apple’s new offering shows what every cloud service should aspire to exceed. 

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It will take a while to process all of Apple’s many big WWDC announcements on Monday, but one set of improvements I can’t wait to use are the ones packed inside the Apple Intelligence-augmented Mail app. 

Based on what we’ve been told, these enhancements will really help any enterprise professional, knowledge worker, or frankly anybody who uses Mail. 

I ask you, who doesn’t struggle with over-full email boxes and important responses we don’t make because “life” gets in the way? It is also interesting that those improvements mean Apple devices will now offer the tools we used to have to pay through the nose for with Grammarly.

Ease the email pain points

As had been rumored, Apple took the wraps off its plans for artificial intelligence (“Apple Intelligence) at its big developers conference. We’ll be writing about them for weeks and months to come. I’m focused now on Apple’s improvements to Mail, which should (I hope) help push the tech out of the way and let us get on with what we need to do. They do so because they begin to answer the biggest problem with email: why is an industry standard solution that’s packed with our data — and that we use every day — now a more actively useful space.

That’s because, in tandem with the company’s on-device contextual intelligence, the information coming into your email box is made more easily actionable with the changes and additions Apple plans.

Together, these should go far toward turning Mail into a central focus space from which users can complete most communication and task-related projects. And by the time the changes ship this fall, I expect Apple will deliver a powerfully integrated mail experience that helps you get work out the way — so you can focus on making better genmojis.

Just take a look at the powerful features Apple Intelligence promises us.

Powerful and useful writing tools

Apple’s new Writing Tools (available in Mail, other Apple apps and to third-party developers via an API) offer a range of functions. They can rewrite and/or proofread what you have already written; summarize your message; bullet point the key points in your message; create tables and lists; and even change the tone of your mail.

The latter feature lets you take what you’ve written and, at the tap of a button, generate (for example) a professional tone that still says what you want to say, while not being overly informal. Better yet, these tools are available system-wide, and none of what you write leaves your system, unless you make and approve a request that wants to use tools provided by OpenAI’s Chat GPT. (Yes, that pre-WWDC rumored tie-up turned out to be correct, as well.)

Smart message prioritization 

Apple Intelligence will learn which of your incoming messages are most likely to be important and file them into the Priority Messages view in your Inbox. This will make it much easier to find them.

Apple explains: “On-device categorization organizes and sorts incoming email into Primary for personal and time-sensitive emails, Transactions for confirmations and receipts, Updates for news and social notifications, and Promotions for marketing emails and coupons. Mail also features a new digest view that pulls together all of the relevant emails from a business, allowing users to quickly scan for what’s important in the moment.”

It also handles important notifications the same way.

Summaries in messages and mail

Sometimes we have little time, and yet whoever we’re interacting with has a great deal of complex information to share; the result is a lengthy email. Sure, the whole message should probably be read, but if you’re short of time, you can use Summaries in Messages to get the gist of the entire diatribe. Yes, if you completely rely on summaries you’ll probably miss something, but if you are in a hurry and just need the basics, Apple Intelligence has your back.

Built-in transcription tools

Apple Intelligence lets you generate summaries and transcripts of audio recordings captured with the Notes app or during a phone call. This is going to be popular with a lot of people — particularly researchers, students, and journalists. (If you’re concerned about privacy, all parties in a phone call will be told this activity is taking place.)

The new audio transcription and summarization features in Notes enable a device to take notes for the user, Apple says. This lets them, “stay present in a situation where they need to capture details about what’s happening,” which means you can stay focused in that meeting and still have a useful and usable aide memoire.

Natural Language search

Have you ever spent time searching Mail for a message from a specific person that contains something you vaguely recall, but which you just can’t find using standard search in the app? Apple Intelligence brings natural language search, which should make it easier to find messages, documents, and other items when you can’t quite recall what they were called or where they are.

Contextual Siri

Siri now (finally?) gains semantic search. That means it will be able to understand information and relationships it couldn’t decipher before. Apple seems to promise this extends to understanding and creating language and images, acting across apps, and simplifying and accelerating everyday tasks. You can switch between text and voice to communicate with Siri in whatever way is most appropriate. 

What about Grammarly?

Many users rely on Grammarly to improve their writing. That seems like a less essential investment now that Apple’s writing tools exist, and not only do they exist, but they do so at no charge. One more thing? Apple’s writing tools do not collect the writing work you’ve done. To be fair, Grammarly says it protects your data; but as every hacker knows, the best data you can have if you want to stay secure is data that does not exist. Apple delivers.

Whatever next?

Apple execs, over the course of there presentations, introduced a horde of improvements, many of which will I think improve the user experience across the iOS, macOS and iPadOS platforms. Many of the richer experiences it highlighted mean its entire platform ecosystem (with the weird and probably temporary exception of visionOS), is now an AI platform. It also means that whatever Apple can’t yet do on the device can be outsourced easily to partners like OpenAI. 

The deal here seems to be that Apple maintains its hold on the intention and the experience, while also delivering access to genAI tools, preserving user privacy, and massively enhancing the email experience to the benefit of all knowledge workers. The integrated AI on your device can deliver highly personalized responses based on your specific data, without anyone other than you and the device knowing anything about you.

“It’s personal, powerful, and private — and integrated into the apps you use every day,” wrote Apple CEO Tim Cook.

That privacy promise is powerful. Though, there is a catch. 

As we had heard, you’ll need a Mac or iPad running an M1 or newer chip, or an iPhone 15 series device or newer to use Apple’s AI features, though anyone with a device running iOS 18 will probably enjoy the little blip they might see appear on screen when pressing a side button. Apple’s WWDC announcements show its continued attention to detail, as does the way it has chosen to bring genAI to the rest of us, while working to protect our privacy.

No other company does this as well — and no one else just hit the ground with hundreds of millions of users in one move.

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It looks like artificial intelligence (AI) will be the heart of Apple’s announcements at WWDC this week. Now, we think we also know what devices will be needed to support the new — beta — features if you’re a developer given the right to install the new operating systems.

What is expected

Apple is preparing to shake a little of its reality distortion dust. That magic powder will be used to show how the company has already placed AI inside its devices, and to show how with the addition of generative AI (its own and from partners) it now offers the world’s first multi-platform (PC, smartphone, tablet, watch, spatial) AI computing ecosystem.

Apple will call it “Apple Intelligence,” according to Bloomberg.

The company might not fully realize its ambitions, but this is the direction in which it is going. It is also possible that not every feature Apple wants to talk about will be fully active yet — and some might not reach our devices until 2025. 

But they’re certainly coming. Apple has, after all, been informed by cutting-edge AI research since the company’s inception, though there’s no doubt that the rate of innovation has accelerated incredibly rapidly in the last two to three years.

The current thinking: Apple now sees this AI work as transformational and thinks it will form the foundations for another decade of product innovation — the USP of which will likely be Apple’s hardware and software excellence all supported by AI and trusted cloud services.

AI improvements will include…

Along with news of partnership with third-party genAI developers, these are some of the improvements coming:

• Mail becomes far smarter. Not only will it be able to recommend genuine seeming pre-written emails to help you get through them faster, but it will be capable of automatically filtering emails into specific channels and more. All of these features will be incredibly welcome, and some extend to Messages.
• Automatic on-device transcription tools that should make most enterprise professionals happy (most of the time). You’ll never need to argue over what was discussed during a meeting again.
• AI-powered tools in Keynote and Pages to help you swiftly put together presentations and documents.
• Safari will summarize web pages, Spotlight improves, new health and AI features will appear, notifications and news reports will be summarized, and Siri will get smarter and gain more capabilities.
• AI-boosted image editing in Photos and other additions to most of Apple’s own apps.

These tools and features effectively represent a quantum leap forward for what Apple’s hardware can achieve. Those AI-powered gadgets that raised a little attention earlier this year were interesting, but these tools get even better when you can access some of them via the Apple Watch you already wear on your wrist.

What you’ll need

Not every Apple Watch, iPhone or other device is expected to be able to run some or all of the new AI features, and the current speculation is that only the most relatively recent Apple Silicon processors will make the grade.

If that is the case, this is possibly because handling the kind of computational load created by genAI requests is extremely intensive. It takes a lot of computer power to ask ChatGPT for a recipe suggestion, and even some relatively recent devices might not yet be up to the task.

What this means is that to access these services, you will need to be running an iPad or Mac with an M1 chip, or later. These services will also require at least an iPhone 15 series device. I imagine this will spark an upgrade surge as Apple customers seek to try these new services.

In use, Apple is thought to have developed an on-device computational mechanism that will choose whether to process specific tasks on the device or via M2-based servers it is now thought to be putting into place. You’ll be able to opt-in to using these services, and the company will focus on privacy.

That’s the speculation so far, we’ll learn the real deal soon at WWDC 2024.

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