Apple's WWDC 2024: AI, Private Cloud Compute, and Responsible Framework

[00:00:00] It's Wednesday, June 12th, 2024, and I'm Dave Sobel. Let's go deep on Apple's WWDC with three things to know today. All the relevant announcements from the event, a look at Apple's private cloud compute, and Apple's AI framework and what providers can learn. This is the Business of Tech.

[00:00:23] I don't rush to break a story because I hope the value I bring is analysis. I'm glad I waited to review the major announcements around Apple's WWDC because most interesting details were not in the headlines. So let's hit the big ones then. I'll highlight the ones I notice.

[00:00:39] So for a summary, Apple's WWDC 2024 keynote featured the introduction of Apple Intelligence, an AI system for iPhone, iPad, and the Mac. Siri also received significant AI upgrades and integration with OpenAI's Chat GPT. Other highlights include new AI features in Mail, Messages, Photos, and more, a more

[00:01:00] customizable Control Center in iOS 18, RCS support for iPhone, and a new Passwords app. iPadOS 18 adds a Calculator app with Apple Pencil support, macOS 15 allows iPhone to be mirrored to the Mac, and watchOS 11 brings new features like Automatic Widget Addition and the Vitals app.

[00:01:22] VisionOS 2 introduces Spatial Photos and an ultra-wide Mac display. AirPods Pro gets Siri interactions and voice isolation. Apple Intelligence is positioned as AI for the rest of us, a kinder and gentler version of AI that powers useful features like prioritizing notifications.

[00:01:43] Unlike other AI demonstrations, Apple's presentation was practical and familiar. Apple Intelligence can perform simple functions like pulling up flight details or helping revise emails. It can also sort emails, prioritize notifications, and enable a reduced notifications mode. It can also be used in image generation.

[00:02:03] Apple Intelligence can retrieve and analyze relevant data from across your apps and reference the content on your screen. It can understand personal information and context, such as recognizing family members and event details, and predicting traffic for route planning.

[00:02:19] Apple has announced AI Additions to its Xcode development environment, aiming to increase the productivity of programmers. The AI features can undertake small and tedious coding tasks, including incorporating AI-powered features into developer apps and adding generative intelligence for code completion in the Swift language.

[00:02:40] And a small note, the largest cheer at the event went up to the release of a calculator app for the iPad as part of iPadOS 18. The app does support Apple Pencil and includes a feature called Math Notes for solving handwritten math problems.

[00:02:55] iPadOS 18 also includes Smart Script for improved handwriting legibility and personalization updates from iOS 18. Now why do we care? People love that calculator. I did want to call out that password app, as there will be a new player in password management that users may quickly migrate to.

[00:03:16] Now there's lots of feature stuff, there's a lot I'm interested in. That said, we care because Apple's AI strategy bakes the technology right into the operating system, and this fall it will be on all Macs with Apple Silica.

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[00:04:31] Visit trinitycyber.com slash MSP4 to learn about their discounted MSP pricing options. But now the stuff I was really intrigued by, the tech used by Apple Intelligence. Apple has launched Private Cloud Compute, a cloud intelligence system designed for privacy-centric AI processing.

[00:04:55] PCC offers advanced security architecture and stateless computation to ensure data privacy. It coincides with the introduction of Apple Intelligence features, including that integration of OpenAI's Chat GPT. PCC utilizes a custom-built server node with Apple Silicon, Secure Enclave, and Secure

[00:05:14] Boot, providing a narrow attack surface and leveraging code signing and sandboxing for data center security. PCC requests are routed through an oblivious HTTP relay to conceal IP addresses. Independent security experts can inspect the code running on Apple Silicon servers, and software images are published for transparency.

[00:05:35] Now how does this work? From the keynote, quote, When you make a request, Apple Intelligence analyzes whether it can be processed on-device. If it needs greater computational capacity, it can draw on Private Cloud Compute and send

[00:05:48] only the data that's relevant to your task to be processed on Apple Silicon servers. Your data is never stored or made accessible to Apple. It's used exclusively to fulfill your request. And just like your iPhone, independent experts can inspect the code that runs on the servers

[00:06:05] to verify this privacy promise. In fact, Private Cloud Compute cryptographically ensures your iPhone, iPad, and Mac will refuse to talk to a server unless its software has been publicly logged for inspection. End quote.

[00:06:19] If you want to go deep here, MIT Technology Review has a solid look at the technology, and the Register talks about the servers themselves, those custom servers built on Apple Silicon. Now why do we care? And here's where things get particularly interesting.

[00:06:35] This architecture is what all the money buys you. A thoughtful solution built around privacy. Of course, it's sensible to wait for a full security analysis. But just the overview shows the difference in approach from Microsoft, OpenAI, and Google.

[00:06:49] What's also unique about all of this is that it's a feature, not a product. If you're an Apple user, you get all this. No extra fees for Apple's version. That's not reductive of the IT service provider value, as the advice, guidance, training,

[00:07:03] and consulting work is all still relevant. AI is a feature, not a product. And how that feature works is IT's job to understand and make relevant for customers. I talk a lot about frameworks on the show, and Apple has a specific one they announced from their blog. Quote,

[00:07:26] We have created a set of responsible AI principles to guide how we develop AI tools as well as the models that underpin them. One, empower users with intelligent tools. We identify areas where AI can be used responsibly to create tools for addressing specific user needs.

[00:07:42] We respect how our users choose to use these tools to accomplish their goals. Two, 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 systematic biases across our AI tools and models.

[00:08:01] Three, 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.

[00:08:14] We will continuously and proactively improve our AI tools with the help of user feedback. And four, protect privacy. We protect our users' privacy with powerful on-device processing and groundbreaking infrastructure like private cloud compute.

[00:08:27] We do not use our users' personal, private, and data or user actions when training our foundation models. Why do we care? Apple's created a pretty high standard for privacy around AI and then finally showing transparency on their approach.

[00:08:43] I highlight this as a case study for use with customers. There's a ton of work with here. This is the beginning work for a successful implementation and what providers should be working on now.

[00:08:55] On the live show today, Seth Robinson from CompTIA and I talked about how to do it. That'll drop on the podcast feed on the weekend. Thanks for listening. Today is National Loving Day. How could I not spread such a positive one? Have a question you want answered?

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