FOD#56: Apple Intelligence – A Calculated Leap into the Future?
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"People who are really serious about software should make their own hardware." This famous quote, often attributed to Steve Jobs but originally from computer scientist Alan Kay, encapsulates Apple's philosophy: a deep integration of hardware and software is key to delivering the best user experiences. Apple's journey in chip design, from outsourcing to developing its own silicon like the A-series and M-series, underscores this philosophy. It began with Steve Jobs' vision and was realized through significant investments in research and development, strategic acquisitions (like PA Semi in 2008), and a close partnership with TSMC for chip fabrication. By making the right move with designing its own chips back then, Apple has set the stage for its current AI strategy. Everyone is now watching to see how Apple will play its AI game, and they answered this question at their annual Worldwide Developers Conference (WWDC) in Cupertino.
The AI Leak and Apple's Strategy
While Microsoft and Nvidia have embargoed pre-briefings to keep one big thing confidential until the very event, Apple involuntarily had to take a different strategy. Everything they were going to announce on Monday was leaked to Bloomberg's Mark Gurman the day before. How that happened – nobody knows, but the company decided to ignore it and calmly announced the old news. Apple has been steadily leaking iPhones since almost the very beginning, so who knows, maybe it is their strategy. Nonetheless, their announcements prove the original strategy of seamless integration of its existing hardware and software ecosystem. This is where the "Apple Intelligence" announcement comes in.
Apple Intelligence and The Power of Integration (with OpenAI)
Two main things from the today’s keynote: Apple’s AI system called "Apple Intelligence," and its collaboration with OpenAI. By waiting and not developing its own conversational LLM like GPT, Apple achieved at least two things: it observed several rounds of GPT developments and saved hundreds of millions of dollars on training the model. Now it can weave the existing and working model into the fabric of the Apple experience. They introduced AI-powered Siri, which will be able to address everything on your Apple device. AI features will include summarizing articles, emails, and messages, and auto-reply suggestions. Big hits are AI-created custom emojis and auto-transcription in Voice Memos. Enhanced photo editing in the Photos app is finally here also. A nod to developers is AI-infused Xcode for automatic code completion, similar to GitHub Copilot.
Apple's advantage is its control over the entire stack, from the chip to the operating system to the apps. This allows for a level of optimization and integration that competitors can't easily match.
Why Apple's AI Matters
Apple's entry into the AI arena is significant for several reasons:
The Road Ahead
While WWDC didn't bring new hardware, it did offer a glimpse into Apple's AI-powered future. It’s well-measured timing to become a major player in the AI landscape. As AI continues to evolve, Apple's ability to seamlessly blend it with its hardware and software could set a new standard for user experiences. The company is betting on the idea that when it comes to AI, the whole is greater than the sum of its parts. And if history is any indication, Apple's bet is likely to pay off.
Additional reading: Great analysis by Stratechery.
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News from The Usual Suspects ?
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The day after Nvidia's introduction of their new chips ahead of the official Computex schedule, AMD announced the MI325X accelerator, available in Q4 2024, and plans for the MI350 series in 2025, boasting 35 times better performance in AI inference compared to the MI300 series. AMD also detailed the MI400 series, expected in 2026. Like Nvidia, AMD is now going to ship new chips annually.
Microsoft faced backlash over its "Recall" feature, which captures screenshots every five seconds, posing significant security risks. Instead of making this feature ‘built-in,’ they switched to opt-in, requiring facial recognition or fingerprint ID and encrypting the search database. From the very beginning, ‘Recall’ didn’t seem to be well thought-through.
On the positive note: Microsoft just introduced Aurora (1.3 b parameters), the first large-scale foundation model of the atmosphere. It uses advanced 3D Swin Transformers and Perceiver-based encoders and achieves remarkable accuracy, outperforming traditional models by predicting atmospheric dynamics, air pollution levels, and extreme weather events with a computational speed-up of approximately 5,000x.
In their blog, they detail how their AI-based code completion now assists with 50% of code characters, significantly boosting developer productivity. Recent updates include AI resolving over 8% of code review comments and adapting pasted code to context. Future goals involve expanding AI applications to testing, code understanding, and maintenance.
Misinformation has been one of the main topics in AI discourse. AI practitioners like Oren Etzioni start companies (check our interview) to prevent harmful misinformation. Though it is still a problem, a paper by Ceren Budak et al. suggests that misinformation is a more manageable problem than previously thought.
Additional read: The Platformer discusses how misinformation's impact is smaller than expected, challenging the notion that it severely undermines democracy. It’s actually a small number of individuals who are responsible for most misinformation spread and that its influence is limited. Platforms like Twitter reduced misinformation significantly by banning habitual spreaders. While concerns remain about the information environment, there is hope that platforms can control misinformation effectively.
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