Apple Predictions in the AI space.md

Prediction: Apple's Moves in AI

My intuition about Apple Intelligence's failure, is that Apple got burned badly by releasing a half-baked, pitifully small on-device effort too early. They recognised the strategic error and have since pivoted to play a different game - choosing not to follow others in burning their capital or, worse, their product credibility in this space.

Hence, the modest partnership with OpenAI for now. They are unlikely to be market leaders in high-power, on-demand AI, unless they make significant acquisitions in vendor model makers and invest heavily in high-power server-level inference silicon.

Strengths

However, their core product strengths remain clear:

• The consumer (not server—still very AMD-level, nothing special) hardware is amazing.
• A strong recent pivot to near-peerless, end-user, low-power and extraordinarily capable compute silicon.
  • Note: M1 was a gorgeous, groundbreaking piece of hardware
  • Subsequent evolutions have eventually lead to M4, a full generational leap - my personal MacBook Pro is a genuine "pleasure model".
  • The ecosystem/binary transition was clean and, after a few months, felt well-engineered.
  • (Crucially) They have an on-board fast GPU and an inference engine to support small models.
• Similarly, iPhones and iPads have amazing silicon - the last three refreshes in particular.
• Product customer loyalty and a well-integrated ecosystem.
  • Others throw away product. Apple generally looks after their customers, even when they release product with defects.

Strategy

The strategic bets for them — all of which I would eventually take — include:

• The emergence of small (potentially swappable) models that load quickly and fit on consumer devices, providing high-quality general utility.
  • Google is already doing this: Gemma 3n is natively multimodal, even video-capable, and released it under a permissive licences.
  • Meta may have started to lead the way here, but are falling behind, and losing key staff elsewhere.
• Tool-use and instruct will matter, so small model agent prompting can work effectively.
• Agent tools that reach into key Apple developer APIs to fetch context, all while not leaving the phone, tablet or computer, thanks to Apple’s fine-grained, detailed, and well-sandboxed permission model. Respecting user privacy? Piece of cake.

NB: Agentic web search might still be a key feature—so Apple throwing money to buy or licence Perplexity's tech would be a smart bet.

Apple Core Business isn't AI. It's Product

Their business value lies in products which provide clean end-user utility, their loyal creative user ecosystems, and making it easy for developers — and hopefully Apple themselves — to wield small models for powerful, intelligent apps that slot into regular user's lives seamlessly. Useful, intelligent apps that run on Apple consumer devices while positioning inference and context privacy as valuable, marketable features.

All this without overtly burning capital. Apple’s business model is primarily built on hardware or services for cash — we’ve come to expect that ever since Jobs kept pulling "one more thing" rabbits out of hats.

Others do loss-leaders, subsist on venture capital and capture different value.

Apple, by and large, does not. You pay Apple, they give you a product. That's how they built their war chest and I expect they will keep it that way.