Apple has three pillars for AI: On-device for most of what you need, on Private Cloud Compute servers for most of the rest, or via third-party server-based systems for the most demanding tasks. That’s a blueprint for how the industry will evolve as technologies represented by PrismML tend toward bringing more of that intelligence to the device. Over time, those local tasks will become more sophisticated, eroding the available market for today’s heavily-indebted AI incumbents.
Emerging priorities such as the need for privacy, data sovereignty, and trusted cloud will also spur the emergence of a multipolar AI future in which no one vendor dominates, further complicating their journey to profitability. It’s a model that favors the kind of service-agnostic, edgeAI approach Apple has taken.
EdgeAI for the rest of us
In the end, I don’t think there will be a need for much of the AI data center capacity now being built, because Apple and others will figure out how to use data minimization to transact sophisticated AI tasks on the device. For the most part, EdgeAI will deliver the consumer AI experience, while data centers cater to more sophisticated use. One day, after this gold rush has run its course, we’ll peer outside of our basements to see which of today’s AI firms actually are the chosen ones.
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