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Apple’s Core ML: The pros and cons

Matt Asay | June 19, 2017
Apple’s impressive iOS machine learning technology teeters between its limits and its ease of adoption by developers.

Still, there’s one thing Apple probably should have done, even though it’s still foreign to its culture: Open-source Core ML, thereby giving savvy developers the ability to mold it to their needs. As Holleman points out, “As most other machine learning toolkits are open source, why not make Core ML open source too?”

Except for Apple itself, it doesn’t really matter whether Apple gets machine learning right. “The deeper point,” VC Evans says, is that “many machine learning techniques are getting commoditized and pushed into developer APIs and onto devices and apps very fast.” Because of this, he says, “there won’t just be one Google or Facebook cloud that does all the machine learning—this is a foundational tech that will be in everything.”

Apple’s Core ML is an impressive, even if admittedly limited, step toward this “machine learning inside everything” future.


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