Recently, Apple made headlines for hiring John Giannandrea, Google’s former head of search and artificial intelligence, to lead Apple’s machine learning and AI strategy. For many, including myself, this was welcome news. Of all the tools available, Siri has been the AI laggard, and it’s a shame. Not just because it’s [severely] limited in comparison to Google Assistant and Amazon Alexa, but because they lost an early lead. But does hiring Google’s AI Chief mean a better Siri?
It’s hard to believe, but Siri was introduced with the iPhone 4S—nearly seven freaking years ago. Seven years! Well before Alexa was even a twinkle in Jeff Bezos’ eye. Years before Google Assistant or Cortana was even a thing.
I don’t have to play-back all the ways Siri lags behind its brethren. That story’s been written a thousand times. And I won’t even bring up the merits of Siri’s intent-based structure (that allows users to ask the same question many different ways), over Alexa’s “you-better-remember-the-unique-syntax-of-each-and-every-Alexa-Skill” approach.
The bottom line is, in 2018 (or 2016 for that matter), that’s not nearly good enough. For the record, it’s not because it painted itself into a security/privacy corner by not letting iCloud and Tim Cook read every message you write and see every picture you take (you listening, Zuckerberg?). Yes, the more data the better is the rule of thumb when building-out machine learning and AI algorithms, but the sheer size of the Apple ecosystem means Apple already possessed enough data to be a helluva lot better than they are…especially if you believe in differential-privacy.
What matters is that Tim Cook and Apple have realized it’s time to do something different (remember “Think Different?”) if they no longer want Siri to be the laughing stock of Silicon Valley. Or perhaps they finally realized the future is an AI-centric world.
Apple has taken additional steps to improve its machine learning and make it available to iPhone users. It was once believed that Apple couldn’t hire the best because they wouldn’t let employees publish their work. That’s changed. In fact, the Apple Machine Learning Journal has been a pretty good read. CoreML is a powerful way to let developers incorporate state of the art Machine Learning algorithms into their apps and doubled-down on that approach with the announcement last month they are expanding their partnership with IBM to bring the power of Watson to the iOS platform. Plus, Apple has done some amazing work using Neural Networks in the iPhone/iOS, including Face Detection and Voice Detection. So it’s not like they don’t know what they’re doing.
But now they have hired Giannandrea—arguably one of the best in the field. And when it comes to machine learning—like data—more is better. But is it enough?
The one thing that’s always driven me crazy about Apple’s approach with all their cloud-driven services is that they sync updates with iOS releases, when everyone knows the cloud doesn’t work that way. I know this is nothing new; similar things have been said by Stratechery’s Ben Thompson as well as by that “other Gruber.” Some of this owes to the iPhone being far and away the most important product for the company and some owes to the functional organization structure Apple is famous for. This organization structure is absolutely appropriate when you need to keep hardware and software advancements in sync for the launch of a new device with amazing new technologies. If those teams are not all on a string, it would be almost impossible to pull off something like Face ID.
But the cloud, machine learning, and AI don’t work like that. These services should be constantly evolving based on new data that just came in—not based on the iPhone’s annual release schedule. Keeping such teams in organizational alignment with the hardware/OS teams not only doesn’t make sense, it also holds back the full potential of the team.
Do I believe the Apple Services business needs to be spun off to finally unlock that potential? No. But a little organizational freedom may help. And that’s where the press release around Giannandrea’s hire gives me hope. He was hired as a direct report to Tim Cook, not under Hair Force One. Perhaps…perhaps…Cook will let Giannandrea run his team the way he wants, free from being tied to the rest of the engineering organization, so he can move at “web speed” versus to an annual cadence.
So, will the move solve Apple’s AI problem? I have hope.