Don’t get me wrong: Apple’s strategy is very smart from a UX perspective, assuming the Neural Engine
gets a full workout. Use deep learning to power tasks like facial recognition (I’m not convinced this is a game-changer), NLP for text messages, image processing and, of course, Siri. In the process, save battery life by minimizing use of the main CPU and GPU, thus making users that much happier.
But at some point, we might expect the company that all but invented the current image of consumer AI—with Siri—to do something else revolutionary. We might be waiting longer than we think. And not just from Apple, but from Google, Samsung and everybody else, too.
The fact of the matter is that while the field of AI—and deep learning, in particular—is advancing like mad, its strong suit is still in what we might call machine perception. Vision, speech, hearing, language, stuff like that. Which is why we now have devices like the Amazon Echo and Google Home, and phones that can understand us, predict our next words and recognize who’s in our photos. Most of these things we could do before; now we can do them easier or better.
However, there’s still a long way to go before these areas are perfected, and it’s not entirely clear where the next big idea in consumer AI will come from or when it will hit the mainstream. If you look at most consumer applications of AI and machine learning today, they’re really step improvements over the status quo. I think a lot of people would say companies are spending an awful lot of time on AI research so we can add funny mustaches to selfies.
That’s not an indictment of anything, but rather, I would argue, a function of how research works. You don’t change the world overnight, and even promising experimental results can take a long time to make it from lab to production. When they do, I have an easier time seeing game-changing applications of AI in fields like manufacturing, logistics, media and health care than in pure consumer spaces. And even there, we’re talking more about process automation and optimization than about, say, anything that would strike an outside observer as revolutionary. At least in the near term.
Adding intelligence into everyday home appliances at scale could actually be a very big deal, but I don’t recall the last time Whirlpool announced a new dishwasher with all the world watching. Who knows: maybe the consumer-AI winter will come not because there’s no meaningful progress, but because consumers grow tired of incremental improvements presented as monumental achievements and device-makers using AI as a hammer in search of a nail.
I hope I’m wrong (and, let’s be honest, I probably am), because I’d love a new reason to get truly excited about Apple or Google talking about AI during their big unveilings. Until then, I expect to hear a lot more about better battery life, and even better photos and speech recognition. And while they’ll continue to be useful improvements, I also expect the novelty of “we’re doing AI in your phone!” will wear off pretty quickly without some new tricks to back up the claims.