When I have written about Apple’s AI and Machine Learning initiatives in the past, the articles have usually centered around Siri and Voice Dictation. It’s easy to put these things together because Siri is the most visible and user-centered Apple interface that involves AI. However, as we have seen this month, there is a lot more than meets the eye going on beneath the surface at Apple.
Last week, Wired ran a story about a lunch talk given by Apple’s leading AI expert, Rutland Salakhutdinov, for around 200 others in the field during the NIPS machine learning conference. The most interesting thing to come out of his presentation was fresh news of Apple’s continued work in the field of self-driving cars.
When Apple scaled back its initial car ambitions a couple of years ago, most of the tech press wrote the company’s initiatives off as somewhere between dying and completely dead. Considering how little we have heard about what Apple has been doing with cars since then, this was an easy assumption. However, as Mr Salakhutdinov’s talk shows, self-driving car technology still remains a priority for Apple’s AI and Machine Learning experts.
Another example of the wider goals of Apple’s AI initiatives can be seen in the company’s Machine Learning Journal, which was started back in July. The most recent post from earlier this month is centered on Apple’s use of Differential Privacy to protect the privacy of individual users’ data while still using Machine Learning to improve their software and services products. The article starts off fairly technical and then REALLY gets into the weeds from there, but it is still an interesting skim, at the very least. This is an area of Machine Learning where Apple has set itself apart from the competition, so it is interesting to gain insights into their work and what is different about it.
While there may be a lot going on with Apple’s AI and Machine Learning efforts beyond Siri, their plucky digital assistant is still a focus. In fact, Siri was included in other discussions at this same Apple lunch event at NIPS. With the HomePod coming soon, you can bet that more on Apple’s direct efforts to improve Siri will come to light after its release. As an example, the Machine Learning Journal entry from November covers Face Detection techniques. This came out right after the release of the iPhone X, with its Face ID facial recognition system and the TrueDepth camera. I would expect a similar article or articles after the HomePod finally arrives.
While these combined efforts are far beyond anything that Apple has allowed in the past, they have to be the be beginning of an even bigger commitment for the company to ultimately have success in AI and Machine Learning. Public presentations, published papers, hiring staff from leading universities (while allowing them to retain their academic connections), and the Machine Learning Journal are just a great start. As Tom Simonite of Wired points out in the aforementioned article, Apple employees have released five academic papers since 2016, while Alphabet staff contributed to 60 papers accepted for the NIPS event, alone. This Apple lunch event was as much a recruiting event as anything else, and if they want to compete for top talent, the doors still have to open much wider.
The encouraging thing here is how much things have changed in just a year since Ruslan Salakhutdinov was hired. This proves to me that executives at Apple were finally convinced of just how behind they are in AI and Machine Learning, and that their typical way of handling all internal business privately wasn’t going to cut it in this field. Based on the evidence, it looks like they have put the right person in charge and are giving him the authority and resources to change things pretty radically.
Hopefully we can look back in another year and see even more signs of openness, as well as some tangible user-facing improvements to Apple’s AI and Machine Learning platforms. Apple will still be making up ground for a while, no matter what, but at least we can now see some evidence that they are heading in the right direction.