Apple vs. Google: enter the mobile machine learning race

The competition between the biggest tech companies in the world is no doubt an intense one. Just take the heated battles over cloud computing dominance as an example.

Companies like Amazon, Microsoft, and Google want to be at the top of the mountain and are trying to do so with cutting edge technological advances and better deals for consumers. The same can be said of the mobile device race. We’ve already seen how Apple, Google, and others are trying to one-up each other with better devices showcasing revolutionary new features.

One particular feature happens to be a major focus for both Google and Apple. Machine learning may not be one of those items that consumers know a lot about, but it could end up defining a new generation of mobile devices. Both Apple and Google hope to be the leaders on this front, and both are going about it with different strategies.

Machine learning essentially means having a computer able to sort, organize, and analyze vast amounts of data without actually having explicit programming telling it what to do exactly. Think of it like a limited form of artificial intelligence. In essence, the computer learns what it should do based upon user feedback, and this can lead to more convenient products that improve over time without the need for updates based off of programmer recommendations. It’s a new field just brimming with potential, so it’s little surprise why the major players in the mobile device marketplace want to capitalize on it.

Google hopes to implement machine learning into its popular Android devices. Part of this strategy involves the recent announcement of a partnership with Movidius. Google plans on buying special chips from Movidius specifically designed for machine learning processing.

The idea of using machine learning for mobile devices is certainly not a new one. In many cases, this attribute is still present with Google’s cloud applications, however the inclusion of Movidius chips means the machine learning capability will be present on the devices themselves. That means machine learning processing can happen much more quickly, even in real time. The result is no latency issues like those found going the cloud computing route.

Apple is also trying to incorporate aspects of machine learning into its own lineup of iPhones. In much the same way Google is working with Movidius, Apple recently acquired Perceptio. Perceptio is an artificial intelligence company that specializes in processing real time machine learning data on mobile smartphones and other devices. From these recent announcements, it’s clear Apple is favoring an approach emphasizing new software, while Google is going the route of better processors.

Both of these strategies show that the race toward machine learning mobile devices is going to be a tight one.

The results of that race, however, probably won’t be seen for another few years. The newest Androids and iPhones won’t have them, so the strategies are more of a long-term investment for both companies. The mobile device emphasis can also be seen as only a portion of what is a much larger scale strategy involving machine learning and artificial intelligence in multiple facets of Apple and Google.

Apple, for example, recently hired more than 80 artificial intelligence experts to help with the company’s efforts at capturing the potential of machine learning and discovering big data solutions. Google has been pursuing machine learning options for many years now, in part because data mining is such a key element of how the company operates. Combine that with their efforts to use machine learning in their cloud computing strategy, and the bigger picture becomes clear — machine learning and artificial intelligence could be the next great untapped market for tech companies to venture into.

Artificial intelligence for enterprise applications is a growing market. Some experts even predict for it to hit over US$11-billion by 2023. With the impressive growth of cloud computing, software defined storage, and converged architecture, it’s no wonder companies like Apple and Google want to be industry leaders in an emerging technological landscape. Eventually, we’ll have a winner in this mobile machine learning race, but the real winner will likely be the consumer, who will be able to do even more with their devices than they can today.

Feature image: Insomnia Cured Here via Flickr