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Machine learning powered features will be the main point of differentiation of mobile phones and Google’s prowess in data mining will set Android apart.

A few years ago, hardware distinguished mobile devices. Setting Apple’s Retina display aside, most Android devices and iPhones are functionally equivalent and equally powerful. Then, content became the battleground. App stores raced to cultivate critical masses of applications, movies, books and music. Today, Android, iOS and Kindle Fire have reached the same plateau in these categories. In the next few years, mobile operating systems will use machine learning expertise and its application as points of differentiation and I believe Android will win disproportionate market share because of Google’s superiority in machine learning.

Voice / Siri

Voice recognition and voice commands, like Siri, represent the most salient example of machine learning on a mobile phone. Voice input machine learning problems ingest human speech and output text or trigger actions such as scheduling a meeting or setting an alarm. Successfully implementing this feature over many languages is no small data mining feat. Google developed this feature before Apple acquired Siri and because of its Google Voice transcription service plus the number of voice search queries, it likely has a much larger data set on which to train its models.

Google Now / Notifications

Google’s Now feature, which intelligently predicts information you might need during your day, impressed me most at Google IO. A Jelly Bean powered phone automatically informs you when you should leave to arrive on time for an appointment (including public transportation transit time) and learns that you may want to visit the gym in an hour based on your habits. Digital personal assistants have been a dream for a while. The first versions are finally here. While Apple’s Siri can’t be far behind, Google’s hundreds of millions of GMail users and Google Apps for Enterprise users form a much larger data set than Apple’s or Amazon’s.

Search

Search is the original machine learning problem. Google runs the tables on search for the moment. Clearly, Apple’s move into Maps diminishes Google’s local query share and it invites speculation of Apple delving deeper into search. After all, search query data could inform other features within the OS. But Google’s search queries and data richness are unmatched. Because of the breadth of its search index, Google can build relevance and relationships across web data no other OS vendor can match, save Microsoft.

Content Recommendations

Not to be overlooked, content recommendations in the app and content stores will be important over the long-term. Finding the right content for the right person at the right time set Netflix apart. Despite Apple’s iTunes query and purchase advantage, Apple relies mostly on editorial curation for content recommendation, an approach that fails to personalize shopping. Amazon has an edge with all its existing purchase data and behavioral intelligence from commerce.  Android lags in this area, but given enough handset distribution and even a modestly successful store, Google’s data asset will bloom.

The Foundation of ML

Machine learning’s life blood is data. The more data an algorithm has, the more accurate it becomes. Capturing, aggregating and leveraging this data is the mobile OS battlefield for the next few years. The scale of Google’s machine learning teams eclipse its competition. To supplement their ranks, Apple, Microsoft and Amazon will likely acquire many teams building consumer applications using machine learning. The most valuable ones will have large proprietary and datasets eminently useful for machine learning based features.

The race is on to build the best machine learning enabled mobile personal assistant at all costs. Ultimately, I believe Google’s access to significantly larger data sets, many of them proprietary, will enable superior Android features conquering larger market share.

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12 thoughts on “Android > iOS

  1. I understand your argument, but there’s one assumption in here that breaks down for me — Apple’s lead on the hardware/chip side just feels way too great. I think it will be quite some time before a physical device with sensors to compete against iOS will emerge.

  2. You didn’t talk about the fragmentation. That is the main killer of Android IMO.

  3. The issue with ML is that there is a strong imbalance between your delight with when it tells you something you wanted to hear and the frustration when you hear something that is incorrect or irrelevant to you. If Google can exceed 97% accuracy and relevance, this is a huge game changer. Siri is very far away from this number right now.

  4. First, may I say “thank you” for putting together a great blog. I read it quite frequently.

    Now, wrt your most recent post here, I’m not sure I wholly share your conclusion. I understand your rationale around large data sets and how this contributes greatly to improvements in machine learning; however, the market has indicated that design, user experience, and the ease of use of iOS devices are more important factors.

    An arguable unforeseen factor is the penchant for iOS users to purchase more apps and insist on free apps such Android users. This runs in the same vein as the fragmentation issue, which I would say that you are partially correct in that it is a “developer problem,” but doesn’t this ultimately become a user problem b/c there are fewer options out there?

    In my experience (and imho), app developers really do prefer iOS over Android and until Google, the handset OEMs, and carriers all work to solve this it will continue to be a problem for developers, users, and Google alike. This feeds on itself and will keep Apple in a better position.

    So, I guess I would say that the argument that Android will beat out iOS is predicated on much, much more than just machine learning and data sets.

    • Thanks for the comment. I understand what you mean. My argument deals entirely with the consumer side.

      My point is that there isn’t much hardware and OS differentiation any more. Both iOS and Android have similar content and app libraries. The phones have similar specs and even the UIs are nearly identical.

      There might be a branding difference between having an iPhone and an Android and there might be a bit of a hardware difference, but for most consumers I’d argue the devices are functionally identical.

      The only way to differentiate is now technical skill. Machine learning and data sets create a barrier to entry, one that content libraries, app libraries or hardware can no longer provide to either Apple or Google or Amazon.

      As for developers, fragmentation is a challenge on Android. Payments and revenue are a challenge. But with a much larger user base (whose delta is growing with time), most developers must deploy to Android. Developers will eventually pursue the largest revenue opportunities. For the top developers, Android and iOS offer similar monetizatio (http://techcrunch.com/2012/06/13/the-1-grossing-game-on-android-and-ios-denas-rage-of-bahamut-has-almost-even-revenues-from-both)

      • Gotta love these debates. =)

        Point well taken with respect to specs; however, I would still have to say that I think the market gives iOS a distinct edge wrt design and UI. Users seem to find iPhones / iPads easier to use. At a minimum there is some strange reason that people really love their iOS devices (fyi, to date, I’ve been an Android user) and I’m just attributing that to the UX.

        I’ll also concede that the monetization offerings are similar for developers across both platforms. However, if we look at user behavior across multiple apps (not just the top grossing), iOS users seem to generate more revenue for developers (http://www.businessinsider.com/evernote-a-great-example-of-androids-monetization-problem-2012-6). I think Google will gain ground on Apple, but time will tell.

        Also, I think that the release of the Google Nexus 7 tablet will really provide some insight into whether Google can gain ground on Apple b/c tablet sales will also start playing a larger role in data sets (to go back to your original post).

        Regardless, I appreciate your comments. Thanks!

      • Yes, I’m being a bit hardline here. But I agree. Apple’s design advantage is unquestionable. So is it’s brand and the success of its developer ecosystem.

        Thanks for reading!

  5. Google Now sets a new standard for what people will come to expect from their information services. The way it’s able to bring together such a large set of personal information stored in email, maps, contacts (etc) and present them through a mobile device is something that Google is uniquely positioned to do. Facebook lacks the mobile presence and Apple lacks the personal information and probably some of the ML expertise (I like the way you put it, as having “an approach that fails to personalize” and I think that charge could be applied to many of their products).

    Nowadays when choosing a mobile phone the hardware, carrier, and even OS aren’t the most important considerations. That’s partly due to the minimal differentiation of those things, like you say. I suggest that the most significant choice being made is to align with a set of platform services from one of the leading tech companies of today. All of the companies mentioned above, along with Amazon, are racing to build their own sets of these services for consumers, and they’ve got different backgrounds and strengths.

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