Narrative: Google is Ahead in AI
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Narrative: Google is Ahead in AI (Jan 24, 2017)
Written: January 24, 2017
Just over two years ago, I wrote a piece entitled “What is Google?” in which I investigated several different ways of seeing the company and the unifying theme which brought all its disparate activities together. This was before the Alphabet restructuring, and so at the time Google encapsulated everything from the search engine to YouTube, from Nest to self-driving cars, and from robotics to healthcare. The one unifying theme, I argued, wasn’t advertising as a business model, or search or data, but machine learning and artificial intelligence.
Since that time, we’ve seen Google (and the broader Alphabet) double down on AI as a differentiator – it frequently comes up in its developer events and product and service launches, and the company has engaged in frequent demonstrations of its AI prowess, not least its experiments with the board game Go. The perception has emerged that Google/Alphabet is ahead of all of its competitors in the AI field, and that this will be a major differentiator and advantage going forward.
The problem here is that it’s almost impossible to gauge companies’ AI chops objectively – there are measures like patents held, but that’s an oversimplification, as are numbers of employees working on AI and other similar measures. Those metrics all get at effort put in, rather than real benefits users get out on the other end. A big part of the problem with the current obsession with AI in consumer tech is that companies are spending too much time telling, and too little time showing.
In other words, these companies talk lots about their AI capabilities, but don’t do enough to demonstrate real consumer benefit deriving from those capabilities, and Google is perhaps guiltier than most of this. Its Go experiments are enormously impressive, but it’s turning those skills into something that improves products and services real people use every day that’s the key. A recent counterexample is Google’s RAISR, which helps reduce file sizes for photos while increasing resolution using AI.
Google is in this sense the opposite of Apple (see the Apple is Behind in AI narrative), which until 2016 tended never to talk about AI or machine learning, and instead focused solely on features and benefits. In the process, it rather sold itself short, and it began to change its strategy this past year, referring more explicitly to those technologies by name in its keynotes. Microsoft and Facebook are also making massive investments in AI and machine learning (Microsoft actually comes out on top in that patent comparison), and each of these companies has made meaningful progress.
At the end of the day, it’s impossible to say whether Google is really “ahead” in any meaningful way in AI – it’s certainly a core competency for the company and it’s absolutely one of the leaders in the field, but Microsoft and Facebook are certainly competitive, and it’s arguable that in terms of delivering real end user benefit Apple is too.
Quartz reports that Alphabet’s DeepMind subsidiary, which is still registered as a separate private company in the UK and therefore has to report its own financials, lost $162 million in 2016, on revenues of just $40 million, all of which came from Google. It’s a quirk of accounting that DeepMind is still reporting as a separate company, but it gives some insight into the cost of running such a business, which is focused on cutting-edge AI work, much of which is not ready for direct monetization in revenue generating products. Given that Alphabet as a whole spent over $15 billion on Research and Development in the past year, this is a tiny fraction of the total, and an operation the company can easily afford to keep going along these lines. Much of the losses, incidentally, stem from the $137 million the company spent on staff and related costs, of which I would guess a big chunk is stock-based compensation, which runs at $2 billion per quarter for Alphabet as a whole and $100-150 million per quarter in the Other Bets segment. And of course there are big chunks of Google itself working on AI as it relates to specific products too, so this is far from the scale of Alphabet’s overall investment in AI, which is increasingly filtered into everything Google does.