Company / division: DeepMind
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.
Google’s AI Explosion in One Chart – MIT Technology Review (Mar 27, 2017)
One of the big problems with evaluating which company is ahead or behind in a field like AI is that there are few external signals – companies work on a variety of AI projects behind closed doors in their R&D departments, and many of them only surface when they’re built into products and services they bring to market. Some have suggested using patents as a way to measure leadership, and this article cites publication in scientific journals as another. Certainly, Google’s publishing is a sign that there’s lots of work going on, but it also reflects the (deliberately) quasi-academic culture at DeepMind, its big AI acquisition, while Apple is also slowly moving in this direction with regard to AI specifically. Neither patent filings nor academic papers, however, have a direct connection to using AI to provide better products and services, and that remains very difficult to measure.
I tweaked one part of the headline – it later emerged that Alphabet’s DeepMind subsidiary’s AlphaGo technology was the one beating all comers. This is the best possible kind of publicity for AlphaGo, DeepMind, and Alphabet around AI – creating massive organic buzz before it is even known the company is behind it. Alphabet’s Go experiments have been great advertising in general, but of course the key remains putting this same technology to work in ways that benefit ordinary people in their everyday lives.