Word on the street is that Alphabet (née Google) is looking for some revenue from its Automated Vehicle unit, and absent that, might be getting bored with the whole endeavor. Google has gotten bored with things before, and one can imagine it doesn’t view itself as having an infinite pocket to pay for interesting things. There have been reports of this before.
One of the great questions is how long do you tolerate losses in an operation before you cut your losses and convince yourself there will never be gains. Many projects are undertaken (ventures are funded) with great promise.
Yet technological change often happens one bankruptcy at a time, where first movers borrow heavily to invest in new systems with unproven demand. This creates second mover advantages. This is a danger for initial massive investment in self-driving cars in the near future, especially as there doesn’t seem to be any demand from the public currently. (Recognizing that as Henry Ford never said (but almost certainly felt) “If I had asked people what they wanted, they would have said faster horses.”)
In the autonomous vehicle market, suppose someone claims there will be gains in excess of losses, and someone else, with access to a checkbook, believes them. Now we all understand Expected Value depends both on the Potential and the Probability of that Potential being realized. In practice both of those are uncertain and dynamic. Today’s potential in today’s market conditions differ from tomorrow’s. Today’s probabilities also differ from tomorrow’s.* At what point do you recognize the potential as lower than claimed, and the probability as lower still? When, in Bayesian terms, do you update your priors?
In Alphabet/Google’s case, I think the potential of being the first mover is lower because there are now many more people serious about AVs since Google kick-started the latest wave of development of self-driving cars, following upon the DARPA Urban Challenge. In contrast, the likelihood of success might be higher, since there is no more proof-of-concept.
Unless Alphabet imagines itself actually manufacturing cars (probably in a contract facility), one assumes either it hopes to get revenue from (a) more eyeballs on Google-ad-powered screens (phones, dashboard, and especially heads-up displays) in a world of AVs, (b) cutting a licensing deal with manufacturers, or (c) providing mobility services directly a la Uber-type of business.
But in a sense they have been overtaken. For services, all major automakers have now partnered with some other company to explore ride-hailing. Toyota and Volkswagen are the latest to announce this (following historically on similar patterns where automakers invested in rental car companies (e.g. Hertz by GM 1925-53 and Ford 1987-2005, Avis by GM 1989 – 96, Dollar Thrifty by Chrysler 1990-97). Daimler owns car-sharing service company Car2Go and Moovel and is certainly looking at this market. Google rival Apple invested in Chinese hailer Didi.
For autonomous technology, Tesla has cars on the road already.While Tesla Autopilot is not the equivalent of Google cars, as it still requires driver attention, it is also a real product accumulating real experience at an accelerating rate, as shown in the graph, with two orders of magnitude more distance traveled and seemingly fewer incidents per distance traveled (I am going on press-reports of Google and Tesla crashes).
If the logic of machine learning is right, it will get better and better over time. There have apparently yet to be serious crashes with 100 million miles of Autopilot experience (though there have been a few issues, there have also been claims of lives saved), so perhaps this is the right technological trajectory.
This is the incrementalist approach, leaving the steering wheel and brakes facing the driver, which counters the more radical Google approach of removing (almost) all control from the driver, and trusting the machine completely. The risk has always been the transfer, when the car tells the driver to take over if the driver isn’t ready. But if that issue is small compared to the general safety benefit of letting the machine do the steering, accelerating, and braking, it is a risk worth taking.
So will Google close its unit and set its code and data free, let it wither away as staff start up spinoffs like Otto, or sell it outright to a manufacturer if they choose not to pursue it with gusto? Or, perhaps the rush to dominate the initial market for AVs will lead to a unsustainable bubble that hits everybody’s valuation (not just Alphabet’s).
I expect there is value to the unit collectively above and beyond the value of the individuals (though I have no personal knowledge), so one hopes they keep the team together, under their ownership, or another patient patron.
* In more typical infrastructure terms, when someone comes and says the Northstar Line will have a Benefit Cost ratio of 2, but it turns out to have a B/C ratio of 0.15, how long do you keep pouring good money after bad? At what point do you recognize the potential as lower than claimed, and the probability as lower still? Sacramento, for instance, is considering shuttering a disappointing LRT line.
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