Perched on the edge of a curb, squinting down the length of Market Street in the US city of San Francisco, I find myself twitchily tapping my phone, only to wince as the time ticks away. And up the Market Street rail line rumbles my deliverance: a 1928 wood-panelled tram in green-and-white trim. Oh, the irony: I'm headed to test out one of the city's newest transportation options while creaking down the road on one of its oldest. San Francisco has long been a hub for transportation innovation. It was here that the first cable car system was put into use.

Have you put a real killer application that exploits AI into volume production use? As of last year, only 4 (that's FOUR) percent of 3,182 CIOs world-wide report they've put an AI-related application into production (or planned to do so within the next 12 months.) CIOs don't always know everything going on in the enterprise, but this number most likely isn't off by more than a factor of 2. (And maybe eight percent of enterprises have such an application in production, but 8 percent is probably an overestimate.) On 27 June this year, we published research for our clients on AI Technical Maturity for Enterprise Architects and Technology Innovators. On the face of it, there has been breathtaking progress on AI in the last decade: The science of AI continues to blaze new, highly valuable trails.

The term "self-driving car" might conjure up images of an autonomous four-door sedan, but self-driving vehicles are likely to take many forms, including shapes that have never before been considered for transportation. Consider the Nuro self-driving delivery vehicle, currently slated to begin public tests this fall with the grocery store Kroger. Nuro's self-driving delivery vehicle has space for groceries, but not for passengers.Nuro and Kroger This vehicle was specifically designed to deliver goods on public roads. So it has a chassis and drivetrain appropriate for the street, but is small and efficient, with no space for passengers. On the other end of the spectrum are self-driving shuttles from companies like Navya and May Mobility.

In the past five years, autonomous driving has gone from "maybe possible" to "definitely possible" to "inevitable" to "how did anyone ever think this wasn't inevitable?" Every significant automaker is pursuing the tech, eager to rebrand and rebuild itself as a "mobility provider" before the idea of car ownership goes kaput. Ride-hailing companies like Lyft and Uber are hustling to dismiss the profit-gobbling human drivers who now shuttle their users about. Tech giants like Intel, IBM, and Apple are looking to carve off their slice of the pie as well. Countless hungry startups have materialized to fill niches in a burgeoning ecosystem, focusing on laser sensors, compressing mapping data, and setting up service centers to maintain the vehicles. And cars that drive themselves are now everywhere.

Commentators on AI converge on two goals they believe define the field: (1) to better understand the mind by specifying computational models and (2) to construct computer systems that perform actions traditionally regarded as mental. We should recognize that AI has a third, hidden, more basic aim; that the first two goals are special cases of the third; and that the actual technical substance of AI concerns only this more basic aim. This third aim is to establish new computation-based representational media, media in which human intellect can come to express itself with different clarity and force. This article articulates this proposal by showing how the intellectual activity we label AI can be likened in revealing ways to each of five familiar technologies.