“STRIKES: CONSIDER CARPOOLING” is a message that motorists in the Paris region could read on overhead signs on the A86 highway during walk-outs by railroad workers in the spring. Most likely, few of them connected the emergence of this new transport solution to the possibilities offered by artificial intelligence (AI). And yet AI is one of the technological building blocks used by Karos, the top court-voiturage™ (short-carpooling) app in the Paris region, to organize the liquidity of their marketplace.

AI — the ambitious goal of which is to create cognitive processes comparable to those of human beings — was developed as a specific field of research in the middle of the 20th century; however, it is only now that its promise is being realized as an everyday reality.

What is behind the recent surge of this technology and what specific prospects does AI offer for mobility?

An alignment of the planets is ushering in a new era for artificial intelligence

After various bouts of hype and disillusionment over the past 60 years, it appears that the time for mainstream, economically viable AI-based applications has come. This myriad of uses is the result of an alignment of the technological planets, including:

1. Algorithms which have constantly improved since 1950 and become increasingly widespread
2. The huge increase in the amount of data available: some of this data is produced by connected devices, the number of which will soar from 8 billion in 2012 to 50 billion by 2020
3. The significant increase in calculation and storage capacities: today’s smartphone has 1,000 times more computing power than NASA had to guide an Apollo mission!

“Data is the new source code”

With the implementation of AI, the days of programming machines appears to be over: let’s hear it for training machines! As input for machine learning, data therefore becomes the key ingredient.

GAFA and other BATX called it right when they made data collection and enhancement the cornerstone of their strategy, as did, even more so, the contributors to the Villani report in insisting on the need to organize the sharing and pooling of sector data to counteract the dominance of web giants.

If the battle over the massive collection of data is being played out among the giants, startups using AI as a technological building block are, for their part, concentrating on data preparation, uses and solutions and drawing the outlines of more sustainable mobility based on a simple equation

The Villani report on artificial intelligence published in March highlights three promising areas of application of AI: “technological developments and the expectations of the ecosystems are concentrated in three key markets: the development of self-driving vehicles, sustainable — particularly electric — forms of transport, and the emergence and interconnection of new mobility solutions to reduce traffic density in certain segments.”

The innovative products and services developed by startups illustrate the way in which these hopes are gradually becoming a reality.

For example, in the area of self-driving vehicles — which we agree must be shared in order to be sustainable — some startups such as RealSynth (D) and Cognata (IL) are developing solutions to virtually train artificial intelligence. The goal is to cover the maximum number of driving scenarios by saving millions of kilometers driven and to bring self-driving vehicles to market more quickly.

While DCbrain (F) and its Israeli counterpart Optiways (IL) implement their AI-based solution to optimize logistical flows, Karos (F) and Padam (F) are developing on-demand carpooling and transport as solutions for inadequate or limited mass transit.

AI can also be a good way to prepare cities and operators for the arrival of electric vehicles (fleets or individually owned). For instance, Cosmo Tech, a startup specializing in augmented intelligence, is gearing up to use its know-how to optimize recharging infrastructures and strategies.

Lastly, to take full advantage of the prospects offered by AI, a data cleanup and structuring policy is necessary. This is precisely the value of the solutions offered by Element Analytics (US) and Tamr (US).

* verbatim statement made by Nvidia’s CEO in March 2018 at the GPU developers conference