Artificial Intelligence (AI) Industries Interview Smart Cities Technologies

Spatial.ai: Personalizing Automotive Rides Through the Use of Fast Moving Social Data

Spatial.ai: Personalizing Automotive Rides Through the Use of Fast Moving Social Data 29/11/2017

Photo Credit: dolgachov/123RF

This post is part of our Future of Smart Cities series where we interview the leading founders and executives on the front lines of their industry to get a better understanding of what problems the industry is facing, what trends are taking place, and what the future looks like.

The following is an interview we recently had with Lyden Foust, CEO of Spatial.ai.

1. What’s the history of Spatial.ai? Where and how did you begin?

LF: Spatial.ai originated from the question “why with all this rich human data pouring out of cities can we still not understand what an area is like?”.

I worked as an ethnographer studying communities, my partner and CTO Will built software that handled jet engine data from GE. We put our heads together building a tool that could decipher the language of cities.


That was January 2016. We experimented with applications in urban planning, travel, and real estate, but realized fundamentally transportation and mobility affects all of the markets we were considering. So we decided to get at the core of the problem and partner with automotive companies.


By September 2016 we had landed a contract with Ford and have been taking off since.

Today, we have API’s that power the following use cases:

1. Personalized vehicle location questions

2. Urban planning tools to track how communities evolve and change over time

3. Site selection tools to fit retail stores to the right communities.

Ultimately we are building a dashboard of human society to fit cities around humans. A real-life Simcity.

An example of some questions answered by our API:

2. What specific problem does Spatial.ai solve? How do you solve it?

LF: In automotive, we use our location data to power vehicles to answer questions only a local would know using every fast moving social data source imaginable. This allows users to ask questions via voice like “find live jazz music tonight” or “show a coffee shop only locals know about”. Questions that cause personal assistants like Siri to default to internet searches because of the lack of real-time human data.

Further, we personalize the experience by connecting the user’s Facebook page. This way the system can give personalized answers and even give you spots in new towns that are similar to the profile of place that you like. Most importantly, this facilitates building a relationship with the machine, something that we have lost over time with our vehicles, but will be important as move into an autonomous future where trust is the ultimate currency.

Here is a Ford Ranger beating a Tesla at location questions: 

3. What’s the future of transportation?

LF: Beyond the ACES framework (autonomous, connected, electrified, shared) here are my predictions.

Prediction #1: The grid is socially aware. I was coming back from Nashville after viewing the total solar eclipse. It took us four hours to get down there from Cincinnati. It took us 13 hours to get back. Total gridlock for 13 hours. Navigation apps lack social awareness, such as events like the eclipse. They route everyone the fastest way, which creates major load balancing issues. In the future, we will be able to anticipate how social events affect transportation and optimize which type of autonomous vehicles to send where. As a bonus, we can even route people the “most scenic route”, or the “best route for architecture”.

Prediction #2: Cities are going to get bigger, transportation will diversify. Cities will continue to build up and out. Gridlock will get worse. If we don’t solve some of these problems it will quantitatively hold back progress for cities. This is why things like hyperloop, city bikes, tunnels, crowdsourced commutes, and walkable cities are important.

Prediction #3: It is personalized. Autonomy is going to be table stakes. The automotive companies that create a trust relationship between their vehicles and the users that choose to ride in them will win. One way to create trust is for the technology to show it understands what the user needs and remember preferences.

4. What are the top 3 technologies trends you’re seeing in transportation?

Trend #1: Computer vision.

Trend #2: Machine learning.

Trend #3: Lithium batteries.

Bonus:

Trend #4:. Organizational speed. The biggest innovation, in my opinion, is organizational. For the first time startups are tackling the space and are getting funded.  Before the cruise acquisition investors weren't putting money into mobility companies because historically these were big bets that required big capital that wouldn't return for some time. This is massively increasing speed – forcing even automotive companies to move faster.

5. Why is the transportation industry ripe for disruption?

LF: History repeats itself, and we are following a similar pattern to pre-industrial age (late 1800’s). Just like that era, people are moving to cities in droves for work. Just like the era of the internal combustion engine, there is a new technology that has caught up (AI, lidar, computer vision).

Back then, the vehicle was a driving force for new technology. It pioneered roads, lights, radios etc. Today, humans will be a driving force for new technology. As we master our technology (AV’s) we will seek a greater command of the world around us. There are many technologies that will rise up and meet that need, at Spatial we are excited to be one of them.

About Lyden Foust

Lyden Foust is the CEO of Spatial. Before Spatial he was an ethnographic researcher, where he traveled to cities to research how communities move and change over time.

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