General Motors' (GM 2.40%) Cruise is collecting data for its self-driving cars at any cost, using more sensors on its vehicles than Tesla and mapping real city streets rather than using simulations. In this Backstage Pass clip from "The AI/ML Show" recorded on Jan. 12, Motley Fool contributor Jamie Louko shares how these competitive differences could set Cruise up for incredible success.
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Jamie Louko: Cruise is a subsidiary of GM that was acquired in 2016. But for the most part GM just lets Cruise run itself, which I really like. I like the management team that Cruise had as of late. When it comes to old tech cars like GM, I'm pretty happy when we were keeping innovative leaders at the forefront of this, it's estimated to be worth $30 billion. It's really growing despite not rolling out any cars yet. It's still waiting on a couple of regulatory things, but I can get into that later.
It's going to be using GM basically as just a production and financing partner. Once it gets 10 years out, it's really going to be using GM to build Cruise's software into cars and things like that. Pre-revenue right now that could change in 2022. I'll get into all of that later.
But how does Cruise use AI? It really focuses on employing as many sensors as possible. That is really the key here. Like Tesla it is not really focused on scale right now. It's completely focused on performance. It wants to be the best autonomous vehicle company. Then it will figure out about how it can lower that price later. Right now, it's only focused on performance. You can see that with some of these things, they're using 40 sensors. I think, Trevor, correct me if I'm wrong, I think you said Tesla had eight, I think.
Trevor Jennewine: Yeah. Eight overlapping external cameras plus 12 ultrasonic sensors.
Jamie Louko: They're using 40. That could show some scale about how really they care about collecting this data at any cost. They are also using mapping simulation, LiDAR, some audio inputs and predictive modeling to see where things in front of it are going to be moving and it measures within centimeters and like Trevor said in his presentation, it has data on 2 two million miles driven. But a key part that I really like is that it's in San Francisco, it's mostly real data instead of just simulated data.