Scale to launch a mapping product to address the changing needs of its autonomous driving customers – TechCrunch


Solving the various challenges that come up in autonomous driving is an extremely advanced process, however even trying to get began means making certain you’ve got high quality knowledge that’s correct and well-annotated. That’s the place Scale is available in, having recognized early on that the AV business would require annotation of big swaths of knowledge, together with specialised lidar imaging. Now, co-founder and CEO Alex Wang tells me at TC Sessions: Mobility 2021 (Extra Crunch subscription required) that it’s transferring into mapping with a new product that’s coming later this month.

“Our role has continued to evolve,” Wang mentioned, relating to the way it works with its transportation business companions, which embody Toyota amongst many others. “You know, as we work with our customers, and we solved one problem for them around data and annotational data labeling, you know, it turns out they come to us with other problems that we can then help solve as well around data management; we launched a product called Nucleus for that. A lot of our customers are thinking a lot about mapping, and how to deploy with more robust maps. So we’re building a product, I’m going to announce that probably later this month, but we’re helping to address that problem with our customers.”

Despite my prodding, Wang wouldn’t present any specifics, however he did go into extra element about the challenges of mapping, and what’s missing in current maps obtainable to corporations engaged on integrating these with AV methods that embody different alerts, like sensor fusion and vehicle-to-infrastructure parts.

“I think a big question for the overall space has been that historically, the industry has relied very, very heavily on mapping — we relied very, very heavily on very high-quality, high-definition maps,” he mentioned. “The tricky thing about the world is that sometimes these maps are wrong, and how do you deal with that? […] How do you deal with kind of this challenge of robustness, or updates. Even, if you think about it, Google Maps, which is the best mapping infrastructure in the world, by a huge margin, you know they don’t update quickly enough for [human] drivers.”

Wang mentioned that the problem isn’t all that completely different from the one which Scale has been actively fixing for many of its existence, which is that of the knowledge flywheel. With autonomous driving, it’s of utmost significance to have the ability to accumulate and annotate knowledge rapidly and precisely, which ends up in ever higher assortment and annotation of future knowledge, and extra reliability for the assumptions the system is making about its atmosphere.
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“Figuring out how to deal with the real-time nature of how the world changes is one really big, one really big component,” he mentioned. While we nonetheless have to wait to see what precisely Scale has deliberate, it appears protected to assume that it’s all about constructing confidence in maps and mapping accuracy as a key ingredient in no matter they launch.



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