Home Startups AI Startup DeepScale Raises $15M to Develop Automated Vehicle Perception

AI Startup DeepScale Raises $15M to Develop Automated Vehicle Perception

For the successful development of an autonomous vehicle, perception system design is a crucial step that ought not to be left out.

Autonomous cars mainly utilize sensor technologies including cameras, RADARs, and LiDARs in a bid to acquire human-level perception.

Aside from such technologies, these cars need to be fitted with top-of-the-line AV perception technology.

DeepScale prides itself as an industry leader in developing efficient deep learning perception software for mass-produced automated cars.

Recently, the company revealed that it raised $15M in a Series A round of financing led by both next47 and Point72.

Founded by Kurt Keutzer and Forrest Landola in 2015, DeepScale creates perceptual systems for both autonomous vehicles and semi-autonomous ones.

It assists car manufacturers in using industry-approved low-wattage processors to power a perception that is more accurate.

Mapping, sensors, control systems, planning, and perception (often referred to as computer vision) allows vehicles to make sense of events happening in their surroundings in real-time.

Currently, DeepScale is utilizing efficient deep neural networks on low-cost and automotive-quality processors and sensors to change the precision of perception systems.

These systems classify and interpret sensor data in real-time. As such, DeepScale is delivering autonomous driving and driver-assistance to mass-produced cars at different prices.

According to Forrest Landola, the CEO and co-founder of DeepScale, one of the company’s main objectives include the drastic reduction of the number of injuries and deaths on the road.

The recent Series A financing will help DeepScale in empowering its engineering team to continue making groundbreaking innovations in automated driving safety.

It will also assist the company in luring the brightest talent to revolutionize the future of transportation.

Forrest Landola, the chief executive officer and co-founder of DeepScale, boasts a doctorate from UC Berkeley, working on computer vision systems and deep neural networks (DNN).

While working together with his faculty advisor, currently DeepScale’s co-founder Kurt Keutzer, Forrest’s progress inefficient implementations and scalable training of DNN led to the inception of DeepScale.

Sri Chandrasekar from Point72 said that they have been following Forrest Landola’s research regarding efficient deep learning for several years.

In fact, he added that Forrest’s inventions including small DNN dubbed as SqueezeNet have already become a game-changer, especially for integrating deep learning into smartphones.

Point72 quickly joined DeepScale’s investor bandwagon upon hearing that Forrest had created a company to place small DNNs into mass-produced vehicles.

TJ Rylander, next47’s partner, said that DeepScale has been introducing advancements and unique expertise in DNN design to the automotive space.

As such, he expressed next47’s excitement due to the possibility of autonomous technology that can change transportation markets.

The team at DeepScale is currently expediting the commercialization of not only today’s driver assistance systems but also tomorrow’s self-driving cars.

DeepScale boasts numerous strategic partnerships with OEMs, semiconductor suppliers, and Tier 1 suppliers to deliver automated driving perception solutions such as HELLA-Aglaia Mobile Vision Gmbh.

HELLA’s managing director, Kay Talmi said that DeepScale’s expertise in efficient deep learning networks was an ideal match for the company’s target markets and automotive applications.

Source TechStartups

Subscribe to our newsletter

Signup today for free and be the first to get notified on the latest news and insights on artificial intelligence

KC Cheung
KC Cheung
KC Cheung has over 18 years experience in the technology industry including media, payments, and software and has a keen interest in artificial intelligence, machine learning, deep learning, neural networks and its applications in business. Over the years he has worked with some of the leading technology companies, building and growing dynamic teams in a fast moving international environment.
- Advertisment -


AI Model Development isn’t the End; it’s the Beginning

AI model development isn’t the end; it’s the beginning. Like children, successful models need continuous nurturing and monitoring throughout their lifecycle. Parenting is exhilarating and, if...