Jump to content

User:104gli/DeepScale

From Wikipedia, the free encyclopedia
DeepScale, Inc.
Type of site
Privately held company
HeadquartersMountain View, CA
Founder(s)
CEOForrest Iandola
URLhttp://deepscale.ai

DeepScale, Inc. is a privately held, U.S. based technology company headquartered in Mountain View, CA.[1] DeepScale develops perceptual system technologies for automated vehicles.

History[edit]

DeepScale was co-founded by Dr. Forrest Iandola and Prof. Kurt Keutzer in September 2015.[2] DeepScale is focused on bringing efficient deep neural networks to Advanced Driver Assistance Systems and Autonomous Vehicles.[1] In 2018, DeepScale raised US $15 Million in Series A funding.[3][4] The funding round was led by two funds: Point72, which is the personal fund of billionaire investor Steven A. Cohen, and next47, which is a billion-dollar venture fund backed by Siemens.[5][6] In 2018, DeepScale announced strategic partnerships with automotive suppliers including Visteon and Hella Aglaia Mobile Vision GmbH.[7][8]

Technology[edit]

Prior to the founding of DeepScale, Forrest Iandola and Kurt Keutzer worked together at University of California, Berkeley, on making deep neural networks (DNNs) more efficient.[9][10] In 2016, shortly after the founding of DeepScale, Iandola, Keutzer, and their collaborators released SqueezeNet, which is a small and energy-efficient DNN.[11][12] By developing smaller DNNs, DeepScale has been able to run deep learning on scaled-down processing hardware such as smartphones and automotive-grade chips.[1][11][13] In 2018, DeepScale said that its engineering team had moved beyond SqueezeNet and that it had developed even faster and more accurate DNNs for use in commercial products.[14]

Product[edit]

DeepScale develops perceptual system software which uses deep neural networks to enable cars to interpret their environment. The software is designed for integration into an open platform, where a wide range of sensors and processors can be used.[7] DeepScale's software is able to interpret data from sensors including cameras, radar, and lidar.[1] The software is able to run on a variety of processors, ranging from NVIDIA GPUs to smaller ARM-based processing chips that are designed specifically for the automotive market.[7][14]

In January 2019, DeepScale launched an automotive perception software product called Carver. Carver uses deep neural networks to perform object detection, lane identification, and drivable area identification. To accomplish this, Carver uses three neural networks which run in parallel. While running in real-time, these three networks perform a total of 0.6 tera-operations per second.[15] As a point of reference, 0.6 tera-ops/sec is only 2 percent of the 30 tera-ops/sec that the NVIDIA Jetson Xavier embedded computing system is rated to perform.[16]

Awards and recognition[edit]

In December 2016, VentureBeat named DeepScale one of the "15 interesting startups to watch in 2017," alongside computer vision company Clarifai and augmented reality company Magic Leap.[17] In December 2018, the AI Time Journal listed DeepScale as one of the "Top 25 Artificial Intelligence Companies of 2018."[18][19] In February 2019, DeepScale was featured alongside SenseTime and Graphcore in the CB Insights AI 100, which consists of "the most promising 100 AI startups working across the artificial intelligence value chain, from hardware and data infrastructure to industrial applications."[20]

References[edit]

  1. ^ a b c d Kolodny, Lora (2017-03-21). "DeepScale raises $3 million for perception AI to make self-driving cars safe". TechCrunch. Retrieved 2018-04-07.
  2. ^ "DeepScale". Crunchbase. Retrieved 2018-04-07.
  3. ^ "DeepScale attracts $15M investment to advance automated vehicle perception". Safe Car News. 2018-04-04. Retrieved 2018-04-07.
  4. ^ Marinova, Polina (2018-04-04). "Term Sheet". Fortune. Retrieved 2018-05-22.
  5. ^ Schott, Paul (2018-04-04). "Point72 invests in artificial-intelligence firm". Stamford Advocate. Retrieved 2018-04-07.
  6. ^ Orlowski, Ralph (2016-06-28). "Siemens Will Put $1.1 Billion Into New Startups Unit". Fortune. Retrieved 2018-04-07.
  7. ^ a b c Yoshida, Junko (2018-01-09). "Visteon Works with DNN Vanguard DeepScale". EE Times. Retrieved 2018-04-07.
  8. ^ Yoshida, Junko (2018-04-03). "Are We Short of Deep Learning Experts?". EE Times. Retrieved 2018-04-07.
  9. ^ Keutzer, Kurt. "Faculty Webpage". UC Berkeley. Retrieved 2018-05-22.
  10. ^ Keutzer, Kurt. "Students". UC Berkeley. Retrieved 2018-05-22.
  11. ^ a b Yoshida, Junko (2017-09-21). "DeepScale on Robo-Car: Fuse Raw Data". EE Times. Retrieved 2018-05-22.
  12. ^ Iandola, Forrest N; Han, Song; Moskewicz, Matthew W; Ashraf, Khalid; Dally, William J; Keutzer, Kurt (2016). "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size". arXiv:1602.07360 [cs.CV].
  13. ^ Shazar, Jon (2018-04-05). "Steve Cohen Buys The Dip In Self-Driving Cars". Dealbreaker. Retrieved 2018-05-22.
  14. ^ a b "How to become a Full-Stack Deep Learning Engineer (time: 51:30)". Silicon Valley Deep Learning Group. Retrieved 2018-05-22.
  15. ^ Landen, Ben (2019-01-25). "DeepScale Announces Carver21: Modular Deep Learning Perception Software for Driver-Assistance". DeepScale Blog. Retrieved 2019-02-04.
  16. ^ NVIDIA, Corporation (2018-06-03). "Next-Gen Robotic Systems to Be Enabled by Jetson Xavier Computer and Isaac Robotics Software". NVIDIA. Retrieved 2019-02-04.
  17. ^ Yueng, Ken (2016-12-29). "15 interesting startups to watch in 2017". VentureBeat. Retrieved 2019-04-24.
  18. ^ "TOP 25 Artificial Intelligence Companies 2018". AI Time Journal. 2018-12-18. Retrieved 2019-06-06.
  19. ^ "Interview with Forrest Iandola, CEO and Co-Founder of DeepScale". AI Time Journal. 2019-03-18. Retrieved 2019-04-24.
  20. ^ "AI 100: The Artificial Intelligence Startups Redefining Industries". CB Insights. 2019-02-06. Retrieved 2019-04-24.
Retrieved from "https://en.wikipedia.org/w/index.php?title=User:104gli/DeepScale&oldid=1092463824"