Applied Intuition
 | |
| Type of business | Private |
|---|---|
| Founded | 2017 |
| Headquarters | Silicon Valley, California, U.S. |
| Area served | Worldwide |
| Founder(s) | Qasar Younis Peter Ludwig |
| Key people | Qasar Younis (CEO) Peter Ludwig (CTO) |
| Industry | Computer software |
| URL | www |
| Current status | Active |
Applied Intuition is a technology company providing simulation and infrastructure tooling for autonomous vehicle development.[1] The company is based in Silicon Valley, California, United States, with offices in Detroit, Los Angeles, Tokyo, Seoul, and Munich.[1][2][3] The company's simulation software is used to test how autonomous vehicles would respond to a variety of conditions and scenarios in a virtual world, without any of the dangers present in the real world.[4] The software can also be used to run a high volume of scenarios, allowing quicker development at a lower cost.[2]
History
Applied Intuition was founded by Qasar Younis and Peter Ludwig in 2017.[5] Their employees include former employees from technology companies and automotive OEMs such as Waymo, Tesla, and Apple.[6]
In 2018, Applied Intuition announced a Series A investment of $11.5 million from venture capital firms including Andreessen Horowitz, Lux Capital, and Floodgate.[7] In 2019, the company announced a $40 million Series B investment from General Catalyst, Kleiner Perkins, Microsoft's M12, Sozo Ventures, and La Famiglia, as well as the aforementioned Series A investors.[8] In 2020, Applied announced a $125 million Series C round from Lux Capital, Andreessen Horowitz, and General Catalyst.[1]
Applied Intuition's customers include global automotive OEMs such as Toyota and Scania AB and autonomous vehicle technology companies.[1][2][9][10] Applied Intuition also plays in industries such as freight & trucking, delivery robots, defense, mining, agriculture, construction, autonomous mobile robots, and aviation.[2][11]
Products & Services
Applied Intuition develops simulation software to test the safety, comfort, and performance of autonomous vehicles. Their software allows autonomous driving companies to test their algorithms in scenarios with varying conditions (e.g., traffic, weather, and road conditions) before the software is deployed to the real world.[1] The software is used to analyze data and algorithms used in autonomous cars, vans, and delivery trucks that handle perception, prediction, planning, and vehicle control.[12]
References
- ^ a b c d e Konrad, Alex. "Applied Intuition Reaches $1.25 Billion Valuation In New Funding For Its Autonomous Vehicle Testing Software". Forbes. Retrieved 1 December 2020.
- ^ a b c d "倉庫・工場でも自動運転 仮想試験の米新興、日本進出へ". 日本経済新聞 (in Japanese). 2020-11-20. Retrieved 2020-12-23.
- ^ "Qasar Younis: Dieser Gründer will autonomes Fahren schneller möglich machen". www.handelsblatt.com (in German). Retrieved 2020-12-23.
- ^ "How Self-Driving Cars Can Get Past the Learning Permit Stage, Without Any Risk". Bloomberg.com. 2018-09-12. Retrieved 2020-12-22.
- ^ "Applied Intuition - Crunchbase Company Profile & Funding". Crunchbase. Retrieved 2020-12-01.
- ^ Siddiqui, Faiz (2019-11-11). "What self-driving cars can't recognize may be a matter of life and death". Washington Post.
{{cite web}}: CS1 maint: url-status (link) - ^ "Applied Intuition raises $40 million for autonomous vehicle simulation tools". VentureBeat. 2019-09-12. Retrieved 2020-12-01.
- ^ Geron, Tomio (2019-09-12). "Applied Intuition, Whose Software Tests Self-Driving Cars, Grabs $40 Million". Wall Street Journal. ISSN 0099-9660. Retrieved 2020-12-01.
- ^ "An Autonomous Transport Venture Client Partnership, One Year On". Combient Foundry. 2020-06-26. Retrieved 2020-12-01.
- ^ "Driverless vehicles in the age of the novel coronavirus". TechCrunch. Retrieved 2020-12-01.
- ^ "Applied Intuition raises Series C funding for autonomous vehicle simulation". The Robot Report. 2020-10-22. Retrieved 2020-12-22.
{{cite web}}: CS1 maint: url-status (link) - ^ Loten, Angus (2020-02-20). "More Manufacturers Bet on Simulation Software". Wall Street Journal. ISSN 0099-9660. Retrieved 2020-12-01.