Statements (55)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Company
|
| gptkbp:bfsLayer |
4
|
| gptkbp:bfsParent |
gptkb:Aptiv
|
| gptkbp:acquired |
gptkb:football_club
|
| gptkbp:develops |
Self-driving technology
|
| gptkbp:founded |
gptkb:2016
gptkb:Erik_Branyas gptkb:Karl_Iagnemma |
| gptkbp:has_product |
Autonomous taxi service
|
| gptkbp:headquartered_in |
gptkb:Boston,_Massachusetts
|
| https://www.w3.org/2000/01/rdf-schema#label |
Nu Tonomy
|
| gptkbp:industry |
Automotive
|
| gptkbp:operates_in |
gptkb:Singapore
|
| gptkbp:partnership |
gptkb:Lyft
|
| gptkbp:specializes_in |
Autonomous vehicles
|
| gptkbp:technology |
gptkb:Artificial_Intelligence
gptkb:Sustainability_initiatives Community outreach programs Safety systems Data analytics Autonomous navigation Traffic management systems User interface design Customer relationship management Sensor fusion Simulation tools Control algorithms Investment strategies Data collection methods Public transportation integration Data privacy measures Ethical considerations in AI Market analysis tools User feedback mechanisms User experience research Real-time decision making Cybersecurity protocols Public engagement initiatives Collaboration with research institutions Remote monitoring systems Partnerships with local governments Growth strategies Branding and marketing strategies Partnership development strategies Regulatory compliance strategies Testing and validation processes Vehicle-to-everything (V2 X) communication Business development plans Cloud computing for fleet management Competitive analysis strategies Fleet optimization software Machine learning for driving Mapping and localization Perception systems Pilot programs for testing |