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inDrive, Pony.ai, and Nvidia Target 2027 Robotaxi Tests in Kazakhstan

Robotaxis Autonomous Vehicles Pony.ai Nvidia inDrive Kazakhstan Hyperion
October 23, 2026
Source: TechCrunch AI

This summary and analysis were generated by AI from the original article at TechCrunch AI and may contain errors (how Viqus works). Read the source for full details.

Viqus Verdict Logo Viqus Verdict Logo 7
Global Scale-Up of Physical AI
Media Hype 5/10
Real Impact 7/10

Article Summary

inDrive, a ride-hailing company, has formed an MoU with Pony.ai and Nvidia to test robotaxis in Astana, Kazakhstan, beginning in the first half of 2027. The plan involves Pony.ai supplying its Gen-7 robotaxis, which inDrive will integrate into its platform, while Nvidia will provide the necessary AI technology, including its Hyperion platform. This move highlights the global, capital-light approach to autonomous mobility, contrasting with moves by competitors like Uber. The collaboration is strategically timed with Nvidia's visit to Kazakhstan and aligns with the nation's own plans to launch autonomous services in 2027, making Astana a key testing ground for harsh winter conditions.

Key Points

  • inDrive, Pony.ai, and Nvidia have partnered to test robotaxis in Astana, Kazakhstan, starting in the first half of 2027.
  • Nvidia will supply core AI technology, while the partnership emphasizes a capital-light model for expanding autonomous services.
  • The move reflects a broader, international push into robotaxi markets, including potential future deployments in Saudi Arabia.

Why It Matters

This announcement is significant because it demonstrates the rapid, multi-national commercialization of autonomous vehicle technology, moving beyond initial US/China testing grounds. The focus on emerging markets like Kazakhstan, and the inclusion of Nvidia's cost-saving platforms, suggests a maturing industry focus on scalable, cost-effective deployment rather than just technological breakthroughs. It confirms that global ride-hailing players are aggressively pursuing physical AI infrastructure across diverse regulatory environments.


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