Tesla's robotaxi fleet has been involved in two crashes since July 2025, both happening while remote operators were controlling the vehicles. That's a reminder that even with all the AI hype, we're still far from cars that can handle everything on their own.
The fact that these incidents happened under remote operation is telling. It means Tesla is still relying on human intervention for tricky situations, which is standard practice across the industry but not exactly the fully autonomous future that's been promised.
For anyone following AI progress, this is a useful reality check. Self-driving tech has improved dramatically, but the gap between 'mostly works' and 'works reliably enough to remove the safety net' is massive. The edge cases are what matter.
This matters if you're thinking about how AI handles real-world complexity. Driving is one of those problems that looks simpler than it is. The same challenges show up in other AI applications: handling unexpected situations, maintaining safety when the model encounters something outside its training distribution.
The slow progress here also affects timelines for other autonomous systems. If companies with Tesla's resources are still working through these issues, it suggests we should be realistic about how quickly AI can take over other complex, safety-critical tasks.
