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Tesla FSD

Notes

Tesla FSD

One-line summary: Tesla's vision-only driver-assist and robotaxi stack — supervised Level 2 for consumers, "unsupervised" (remote-supervised) in a handful of geofenced cities.

What it is

Tesla's "Full Self-Driving (Supervised)" is the company's end-to-end neural-network driving system running on either HW3 or AI4 (formerly HW4) in-car compute. v13 introduced a transformer-based "world model" with a ~10-second temporal buffer and voxelized 3D scene representation. v14 (rolling out 2026) pushes further on AI4, with a "v14 Lite" planned for HW3 2026-04-20-autoresearch-tesla-fsd.

The same stack powers Tesla's Robotaxi service — unsupervised (no human in front seat, remote monitoring only) in Austin, Dallas, and Houston as of April 18, 2026 2026-04-20-autoresearch-tesla-fsd.

Why it matters to autonomous-driving

Tesla is the most visible counter-bet to the Waymo/sensor-fusion school: it stakes a full consumer-and-robotaxi business on vision-only perception at scale. Whether that bet works or fails is one of the defining experiments of the field.

Key facts

Strengths (from our perspective)

  • Operates on arbitrary streets rather than an HD-mapped ODD — wider domain than mercedes-drive-pilot.
  • Fleet-learning flywheel: large installed base of camera-equipped vehicles feeding training data.
  • First-person operator assessment from Karpathy (post-tenure, October 2025). andrej-karpathy led Tesla AI / Autopilot 2017–2022. He still rates Tesla's strategy as the more scalable bet relative to lidar-heavy alternatives, with the caveat that he's not fully independent. andrej-karpathy in 2025-10-17-dwarkesh-patel-andrej-karpathy-summoning-ghosts: "I just think people again are sometimes a little bit too naive about some of the progress and I still think there's a huge amount of work and I think Tesla took in my mind a lot more scalable approach and I think the team is doing extremely well... But I do think Tesla is taking the more scalable strategy and it's going to look a lot more like that." Hold as one weighted operator view, not consensus.

Weaknesses (from our perspective)

Open questions

Sources

Related

Referenced by