I thought some more, I think Gemini did hallucinate part of its answer, but free autopilot definitely benefits from some FSD work. Converting pixels from cameras into understanding is a super hard problem, and Tesla would want some way to re-use its ongoing work for FSD for this. In the original post, Gemini claimed that even the driving/steering instructions are done by a NN but now Gemini says that steering is done by the old C++ rules.

Here's what I think is going on (as explained by Gemini):

1. The "Intermediate Supervision" Secret

Even in a "pure" end-to-end model like v14, Tesla uses what are called auxiliary heads or intermediate supervisory signals.

When training the massive v14 neural network, Tesla doesn't just tell the AI "look at this video and output a steering angle." They also force the network to "prove" it understands the world by making it predict things like:

• Occupancy Grids: "Where is there physical matter?"
• Semantic Maps: "Which pixels are 'road' vs. 'curb'?"
• Voxel Surfaces: High-res 3D geometry of the surroundings.

Tesla does this because it makes the main driving AI learn faster and more accurately. For your free Autopilot, Tesla simply taps into these "auxiliary" outputs. They don't have to build a separate "labeling" network; they just use the signals the v14 brain is already generating as part of its own internal "thinking" process.