Tesla FSD Beta V11.4.1 Release Notes (Tesla FSD Beta V11.4.1 Release Notes, Tesla FSD Beta V11.4.1 Release Notes for employee, Tesla FSD Beta V11.4.1 improvements, Tesla FSD Beta V11.4.1 features,FSD Beta V11.4.1)
Today we get from Twitter that Tesla FSD Beta V11.4.1 Release Notes Beta for employees with the latest 2023.7.5 software update.
Here are the all released notes:
- improved control through turns, and smoothness in general, by improving geometry, curvature, position, type, and topology of lanes, lines, road edges, and restricted space. Among other improvements, the perception of lanes in city streets improved by 36%, forks improved by 44%, merges improved by 27%, and turns improved by 16%, due to a bigger and cleaner training set and updated lane guidance module.
- Added lane-guidance inputs to the Occupancy Network to improve detections of long-range roadway features, resulting in a 16% reduction in false negative median detections
- Improved ego’s assertiveness for crossing pedestrians in cases where ego can easily and safely cross before the pedestrian
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- Tesla is building a new crash Testlabs facility in Texas | Tesla recruiting engineering technicians for new crash test labs
- Tesla Utilize “end-to-end Ai” with v12 features in its full self-driving (FSD)| Tesla end-to-end Ai model
Elon Musk said about the v12 version.
We also learn from Elon that this “end-to-end Ai” model can analyze all steps b/w initial input to final output.
Arguably, v11.4 should be v12.0, as there are so many major improvements. v12 is reserved for when FSD is end-to-end AI, from images into steering, brakes & acceleration out.
Arguably, v11.4 should be v12.0, as there are so many major improvements.— Elon Musk (@elonmusk) May 7, 2023
v12 is reserved for when FSD is end-to-end AI, from images in to steering, brakes & acceleration out.
This is the major change Tesla has done with FSD, This end-to-end Ai uses an artificial neural network with an FSD suite, it helps in learning, analysis, and comparing or it improves with every mile driven, the millions of miles traveled by the owner with FSD can help the system to improve times in terms of behavior.
there are more released notes, go through it
- improved motorbike recall by 8% and increased vehicle detection precision to reduce false positive detections. These models also add more robustness to variance in vision frame-rate
- Reduced interventions caused by other vehicles cutting into ego’s lane by 43%. This was accomplished by creating a framework to probabilistically anticipate objects that may cut into the ego’s lane and proactively offset and/or adjust speed to position the ego optimally for these futures.
- improved cut-in control by reducing lane-centric velocity error by 40-50% for close-by vehicles
- improved recall for object partial lane encroachment by 20%, high yaw-rate cut-in by 40%, and cut-out by 26% by using additional features of the lane-change trajectory to improve supervision
- Reduced highway false slowdowns related to underestimated velocities for faraway objects by adding 68K videos to the training set with improved auto-labeled ground truth
- Smoothed in-lane offsetting for large vehicles by tuning the amount of lateral jerk allowed for the maneuver.
- improved lateral control for upcoming high-curvature merges to bias away from the merging lane.
You can take reference of this video