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Tesla Daily: Tesla News & Analysis


May 20, 2022

➤ One of Tesla’s largest shareholders advocates for stock buyback, should Tesla do it?
➤ FSD Beta 10.12 release notes leak
➤ Wedbush reduces TSLA price target
➤ California mayor discloses massive Supercharging site
➤ NHTSA investigates Tesla crash in a California
➤ Twitter execs discuss possible acquisition
➤ Bill Gates declines to comment on Tesla again

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FSD 10.12 Release Notes:

• Upgraded decision making framework for unprotected left turns with better modeling of objects' response to ego's actions by adding more features that shape the go/no-go decision. This increases robustness to noisy measurements while being more sticky to decisions within a safety margin. The framework also leverages median safe regions when necessary to maneuver across large turns and accelerating harder through maneuvers when required to safely exit the intersection.
• Improved creeping for visibility using more accurate lane geometry and higher resolution occlusion detection.
• Reduced instances of attempting uncomfortable turns through better integration with object future predictions during lane selection.
• Upgraded planner to rely less on lanes to enable maneuvering smoothly out of restricted space.
• Increased safety of turns with crossing traffic by improving the architecture of the lanes neural network which greatly boosted recall and geometric accuracy of crossing lanes.
• Improved the recall and geometric accuracy of all lane predictions by adding 180k video clips to the training set.
• Reduced traffic control related false slowdowns through better integration with lane structure and improved behavior with respect to yellow lights.
• Improved the geometric accuracy of road edge and line predictions by adding a mixing/coupling layer with the generalized static obstacle network.
• Improved geometric accuracy and understanding of visibility by retraining the generalized static obstacle network with improved data from the autolabeler and by adding 30k more videos clips.
• Improved recall of motorcycles, reduced velocity error of close-by pedestrians and bicyclists, and reduced heading error of pedestrians by adding new sim and autolabeled data to the training set.
• Improved precision of the "is parked" attribute on vehicles by adding 41k clips to the training set. Solved 48% of failure cases captured by our telemetry of 10.11.
• Improved detection recall of far-away crossing objects by regenerating the dataset with improved versions of the neural networks used in the autolabeler which increased data quality.
• Improved offsetting behavior when maneuvering around cars with open doors.
• Improved angular velocity and lane-centric velocity for non-VRU objects by upgrading it into network predicted tasks.
• Improved comfort when lane changing behind vehicles with harsh deceleration by tighter integration between lead vehicles future motion estimate and planned lane change profile.
• Increased reliance on network-predicted acceleration for all moving objects, previously only longitudinally relevant objects.
• Updated nearby vehicle assets with visualization indicating when a vehicle has a door open.
• Improved system frame rate +1.8 frames per second by removing three legacy neural networks.

Executive producer Jeremy Cooke
Executive producer Troy Cherasaro
Executive producer Andre/Maria Kent
Executive producer Jessie Chimni
Executive producer Michael Pastrone
Executive producer Richard Del Maestro
Executive producer John Beans
Music by Evan Schaeffer

Disclosure: Rob Maurer is long TSLA stock & derivatives