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Tesla FSD Beta 10.69 release notes highlight better left turns, smoother driving
Tesla released FSD Beta 10.69 to the first round of testers over the weekend. Read v.10.69’s release notes below to check out the latest improvements.
Stay in your Lanes
- Added a new “deep lane guidance” module to the Vector Lanes neural network which fuses features extracted from the video streams with coarse map data, i.e. lane counts and lane connectivites. This architecture achieves a 44% lower error rate on lane topology compared to the previous model, enabling smoother control before lanes and their connectivities becomes visually apparent. This provides a way to make every Autopilot drive as good as someone driving their own commute, yet in a sufficiently general way that adapts for road changes.
Nothing Like Smooth Driving
- Improved overall driving smoothness, without sacrificing latency, through better modeling of system and actuation latency in trajectory planning. Trajectory planner now independently accounts for latency from steering commands to actual steering actuation, as well as acceleration and brake commands to actuation. This results in a trajectory that is a more accurate model of how the vehicle would drive. This allows better downstream controller tracking and smoothness while also allowing a more accurate response during harsh manevuers.
- Increased smoothness for protected right turns by improving the association of traffic lights with slip lanes vs yield signs with slip lanes. This reduces false slowdowns when there are no relevant objects present and also improves yielding position when they are present.
- Reduced false slowdowns near crosswalks. This was done with improved understanding of pedestrian and bicyclist intent based on their motion.
- Enabled creeping for visibility at any intersection where objects might cross ego’s path, regardless of presence of traffic controls.
- Improved accuracy of stopping position in critical scenarios with crossing objects, by allowing dynamic resolution in trajectory optimization to focus more on areas where finer control is essential.
- Reduced latency when starting from a stop by accounting for lead vehicle jerk.
Chuck’s Left Turn
- Improved unprotected left turns with more appropriate speed profile when approaching and exiting median crossover regions, in the presence of high speed cross traffic (“Chuck Cook style” unprotected left turns). This was done by allowing optimizable initial jerk, to mimic the harsh pedal press by a human, when required to go in front of high speed objects. Also improved lateral profile approaching such safety regions to allow for better pose that aligns well for exiting the region. Finally, improved interaction with objects that are entering or waiting inside the median crossover region with better modeling of their future intent.
Safety is Number 1
- Added control for arbitrary low-speed moving volumes from Occupancy Network. This also enables finer control for more precise object shapes that cannot be easily represented by a cuboid primitive. This required predicting velocity at every 3D voxel. We may now control for slow-moving UFOs.
- Made speed profile more comfortable when creeping for visibility, to allow for smoother stops when protecting for potentially occluded objects.
- Improved speed when entering highway by better handling of upcoming map speed changes, which increases the confidence of merging onto the highway.
- Enabled faster identification of red light runners by evaluating their current kinematic state against their expected braking profile.
Tesla FSD “Brain” Improvements
- Upgraded Occupancy Network to use video instead of images from single time step. This temporal context allows the network to be robust to temporary occlusions and enables prediction of occupancy flow. Also, improved ground truth with semantics-driven outlier rejection, hard example mining, and increasing the dataset size by 2.4x.
- Upgraded to a new two-stage architecture to produce object kinematics (e.g. velocity, acceleration, yaw rate) where network compute is allocated O(objects) instead of O(space). This improved velocity estimates for far away crossing vehicles by 20%, while using one tenth of the compute.
- Improved geometry error of ego-relevant lanes by 34% and crossing lanes by 21% with a full Vector Lanes neural network update. Information bottlenecks in the network architecture were eliminated by increasing the size of the per-camera feature extractors, video modules, internals of the autoregressive decoder, and by adding a hard attention mechanism which greatly improved the fine position of lanes.
- Improved recall of animals by 34% by doubling the size of the auto-labeled training set.
- Increased recall of forking lanes by 36% by having topological tokens participate in the attention operations of the autoregressive decoder and by increasing the loss applied to fork tokens during training.
- Improved velocity error for pedestrians and bicyclists by 17%, especially when ego is making a turn, by improving the onboard trajectory estimation used as input to the neural network.
- Improved recall of object detection, eliminating 26% of missing detections for far away crossing vehicles by tuning the loss function used during training and improving label quality.
- Improved object future path prediction in scenarios with high yaw rate by incorporating yaw rate and lateral motion into the likelihood estimation. This helps with objects turning into or away from ego’s lane, especially in intersections or cut-in scenarios.
Tesla is rolling out FSD Beta v.10.69 in phases, starting with ~1,000 testers over the weekend. Once the update is rolled out for wide release, the price of FSD Beta will increase.
The Teslarati team would appreciate hearing from you. If you have any tips, contact me at maria@teslarati.com or via Twitter @Writer_01001101.
Elon Musk
Tesla Megapack powers $1.1B AI data center project in Brazil
By integrating Tesla’s Megapack systems, the facility will function not only as a major power consumer but also as a grid-supporting asset.
Tesla’s Megapack battery systems will be deployed as part of a 400MW AI data center campus in Uberlândia, Brazil. The initiative is described as one of Latin America’s largest AI infrastructure projects.
The project is being led by RT-One, which confirmed that the facility will integrate Tesla Megapack battery energy storage systems (BESS) as part of a broader industrial alliance that includes Hitachi Energy, Siemens, ABB, HIMOINSA, and Schneider Electric. The project is backed by more than R$6 billion (approximately $1.1 billion) in private capital.
According to RT-One, the data center is designed to operate on 100% renewable energy while also reinforcing regional grid stability.
“Brazil generates abundant energy, particularly from renewable sources such as solar and wind. However, high renewable penetration can create grid stability challenges,” RT-One President Fernando Palamone noted in a post on LinkedIn. “Managing this imbalance is one of the country’s growing infrastructure priorities.”
By integrating Tesla’s Megapack systems, the facility will function not only as a major power consumer but also as a grid-supporting asset.
“The facility will be capable of absorbing excess electricity when supply is high and providing stabilization services when the grid requires additional support. This approach enhances resilience, improves reliability, and contributes to a more efficient use of renewable generation,” Palamone added.
The model mirrors approaches used in energy-intensive regions such as California and Texas, where large battery systems help manage fluctuations tied to renewable energy generation.
The RT-One President recently visited Tesla’s Megafactory in Lathrop, California, where Megapacks are produced, as part of establishing the partnership. He thanked the Tesla team, including Marcel Dall Pai, Nicholas Reale, and Sean Jones, for supporting the collaboration in his LinkedIn post.
Elon Musk
Starlink powers Europe’s first satellite-to-phone service with O2 partnership
The service initially supports text messaging along with apps such as WhatsApp, Facebook Messenger, Google Maps and weather tools.
Starlink is now powering Europe’s first commercial satellite-to-smartphone service, as Virgin Media O2 launches a space-based mobile data offering across the UK.
The new O2 Satellite service uses Starlink’s low-Earth orbit network to connect regular smartphones in areas without terrestrial coverage, expanding O2’s reach from 89% to 95% of Britain’s landmass.
Under the rollout, compatible Samsung devices automatically connect to Starlink satellites when users move beyond traditional mobile coverage, according to Reuters.
The service initially supports text messaging along with apps such as WhatsApp, Facebook Messenger, Google Maps and weather tools. O2 is pricing the add-on at £3 per month.
By leveraging Starlink’s satellite infrastructure, O2 can deliver connectivity in remote and rural regions without building additional ground towers. The move represents another step in Starlink’s push beyond fixed broadband and into direct-to-device mobile services.
Virgin Media O2 chief executive Lutz Schuler shared his thoughts about the Starlink partnership. “By launching O2 Satellite, we’ve become the first operator in Europe to launch a space-based mobile data service that, overnight, has brought new mobile coverage to an area around two-thirds the size of Wales for the first time,” he said.
Satellite-based mobile connectivity is gaining traction globally. In the U.S., T-Mobile has launched a similar satellite-to-cell offering. Meanwhile, Vodafone has conducted satellite video call tests through its partnership with AST SpaceMobile last year.
For Starlink, the O2 agreement highlights how its network is increasingly being integrated into national telecom systems, enabling standard smartphones to connect directly to satellites without specialized hardware.
Elon Musk
Elon Musk’s Starbase, TX included in $84.6 million coastal funding round
The funds mark another step in the state’s ongoing beach restoration and resilience efforts along the Gulf Coast.
Elon Musk’s Starbase, Texas has been included in an $84.6 million coastal funding round announced by the Texas General Land Office (GLO). The funds mark another step in the state’s ongoing beach restoration and resilience efforts along the Gulf Coast.
Texas Land Commissioner Dawn Buckingham confirmed that 14 coastal counties will receive funding through the Coastal Management Program (CMP) Grant Cycle 31 and Coastal Erosion Planning and Response Act (CEPRA) program Cycle 14. Among the Brownsville-area recipients listed was the City of Starbase, which is home to SpaceX’s Starship factory.
“As someone who spent more than a decade living on the Texas coast, ensuring our communities, wildlife, and their habitats are safe and thriving is of utmost importance. I am honored to bring this much-needed funding to our coastal communities for these beneficial projects,” Commissioner Buckingham said in a press release.
“By dedicating this crucial assistance to these impactful projects, the GLO is ensuring our Texas coast will continue to thrive and remain resilient for generations to come.”
The official Starbase account acknowledged the support in a post on X, writing: “Coastal resilience takes teamwork. We appreciate @TXGLO and Commissioner Dawn Buckingham for their continued support of beach restoration projects in Starbase.”
The funding will support a range of coastal initiatives, including beach nourishment, dune restoration, shoreline stabilization, habitat restoration, and water quality improvements.
CMP projects are backed by funding from the National Oceanic and Atmospheric Administration and the Gulf of Mexico Energy Security Act, alongside local partner matches. CEPRA projects focus specifically on reducing coastal erosion and are funded through allocations from the Texas Legislature, the Texas Hotel Occupancy Tax, and GOMESA.
Checks were presented in Corpus Christi and Brownsville to counties, municipalities, universities, and conservation groups. In addition to Starbase, Brownsville-area recipients included Cameron County, the City of South Padre Island, Willacy County, and the Willacy County Navigation District.
Tesla Megapack powers $1.1B AI data center project in Brazil
Starlink powers Europe’s first satellite-to-phone service with O2 partnership
