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Tesla FSD Beta 10.69 release notes highlight better left turns, smoother driving

(Credit: Tesla)

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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.

Maria--aka "M"-- is an experienced writer and book editor. She's written about several topics including health, tech, and politics. As a book editor, she's worked with authors who write Sci-Fi, Romance, and Dark Fantasy. M loves hearing from TESLARATI readers. If you have any tips or article ideas, contact her at maria@teslarati.com or via X, @Writer_01001101.

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Tesla stuns with another FSD approval in Europe, its second in two days

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Tesla has stunned by gaining yet another approval for its Full Self-Driving suite in Europe, its second in two days and its fifth overall.

Belgium will be the latest country to allow Tesla owners to utilize FSD on public roads in Europe, joining a quickly growing list that started with the Netherlands, Lithuania, and Estonia.

On Tuesday, Denmark announced its approval of the FSD suite, which has now been followed by Belgium just one day later.

The country’s Minister of Mobility, Annick De Ridder, announced the approval on her X account, stating that she had just signed the approval of Tesla FSD. It now goes to the country’s homologation department for the last step of the approval process.

The Belgian approval is one of mighty importance because it truly shows how quickly countries in Europe could greenlight the FSD suite consecutively. Approvals are already coming in relatively quickly, which is a great sign.

Perhaps the next big development that could come from FSD approvals in Europe is an approval from a country like England, Italy, France, Spain, or Germany. It would be something to see how FSD would perform in a major European metro, such as London, Barcelona, Madrid, Paris, Rome, or Berlin.

Full Self-Driving does an excellent job of roaming around major U.S. cities like New York and Los Angeles, but other high-profile international cities of significance would truly mark a line in the sand for Tesla, which can simply enable any vehicle in its customer-owned fleet to run FSD with the correct approvals.

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Elon Musk

SpaceX’s Elon Musk relieves worries about orbital data centers

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Rendering of Elon Musk overlooking a Starship fleet (Credit: Grok)
Rendering of Elon Musk overlooking a Starship fleet (Credit: Grok)

SpaceX CEO Elon Musk recently confronted worries about orbital data centers and launching satellites in mass quantities in space, as some voiced concerns about crowding.

Musk’s SpaceX plans to combat the issue of needing data centers by launching them into space instead of taking up valuable real estate on Earth. It has been a major point of SpaceX’s future, including its looming IPO, which could be the largest ever.

In a recent interview filmed at SpaceX’s Starlink terminal factory in Bastrop, Texas, Elon Musk directly addressed concerns that deploying large numbers of AI satellites for orbital data centers could crowd Earth’s orbit. His message was straightforward and reassuring: space is vast beyond human intuition.

“Space is really big,” Musk said. “It’s not like space is gonna get crowded. Space is enormous. If you actually look at it relative to the Earth, the satellites are so tiny you can’t even see them.” He emphasized that even zooming in makes a satellite appear large, but from a planetary perspective, they are minuscule specks.

Musk pointed to SpaceX’s real-world experience operating roughly 10,000 Starlink satellites as evidence that large constellations can be managed safely. “We’ve got a pretty good idea of how to operate just really large constellations and do it safely,” he noted. SpaceX remains the only operator with meaningful experience at this scale, giving the company unique insight into tight orbital packing without compromising safety

The discussion highlighted SpaceX’s plans for “AI1” satellites—essentially orbiting racks of AI compute powered by massive solar arrays and cooled via radiative panels in space’s vacuum.

These satellites leverage proven Starlink V3 technology, making them simpler to design than communications satellites. A first-generation unit targets around 150 kW peak power, with a 70-meter wingspan for solar panels and radiators. Laser links will connect them to each other and the Starlink network, delivering low-latency access (on the order of a few milliseconds from low-Earth orbit).

FCC accepts SpaceX filing for 1 million orbital data center plan

Musk framed orbital data centers as a practical solution to Earth’s constraints on AI growth. Ground-based facilities face power shortages, water demands for cooling, and grid limitations. In space, constant sunlight (no day-night cycle), vacuum radiative cooling, and abundant solar energy offer clear advantages.

Production will ramp up at an expanded “Gigasat” factory in Bastrop, with solar manufacturing already underway and full AI satellite output expected at reasonable volume by the end of 2027. Starship’s rapid, high-volume launch capability, aiming for multiple flights per hour, will make massive deployment feasible.

Critics sometimes raise risks like space debris or Kessler syndrome, but Musk’s response underscores scale: even a million satellites would represent an imperceptible fraction of available orbital volume when viewed against Earth’s size. SpaceX’s automated collision avoidance and deorbiting designs for Starlink further mitigate concerns.

This vision ties into broader ambitions. Musk sees orbital AI compute as a step toward harnessing more of the Sun’s energy, advancing humanity on the Kardashev scale from a Type 0 civilization toward Type 1 and eventually Type 2. By moving power-hungry data centers off-planet, SpaceX aims to unlock orders-of-magnitude more compute while preserving Earth’s resources.

Musk’s comments should ease public anxiety. With proven operational expertise, incremental engineering, and the immensity of space itself, orbital data centers represent not overcrowding, but smart expansion into the final frontier.

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Investor's Corner

Tesla Full Self-Driving hits Level 4? One analyst says yes

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Credit: Tesla

Tesla Full Self-Driving (Supervised) is currently listed as a Level 2 suite in terms of its passenger cars. As its Robotaxi platform continues to move quickly, it has been recognized as a Level 4 ride-sharing program by the State of Texas, as Tesla recently self-certified itself.

However, a Wall Street analyst is arguing that Tesla (NASDAQ: TSLA) has effectively achieved Level 4 autonomy in most conditions in all of its vehicles, drawing on personal experience and data released by the company.

Alex Potter of Piper Sandler said in a note to investors on Wednesday that “Tesla has solved the self-driving puzzle,” pointing to decisions to offer insurance discounts for FSD-enabled policies as a signal of confidence, which is backed up by stellar safety records compared to human driving.

Investing.com initially reported on Potter’s new note.

Additionally, Potter looks at the recent start of Cybercab production at Giga Texas as a potential indication that Tesla is ready to offer some level of unsupervised driving at least in the near future. The Cybercab has no steering wheel or pedals, completely eliminating the ability for human input.

He also sees Tesla’s allocation of “several hundred million USD (if not $1B+)” as confidence internally, seeing as it would be tough to set aside that amount of capital toward a project that the company does not see as relatively near-term.

Forward thinking, especially as Cybercab has no human controls, it would make sense that Tesla is at least close to self-driving. How close is another question.

Tesla has routinely teased that unsupervised FSD is close, but there are still a lot of things it feels as if the company has to roll out some more capability, including unsupervised parking features, known as “Banish,” better operation with regional self-driving performance, and other improvements.

That is not to say that Tesla FSD is super impressive already. It has already completed coast-to-coast drives across the United States and Canada, it routinely takes the stress out of driving for most people, and it has proven through Tesla Safety Reports that it is safer and involved in accidents less frequently than humans.

Even Potter believes it is capable, as he used it to go from Missoula, Montana, to Minneapolis, Minnesota, back in April.

“There’s no substitute for personal experience,” he wrote.

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