News
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
Celebrating SpaceX’s Falcon Heavy Tesla Roadster launch, seven years later (Op-Ed)
Seven years later, the question is no longer “What if this works?” It’s “How far does this go?”
When Falcon Heavy lifted off in February 2018 with Elon Musk’s personal Tesla Roadster as its payload, SpaceX was at a much different place. So was Tesla. It was unclear whether Falcon Heavy was feasible at all, and Tesla was in the depths of Model 3 production hell.
At the time, Tesla’s market capitalization hovered around $55–60 billion, an amount critics argued was already grossly overvalued. SpaceX, on the other hand, was an aggressive private launch provider known for taking risks that traditional aerospace companies avoided.
The Roadster launch was bold by design. Falcon Heavy’s maiden mission carried no paying payload, no government satellite, just a car drifting past Earth with David Bowie playing in the background. To many, it looked like a stunt. For Elon Musk and the SpaceX team, it was a bold statement: there should be some things in the world that simply inspire people.
Inspire it did, and seven years later, SpaceX and Tesla’s results speak for themselves.
Today, Tesla is the world’s most valuable automaker, with a market capitalization of roughly $1.54 trillion. The Model Y has become the best-selling car in the world by volume for three consecutive years, a scenario that would have sounded insane in 2018. Tesla has also pushed autonomy to a point where its vehicles can navigate complex real-world environments using vision alone.
And then there is Optimus. What began as a literal man in a suit has evolved into a humanoid robot program that Musk now describes as potential Von Neumann machines: systems capable of building civilizations beyond Earth. Whether that vision takes decades or less, one thing is evident: Tesla is no longer just a car company. It is positioning itself at the intersection of AI, robotics, and manufacturing.
SpaceX’s trajectory has been just as dramatic.
The Falcon 9 has become the undisputed workhorse of the global launch industry, having completed more than 600 missions to date. Of those, SpaceX has successfully landed a Falcon booster more than 560 times. The Falcon 9 flies more often than all other active launch vehicles combined, routinely lifting off multiple times per week.
Falcon 9 has ferried astronauts to and from the International Space Station via Crew Dragon, restored U.S. human spaceflight capability, and even stepped in to safely return NASA astronauts Butch Wilmore and Suni Williams when circumstances demanded it.
Starlink, once a controversial idea, now dominates the satellite communications industry, providing broadband connectivity across the globe and reshaping how space-based networks are deployed. SpaceX itself, following its merger with xAI, is now valued at roughly $1.25 trillion and is widely expected to pursue what could become the largest IPO in history.
And then there is Starship, Elon Musk’s fully reusable launch system designed not just to reach orbit, but to make humans multiplanetary. In 2018, the idea was still aspirational. Today, it is under active development, flight-tested in public view, and central to NASA’s future lunar plans.
In hindsight, Falcon Heavy’s maiden flight with Elon Musk’s personal Tesla Roadster was never really about a car in space. It was a signal that SpaceX and Tesla were willing to think bigger, move faster, and accept risks others wouldn’t.
The Roadster is still out there, orbiting the Sun. Seven years later, the question is no longer “What if this works?” It’s “How far does this go?”
Energy
Tesla launches Cybertruck vehicle-to-grid program in Texas
The initiative was announced by the official Tesla Energy account on social media platform X.
Tesla has launched a vehicle-to-grid (V2G) program in Texas, allowing eligible Cybertruck owners to send energy back to the grid during high-demand events and receive compensation on their utility bills.
The initiative, dubbed Powershare Grid Support, was announced by the official Tesla Energy account on social media platform X.
Texas’ Cybertruck V2G program
In its post on X, Tesla Energy confirmed that vehicle-to-grid functionality is “coming soon,” starting with select Texas markets. Under the new Powershare Grid Support program, owners of the Cybertruck equipped with Powershare home backup hardware can opt in through the Tesla app and participate in short-notice grid stress events.
During these events, the Cybertruck automatically discharges excess energy back to the grid, supporting local utilities such as CenterPoint Energy and Oncor. In return, participants receive compensation in the form of bill credits. Tesla noted that the program is currently invitation-only as part of an early adopter rollout.
The launch builds on the Cybertruck’s existing Powershare capability, which allows the vehicle to provide up to 11.5 kW of power for home backup. Tesla added that the program is expected to expand to California next, with eligibility tied to utilities such as PG&E, SCE, and SDG&E.
Powershare Grid Support
To participate in Texas, Cybertruck owners must live in areas served by CenterPoint Energy or Oncor, have Powershare equipment installed, enroll in the Tesla Electric Drive plan, and opt in through the Tesla app. Once enrolled, vehicles would be able to contribute power during high-demand events, helping stabilize the grid.
Tesla noted that events may occur with little notice, so participants are encouraged to keep their Cybertrucks plugged in when at home and to manage their discharge limits based on personal needs. Compensation varies depending on the electricity plan, similar to how Powerwall owners in some regions have earned substantial credits by participating in Virtual Power Plant (VPP) programs.
News
Samsung nears Tesla AI chip ramp with early approval at TX factory
This marks a key step towards the tech giant’s production of Tesla’s next-generation AI5 chips in the United States.
Samsung has received temporary approval to begin limited operations at its semiconductor plant in Taylor, Texas.
This marks a key step towards the tech giant’s production of Tesla’s next-generation AI5 chips in the United States.
Samsung clears early operations hurdle
As noted in a report from Korea JoongAng Daily, Samsung Electronics has secured temporary certificates of occupancy (TCOs) for a portion of its semiconductor facility in Taylor. This should allow the facility to start operations ahead of full completion later this year.
City officials confirmed that approximately 88,000 square feet of Samsung’s Fab 1 building has received temporary approval, with additional areas expected to follow. The overall timeline for permitting the remaining sections has not yet been finalized.
Samsung’s Taylor facility is expected to manufacture Tesla’s AI5 chips once mass production begins in the second half of the year. The facility is also expected to produce Tesla’s upcoming AI6 chips.
Tesla CEO Elon Musk recently stated that the design for AI5 is nearly complete, and the development of AI6 is already underway. Musk has previously outlined an aggressive roadmap targeting nine-month design cycles for successive generations of its AI chips.
Samsung’s U.S. expansion
Construction at the Taylor site remains on schedule. Reports indicate Samsung plans to begin testing extreme ultraviolet (EUV) lithography equipment next month, a critical step for producing advanced 2-nanometer semiconductors.
Samsung is expected to complete 6 million square feet of floor space at the site by the end of this year, with an additional 1 million square feet planned by 2028. The full campus spans more than 1,200 acres.
Beyond Tesla, Samsung Foundry is also pursuing additional U.S. customers as demand for AI and high-performance computing chips accelerates. Company executives have stated that Samsung is looking to achieve more than 130% growth in 2-nanometer chip orders this year.
One of Samsung’s biggest rivals, TSMC, is also looking to expand its footprint in the United States, with reports suggesting that the company is considering expanding its Arizona facility to as many as 11 total plants. TSMC is also expected to produce Tesla’s AI5 chips.
Celebrating SpaceX’s Falcon Heavy Tesla Roadster launch, seven years later (Op-Ed)
SpaceX’s xAI merger keeps legal liability and debt at arm’s length: report
