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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 Semi lands the biggest electric truck deal in U.S. history

Tesla leads a record 2,500 truck order, but not every truck will be a Semi.

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Tesla has landed the largest electric truck order in U.S. history. ZET SCALE, a new alliance of shippers and carriers, named Tesla its primary manufacturer on Tuesday for an initial order of 2,500 electric Class 8 trucks. The deal alone would nearly double the number of electric heavy trucks operating in the country.

According to the press release from Catalyst Mobility, the nonprofit formerly known as CALSTART, Kenworth, RIDE and Volvo were also selected as secondary manufacturers that carriers can pick if their operations call for it. No split between the four brands has been published, so the exact number of Semis in the order is not yet known.

Tesla won the top slot through a competitive request for proposals. The alliance, which Catalyst Mobility runs with the Smart Freight Centre, scored bidders on price, range, charging capability and production capacity. Pooling freight demand from founding shippers, including Microsoft and PepsiCo, let every truck maker bid lower than it would for a single fleet. “The Tesla Semi is designed for lower cost per mile operations than diesel,” said Dan Priestley, director of the Tesla Semi program, as noted in the press release.

The financing is built to pull in carriers who have avoided electric trucks. ZET Financial is issuing the purchase order for all 2,500 units and will place them with fleets through a fair market value lease. The trucks will be deployed over the next few years across 10 freight hubs in Los Angeles, Stockton, Bakersfield, Seattle and Tacoma, Houston, Dallas, San Antonio, Chicago, Atlanta, and the Newark and New York area. ZET SCALE says the first order is only the opening round, with a longer term goal of 10,000 trucks or more.

Even if Tesla ends up with only a majority share, it would still be the biggest Semi deal to date. Einride’s 500 unit order in August was the previous record, and WattEV’s 370 truck order in May was the largest California deal at the time. Einride’s CEO has since said he expects all 500 trucks delivered by the end of 2027.

The announcement lands two days before Tesla formally inaugurates its Semi factory in Nevada on September 24. The 1.7 million square foot plant sits next to Gigafactory Nevada’s 4680 cell lines and is designed for 50,000 trucks a year.

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Tesla integrates Grok Bot into its vehicles for the ultimate personal assistant

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Credit: Grok

Tesla has expanded Grok from an in-car chatbot into a hands-free work assistant. On September 22, Tesla officially launched Grok Bot capability, confirming that drivers can now manage email, calendars, files, chats, and tasks by voice and then hand more ambitious errands to the AI-fueled productivity cheat code.

Grok itself is built by xAI. The new car features split into two layers: Connectors link Grok to outside accounts. Grok Bot, currently limited to SuperGrok Heavy subscribers, can complete multi-step tasks such as placing a usual coffee order, booking a reservation, or scheduling an appointment. It truly puts the driver in a nearly complete hands-free driving and productivity setting, with ironically the only task truly requiring your hands being to touch the “Start Self-Driving” button.

We were granted access to Grok Bot’s Tesla integration a few weeks back, and we’ve been able to do a handful of things with it. On a handful of occasions, we’ve used it to order food and have it ready for pickup slightly later into the evening; we’ve managed to pick up groceries after a day of errands with Grok Bot, and outside of the car, it’s helped with budgeting and even my fantasy football draft.

Tesla shows another way to utilize it: in their demo, a driver says “Hey Grok,” asks the assistant to check an inbox, and hears that a message concerns a weekend reservation. Grok then scans the calendar, reports no conflicts, and confirms the Tahoe trip is clear. It can also add check-in details to a road-trip itinerary. The point is not novelty chat. It is keeping eyes on the road, or on Full Self-Driving, while the car handles the paperwork of a trip:

This Grok rollout is not a gadget add-on as much as it is Tesla’s thesis in software form: the car should stop being a machine you operate and start being a room you occupy.

Connectors and Grok Bot treat the cabin as an office that happens to move, and that has truly been Tesla’s intention for years now. The car has slowly become an extension of a home more than a vehicle. Inbox, calendar, groceries, takeout, and reservations become voice work, not dashboard chores that you need to do before you get in your car.

Responsibility shifts from the driver to the stack, and as many Tesla owners rely on FSD for travel, Grok Bot now handles the monotony of dinner reservations or appointments.

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Elon Musk

X changed how everyone gets paid, and this lawsuit shows why

X sued a Bitcoin account network over fake payouts as its creator pay model shifts

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Elon Musk’s X has taken a Bitcoin-focused engagement ring to court, and the case doubles as a receipt for how differently the platform pays creators today. The company filed suit in the High Court of England and Wales against Vivek Kumar Sen and Zamyang Sherpa, alleging the pair ran six accounts, including @Vivek4real_, @Bitcoin_Teddy and @TrendingBitcoin, as one coordinated operation to fake the kind of engagement that used to translate directly into money.

According to the filing, first reported by Gizmodo, the accounts posted near identical “BREAKING” crypto headlines seconds apart, in one case 11 seconds, then had three more handles like, reply to and repost the material to manufacture what X called “a false appearance of genuine, human communication and interaction.” X says the scheme pulled in at least £207,384, about $278,000, and pegs its own investigation and remediation costs at another £75,000. The accounts were suspended August 18. X general counsel James Burnham announced the case on X last weekend, writing that the company “will act forcefully to protect our platform and the earnings of genuine creators.” Musk’s own reaction, posted shortly after, was three words: “Don’t mess with 𝕏.”

The timing lines up with a a recent update to how X pays its creators. The program these accounts allegedly gamed, Creator Revenue Sharing, launched in mid 2023 and paid out based on how much a post got engaged with. Originality was never part of the formula, which is exactly how the platform ended up flooded with recycled clips, copy pasted “BREAKING” posts and replies engineered purely to farm reactions from paying subscribers.

X tried patching the model more than once, including an April cut to aggregator payouts and a March regional weighting change that Musk personally paused hours after it was announced. X retired Creator Revenue Sharing for good on September 7 and opened its replacement, Original Content Rewards, the next day.

The new math is stricter. Payouts now come only from qualified impressions, meaning unique Home Timeline views from Premium subscribers where at least half the post is visible, and replies no longer count toward eligibility at all. Copied posts, reuploaded media and reposts without meaningful changes are explicitly excluded. Allegra Jacchia, senior product manager for Creators at SpaceXAI, which now runs X’s product and AI work following xAI’s acquisition of the platform, put it bluntly, saying the goal is to reward creators who bring original ideas and perspective, “not those who have become best at gaming the system.”

Read that way, the lawsuit isn’t really about six crypto accounts. It’s X putting a dollar figure on what the old incentive structure cost, then suing to collect it right as the new one goes live. For live updates on how the case and the new rewards program shake out, follow @Teslarati on X.

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