The release notes for Tesla FSD Beta V11.3 have been shared online. Observers from the electric vehicle community suggest that Tesla Full Self-Driving Beta 11.3 is rolling out to the company’s employee FSD Beta testers, at least for now.
The following are Tesla’s FSD Beta V11.3 release notes:
- Enabled FSD Beta on highway. This unifies the vision and planning stack on and off-highway and replaces the legacy highway stack, which is over four years old. The legacy highway stack still relies on several single-camera and single-frame networks, and was setup to handle simple lane-specific maneuvers. FSD Beta’s multi-camera video networks and next-gen planner, that allows for more complex agent interactions with less reliance on lanes, make way for adding more intelligent behaviors, smoother control and better decision making.
- Added voice drive-notes. After an intervention, you can now send Tesla an anonymous voice message describing your experience to help improve Autopilot.
- Expanded Automatic Emergency Braking (AEB) to handle vehicles that cross ego’s path. This includes cases where other vehicles run their red light or turn across ego’s path, stealing the right-of-way.
- Replay of previous collisions of this type suggests that 49% of the events would be mitigated by the new behavior. This improvement is now active in both manual driving and autopilot operation.
- Improved autopilot reaction time to red light runners and stop sign runners by 500ms, by increased reliance on object’s instantaneous kinematics along with trajectory estimates.
- Added a long-range highway lanes network to enable earlier response to blocked lanes and high curvature.
- Reduced goal pose prediction error for candidate trajectory neural network by 40% and reduced runtime by 3X. This was achieved by improving the dataset using heavier and more robust offline optimization, increasing the size of this improved dataset by 4X, and implementing a better architecture and feature space.
- Improved occupancy network detections by oversampling on 180K challenging videos including rain reflections, road debris, and high curvature.
- Improved recall for close-by cut-in cases by 20% by adding 40k autolabeled fleet clips of this scenario to the dataset. Also improved handling of cut-in cases by improved modeling of their motion into ego’s lane, leveraging the same for smoother lateral and longitudinal control for cut-in objects.
- Added “lane guidance module and perceptual loss to the Road Edges and Lines network, improving the absolute recall of lines by 6% and the absolute recall of road edges by 7%.
- Improved overall geometry and stability of lane predictions by updating the “lane guidance” module representation with information relevant to predicting crossing and oncoming lanes.
- Improved handling through high speed and high curvature scenarios by offsetting towards inner lane lines.
- Improved lane changes, including: earlier detection and handling for simultaneous lane changes, better gap selection when approaching deadlines, better integration between speed-based and nav-based lane change decisions and more differentiation between the FSD driving profiles with respect to speed lane changes.
- Improved longitudinal control response smoothness when following lead vehicles by better modeling the possible effect of lead vehicles’ brake lights on their future speed profiles.
- Improved detection of rare objects by 18% and reduced the depth error to large trucks by 9%, primarily from migrating to more densely supervised autolabeled datasets.
- Improved semantic detections for school busses by 12% and vehicles transitioning from stationary-to-driving by 15%. This was achieved by improving dataset label accuracy and increasing dataset size by 5%.
- Improved decision making at crosswalks by leveraging neural network based ego trajectory estimation in place of approximated kinematic models.
- Improved reliability and smoothness of merge control, by deprecating legacy merge region tasks in favor of merge topologies derived from vector lanes.
- Unlocked longer fleet telemetry clips (by up to 26%) by balancing compressed IPC buffers and optimized write scheduling across twin SOCs.
Here are the V11.3 release notes again if you haven't seen them. Very happy to see improvements in rain reflections as that was rare, but could give some insane errors #FSDBeta @elonmusk pic.twitter.com/ZIOcIhmUMd
— Dirty Tesla (@DirtyTesLa) February 20, 2023
Several longtime FSD Beta testers have pointed out some key improvements that would likely be very appreciated by users in V11.3. These include the systems’ improved handling through high speed and high curvature scenarios, as well as improvements to Automatic Emergency Braking (AEB). With the improvements in place, FSD Beta V11.3 would behave closer to a proper human driver.
Comments from longtime Tesla FSD Beta testers also suggest that V11.3 is still only being released for company employees for now. Considering Tesla’s past updates, it would not be surprising if the greater FSD Beta fleet gets the V11.3 update in the coming week or so. This is, of course, unless V11.3 ends up going the way of FSD Beta V11, which was released to employees in November but not to the greater fleet of FSD Beta testers.
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
SpaceX just combined Grok, Cursor, and X into one mega plan
SpaceXSI merges Grok, Cursor, and X Premium into one plan, raising questions for Tesla owners.
SpaceX Super Intelligence has rolled out The X Subscription, a single plan that combines Grok, Grok Bot, Cursor, and X Premium.
There are five levels, including a free plan that includes daily Grok access and a starter allowance for Cursor’s coding agents. Plus is $8 per month, Premium is $30, Super is $100, and Ultra is $200. Usage scales as you move up, with Premium offering four times the Plus allowance, Super 15 times, and Ultra 50 times. Annual billing brings the prices down a bit further, with Premium at $300 per year.
We’ve unified plans across Grok, Cursor, and X Premium.
Introducing The X Subscription. https://t.co/SvkrVvBa0p
— SpaceX Super Intelligence (@SpaceXSI) October 12, 2026
The $30 Premium tier is where SpaceXSI says it packs the benefits of SuperGrok, Cursor Pro, and X Premium+, which previously added up to $90 per month. Grok Bot, the agent that handles tasks like ordering food or managing a calendar, is included from Premium upward but not on Plus. Paid plans share one weekly usage pool across Grok and Cursor, and each plan includes at least twice the coding usage of the comparable Cursor plan. Third party models in Cursor remain available on Premium and above, but they are billed separately at API list prices.
That last detail matters because of what has happened around Cursor this year. SpaceX exercised its option to buy the company for $60 billion in June, and the deal closed in August. Weeks later, OpenAI said it will cut Cursor’s access to its models on November 12. Bundling Cursor with Grok usage gives SpaceXSI a reason to steer developers toward its own models.
Tesla integrates Grok Bot into its vehicles for the ultimate personal assistant
For Tesla owners, the connection is Grok Bot. Tesla brought it into its vehicles last month, and at that point access inside the car was limited to SuperGrok Heavy subscribers. Grok Bot is now enabled across every Cybercab and the rest of the Model Y Robotaxi fleet. Neither SpaceXSI nor Tesla has said how the new plans change inside the car access for owners, or whether a $30 Premium subscription now covers Grok Bot in a personal Tesla. That is the question owners will want answered first.
The company is also changing its name along the way. The rollout follows the rebrand Musk announced on October 4, when he said SpaceXAI would become SpaceXSI, and the plan page now carries that branding.
The X Subscription is available to new customers starting now, and SpaceXSI says it will reach everyone globally over the next few days. Existing SuperGrok, Cursor, and X Premium subscribers do not have to switch. The option to move will appear gradually in billing settings, with a prorated refund for the unused time on the old plan. Switching is permanent once the accounts are unified, and old plans are closed to new sign ups.
Energy
Taiwan power firm bets big on Tesla Megapacks as AI data center thirst grows
Taiwan’s Apollo Power orders 260 Tesla Megapacks, betting AI data centers will need more electricity.
A Taiwanese power company has ordered 260 Tesla Megapack 2XL units, roughly 1GWh of storage, betting that electricity rather than chips will decide how fast AI data centers come online. Apollo Power signed the contract with Tesla’s Taiwan energy arm on October 8, according to the company’s filing with the Taiwan stock exchange.
The filing says the units are meant for behind the meter storage and resilient grid projects, with delivery in batches from the end of 2027 and sites operating in 2028. Apollo and Tesla did not disclose a price, citing a confidentiality agreement. Apollo plans to pay for the equipment through a cash capital increase and bank financing, and it noted the purchase is not revenue and does not mean it holds firm orders from its partners.
Biggo reported that only about 33 units are under signed customer contracts, with roughly 150 more in negotiation. The same report put total project investment near NT$130 billion, but that figure includes installation work, with the equipment itself making up about 40 to 50 percent. In other words, a large share of this order is Apollo reserving supply ahead of demand. Apollo’s chairman told local media global large storage supply is tight, which is why the company locked in the units early, according to Yahoo Taiwan Finance.
Apollo also launched an AI data center and grid resilience alliance with Phison, Gigabyte and Shihlin Electric. The pitch rests on a pilot at Phison’s Zhunan plant, where Apollo and Tesla Energy Taiwan installed grid forming Megapack 2XLs in June. Tesla Energy Taiwan general manager Sun Hsiao-Han said the project went from demo to 1GWh in four months, and that Tesla Energy has deployed more than 50GWh worldwide.
Taiwan’s cabinet has approved amendments that would require large energy users to install their own generation and storage, which gives enterprise storage a regulatory tailwind.
The deal fits a pattern Teslarati has tracked. Tesla’s Megablock targets 1GWh commissioned in 20 business days, a pitch aimed squarely at fast moving data center builds. Megapacks already back xAI’s Colossus in Memphis and a 400MW AI campus in Brazil. Sun Media adds that Megapack 2XL was named among the first products in Nvidia’s DSX Ready qualification for battery storage in AI factories.
Deliveries are more than a year away, so the real test is how much of that 260 unit order turns into signed customer contracts.
For a century, the car has asked the same thing of its owner, which is basically to pay attention. Even the best ride-hailing app like Uber or Lyft only moved the problem into someone else’s hands. You stopped driving, but you still sat in a stranger’s car, while half listening, and wondering whether to take a phone call in the car without being rude. The Cybercab has no wheel, no pedals and no driver. With Grok @bot now live inside it, it becomes something else entirely, and I think that matters more than the fleet count that everyone is tracking.
Grok @bot is an agent, not a voice assistant. A rider signs in once, and from then on can say what they need and watch it happen. Order dinner from a favorite restaurant. Fill the grocery cart. Move money, answer email, adjust a calendar, push a work project forward. Tesla engineer Yun-Ta Tsai confirmed it is enabled across every Cybercab and the rest of the Model Y fleet, and Tesla’s own pitch is that Full Self-Driving handles the commute while Grok handles the errands.
Think about what that does to a thirty minute ride. Uber sells you a trip, while Waymo sells you the same trip in a more private setting. Tesla is selling the thirty minutes themselves, returned to you with an assistant attached. Errands that used to eat a Saturday get done between pickup and drop off. The ride stops being dead time between two places and becomes a place of its own.
Tesla integrates Grok Bot into its vehicles for the ultimate personal assistant
Best of all, your Bots follow you into any Cybercab, and presumably your own Tesla, then logs you out automatically when you step out. Anyone can bolt a chatbot onto a screen, but much harder to own the vehicle, the autonomy stack and the assistant at once. It also quietly ties SpaceX’s Super Intelligence business to Tesla’s fleet, after Tesla converted its xAI stake into SpaceX equity. The relationship between those two companies is getting harder to describe as separate.
This is also where the hard questions start, because an agent that can spend your money in a vehicle other people also ride in needs some answers. How does it handle a voice it shouldn’t trust? What gets recorded, who can see it, and for how long? What happens when a rider leaves halfway through a task?
If Tesla gets those answers right, the scoreboard changes. We have been counting Cybercabs and wait times. The more telling number may be what riders accomplish per trip. That is data almost no one else will ever have, and it is the real reason to watch Grok @bot.
What do you think? Leave me a comment.
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