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.
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Tesla has revealed plans through permit submissions for a massive Robotaxi charging hub in Austin, Texas.
Tesla plans to build the Supercharger hub in multiple phases, with the second phase potentially introducing wireless induction charging, something the company has been developing for the Robotaxi fleet.
Initially, 48 Tesla Robotaxi-geared Superchargers will be built on a lot just across from the St. Elmo, Texas, Service Center. There are about 80 additional spots that will not be impacted by phase 1 of the construction process.
Filings show that the second phase of the project will turn those 80 additional spots into wireless charging for Robotaxi, but it might be an error. The Key Notes state that item 3 is listed as “V4 Charging Cabinet to Support 80 Wireless Chargers in Phase 2. However, the drawings point to V3 Cabinets that are already tied to Superchargers:
There are roughly 128 total spots in the lot, but it is unclear if they will all be used for charging based on what appears to be some sort of typo in the blueprint.
A new Robotaxi fleet charging hub is coming soon to Austin, Texas!!
Permits have been filed for the installation of 48 (V3) stalls in a vehicle storage lot across the road from Tesla’s St Elmo service center. pic.twitter.com/xwRgSWDqht
— MarcoRP (@MarcoRPi1) August 18, 2026
This is among the first Robotaxi charging hubs Tesla has started to develop, as it currently has four others planned throughout various areas: one in Phoenix, one in San Antonio, another in Irving, which will serve the Dallas-Fort Worth area, and another in Las Vegas.
These projects are necessary as Tesla expands its Robotaxi program. Now that preparations have started for the public launch of Cybercab, Robotaxi will likely be expanding aggressively, especially over the next two to three years.
Last night, The Information reported that Tesla was planning to launch Cybercab as soon as the end of August. Hours later, Tesla then announced it was launching a competition for fans to potentially ride in Cybercab during its first public rides.
Tesla’s plan to expand its charging infrastructure in the regions where Robotaxi will initially operate is great preparation for the expanding service. There is still a lot to do, including launching the Cybercab on time.
Tesla got its largest order for the all-electric Class 8 Semi yet, a 500-unit order from Einride AB, a Swedish trucking company.
Einride made the announcement this morning following its second-quarter earnings call. The company said it plans to use 500 Tesla Semi units on its fleet intelligence platform, called Saga AI. The deployments will serve large companies like Amazon and will extend Einride’s electric freight network across logistics routes in California, New Jersey, Texas, Illinois, and Georgia.
🚨 Tesla has received a MASSIVE order from Swedish freight company Einride AB, which placed an order for 500 Tesla Semi trucks
Tesla’s biggest order for the Semi yet! pic.twitter.com/PrtLp5yzvh
— TESLARATI (@Teslarati) August 18, 2026
The deployment is being carried out in several phases over the next two years as Tesla ramps production of the Semi at its dedicated production facility in Sparks, Nevada. Einride will receive its first Semi units in September.
Saga AI
Saga AI is Einride’s dedicated fleet intelligence platform. It enables scaled adoption of electric trucks for freight use and allows shippers to integrate electric capacity without the operational burden or capital risks of managing a fleet. This helps integrate cost-efficient logistics and makes budgeting and forecasting much more accurate.
Tesla Semi’s Adoption
The Tesla Semi is now gathering large-scale clients past those who have helped the company operate a Pilot Program to gain initial information and feedback from real-world drivers.
Perhaps the biggest and most notable is that of Frito-Lay and PepsiCo., who have worked with Tesla for the past several years to dial in the finer details of the truck, including its efficiency and operation-related components.
Tesla Semi gets strange-but-understandable comparison from Jay Leno
There has been tremendous progress in that time, and it even catalyzed Tesla to make some design changes, which were unveiled earlier this year.
But Einride CEO Roozbeh Charli says his company’s partnership with Tesla will continue to push those things forward:
“This deployment is yet another proof point that we can execute at the scale our customers demand. Working closely with Tesla to bring next-generation Semis into active operations quickly and at scale is a testament to the strength of that partnership, and how quickly this technology is maturing from promise to daily operations.”
Additionally, Dan Priestley, the Director of the Semi Program at Tesla, said the partnership is ideal due to Einride’s focus on sustainable transport:
“Einride is at the forefront of sustainable freight, and we are thrilled to deepen our relationship with them through this order of 500 Semis. EV heavy trucks provide lower costs per mile from fuel savings, reduced maintenance, and better uptime over diesel trucks. These savings increase further through operational efficiency when deploying EV trucks at scale, and we are excited that Einride recognizes this and look forward to supporting their deployments.”
Elon Musk
India tells Elon Musk’s X to “Follow the Law” in latest censorship update
Elon Musk says X now exposes government censorship, but India’s secrecy laws complicate that promise.
Elon Musk’s promise to make government censorship requests on X “clearly visible” is running into a wall in India, where the law forbids the very disclosure Musk is promising.
On August 15, Musk responded to an update from X’s open-source algorithm team by writing “Any censorship required by governments is now clearly visible.” The claim referred to a change X pushed two days earlier to its public xai-org/x-algorithm repository, which now includes a controversial filter written directly into the code. The filter suppresses posts from 665 accounts flagged by Brazil’s Superior Electoral Court from appearing in the For You feed of any viewer located in Brazil, unless the viewer already follows the account. The election tied to the filter is scheduled for October 4.
India’s government wasn’t as impressed, and responded on Monday that “X will have to follow the law of the land,” in response to Musk’s transparency push covered by the Times of India. The problem is structural rather than political. India issues content blocking orders under Section 69A of its IT Act, and Rule 16 of the accompanying 2009 Blocking Rules requires those orders to stay confidential. Publishing an India equivalent of the Brazil filter, naming specific accounts and citing specific government orders, would itself violate Indian law. Government use of Section 69A has grown from roughly 6,000 orders a year between 2018 and 2023 to about 24,300 in 2025, according to a Tech Times report.
The contrast puts Musk’s transparency pledge in an odd spot. It works largely as advertised in Brazil, where electoral law requires disclosure and X can point to specific account IDs and a specific court order in public code. It cannot work the same way in India, where the law requires the opposite. X users in India will keep seeing content disappear from search and their feeds without any public accounting of why, even as X tells the rest of the world that its censorship compliance is now inspectable.
This isn’t the first time X’s fights with a national government have shaped how the platform operates. Brazil’s Supreme Court ordered X to suspend the accounts of sitting lawmakers and journalists in 2024, a standoff that cost X its Brazilian revenue for months and froze Starlink’s local accounts before the investigation into Musk and X was closed in March with no evidence of wrongdoing found. X also sued California over a state law requiring moderation disclosures, arguing the mandate itself violated the First Amendment.
Whether India’s government pursues anything beyond a public statement remains to be seen. For now, the mismatch between what X can legally publish and what different governments legally allow it to publish is the real story behind Musk’s seven word claim.
Tesla reveals plans for Robotaxi charging hub in Austin
Tesla Semi gets its largest order yet
