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
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
