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.
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SpaceX Starship Flight 13 faces wrath of the Texas skies
SpaceX pushed Starship Flight 13 to Friday, blaming weather instead of the previous engine issues.
SpaceX called off Thursday’s launch attempt of Starship Flight 13, pushing the mission to Friday because of weather tied to Tropical Storm Bertha. The company confirmed the delay on X, noting “Now targeting Friday, July 24 for Starship’s thirteenth flight test, due to weather. A key objective for the flight test is to get clear imagery from the ground of Starship’s heatshield as it flies at a higher dynamic pressure during ascent, which won’t be possible with today’s weather conditions.”
This is the second delay for Flight 13 in two weeks. SpaceX first tried to launch the mission on July 16, but the countdown ended in an automated abort at T-0 when four of Super Heavy Booster 20’s 33 Raptor engines failed to ignite. Musk said at the time that two Raptors would need to be removed and replaced, as Teslarati reported. The company spent the following week destacking Ship 40 and Booster 20, swapping engines, and running leak checks before restacking the vehicle on Pad 2 Wednesday night, according to Spaceflight Now’s live coverage.
Unlike the engine problem, Thursday’s delay has nothing to do with the hardware. SpaceX wants clean footage of Starship’s heat shield captured from the ground as the vehicle flies through max dynamic pressure, something the storm’s cloud cover over South Texas would not allow. The company said visibility should improve for Friday’s attempt, with the same 90 minute window opening at 5:45 p.m. CT.
Flight 13 will be the second outing for the V3 versions of Starship and Super Heavy, following their debut on Flight 12 in May. The mission carries 20 production Starlink V3 satellites, the first time SpaceX has flown operational satellites rather than mass simulators on Starship. Six of those satellites are fitted with cameras to inspect the heat shield from a different angle during ascent, giving engineers a second data source beyond the ground imagery the weather is currently blocking.
Booster 20 will attempt a boostback burn and a splashdown landing burn in the Gulf of America, while Ship 40 follows a suborbital trajectory toward a landing in the Indian Ocean. The flight plan largely mirrors Flight 12, though the booster will run a more aggressive ascent burn after max Q this time, and the ship’s heat shield includes load sensing tiles meant to measure stress at the higher dynamic pressure SpaceX is targeting.
If Friday’s attempt succeeds, Flight 13 could be the last suborbital test in the program. SpaceX is already looking to push for an orbital flight on Flight 14.
Tesla stock (NASDAQ: TSLA) endured one of its sharpest single-day declines in years on July 23, tumbling approximately 14.5 percent and closing near $320 after opening the session around $374. The drop erased more than $140 billion in market value amid heavy trading volume and left the shares at multi-week lows.
The sell-off followed the company’s second-quarter 2026 results, released the previous evening. Tesla reported record revenue of $28.2 billion, up 26 percent year over year, driven by a Q2-record 480,126 vehicle deliveries. Energy storage deployments also rose strongly.
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Yet profitability disappointed sharply. Operating income fell 57 percent to $398 million, compressing the operating margin to just 1.4 percent. Non-GAAP earnings per share came in at $0.33, well below the roughly $0.53 analysts had expected. Free cash flow turned negative by $1.1 billion as capital expenditures surged 142 percent to $5.8 billion, largely tied to accelerated spending on artificial intelligence, robotics, and autonomous systems.
The losses on capex were expected, as Tesla said it would be spending heavily in 2026.
Investors also reacted to lingering uncertainty surrounding key product timelines. During the Earnings Call, management reiterated ambitions for Robotaxi deployment and the Optimus humanoid robot, but offered limited new concrete milestones, renewing questions about execution pace that have long accompanied Tesla’s ambitious roadmap.
The magnitude of the decline places it among Tesla’s more severe one-day percentage losses since its 2010 initial public offering. Historically, the two largest single-day drops (split-adjusted) remain September 8, 2020, when shares fell 21.1 percent amid broader market volatility and valuation concerns, and January 13, 2012, with a 19.3 percent plunge during the company’s early growth struggles.
Other notable declines include an 18.6 percent drop on March 16, 2020, at the onset of pandemic-related market turmoil. Thursday’s move ranks roughly ninth on the all-time list but stands out as the steepest in more than a year.
Despite the short-term pain, Tesla’s long-term trajectory has repeatedly recovered from such volatility. The latest results underscore both the strength of its core automotive and energy businesses and the near-term costs of heavy investment in next-generation technologies.
Elon Musk clapped back at France’s decision to withhold the approval for Tesla’s Full Self-Driving (FSD) Supervised system, projecting a clear and blunt message to French Transport Minister Phillippe Tabarot, after he publicly rejected the technology in its current form.
Tabarot outlines several concerns with Tesla Full Self-Driving in a detailed video statement, where he said, “The safety trade-offs are not yet sufficient to authorize it as it currently stands,” he said. He emphasized that FSD is not a true self-driving system and that the driver remains fully responsible.
Key issues Tabarot also brought up included allowing speeding when surrounding traffic exceeds limits and what he believes are insufficient guarantees of driver attention during complex urban maneuvers such as lane changes, intersections, and roundabouts.
Delaying the approval of FSD in France will cost lives
— Elon Musk (@elonmusk) July 22, 2026
While acknowledging technological progress and France’s support for autonomous innovation, Tabarot stressed that deployment must prioritize road safety. He noted ongoing technical discussions with Tesla, the Netherlands, and other European partners, with further ecosystem meetings planned for the fall.
Musk’s rebuke highlights the human cost of regulatory caution. Tesla’s latest safety reports provide compelling data supporting accelerated adoption. In the most recent 12-month period, vehicles using FSD (Supervised) recorded one major collision per approximately 5.1 million miles driven, dramatically better than the U.S. national average of one crash per 698,000 miles.
Even Tesla vehicles driven manually with active safety features outperform the average by a wide margin. These figures come from billions of real-world miles of telemetry, showing FSD vehicles involved in far fewer incidents than both manual Teslas and the broader U.S. fleet.
Critics argue Tesla’s comparisons require careful scrutiny regarding reporting thresholds and fleet demographics, yet the data consistently positions FSD as a potential lifesaver. With road fatalities remaining a leading cause of death worldwide, Musk contends that proven safer technology should not face prolonged bureaucratic hurdles.
France’s measured approach reflects the broader European regulatory caution, which many, especially Musk, have been critical of in the past. However, as autonomous systems from Tesla and competitors like Waymo demonstrate superior safety in independent studies, pressure is mounting for harmonized approvals.
Musk’s warning carries the belief that every month of delay may equate to avoidable tragedies on European roads.
SpaceX Starship Flight 13 faces wrath of the Texas skies
Tesla stock tumbles after earnings, one of its sharpest single-day declines
