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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Elon Musk
Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry
Tesla, SpaceX, and xAI unveiled TERAFAB, a $25B chip factory targeting one terawatt of AI compute annually.
Elon Musk took the stage over the weekend at the defunct Seaholm Power Plant in Austin, Texas, to officially unveil TERAFAB, a $20-25 billion joint venture between Tesla, SpaceX, and xAI that he described as “the most epic chip building exercise in history by far.” The announcement marks the most ambitious infrastructure bet Musk has made since Gigafactory 1 in Sparks, Nevada, and it fuses three of his companies into a single, vertically integrated AI hardware machine for the first time.
TERAFAB is designed to consolidate every stage of semiconductor production under one roof, including chip design, lithography, fabrication, memory production, advanced packaging, and testing. At full capacity, the facility would scale to roughly 70% of the global output from the current world’s largest semiconductor foundry from Taiwan Semiconductor Manufacturing Company (TSMC).
Elon Musk’s stated goal is one terawatt of computing power annually, split between Tesla’s AI5 inference chips for vehicles and Optimus robots, and D3 chips built specifically for SpaceXAI’s orbital satellite constellation.
Tesla Terafab set for launch: Inside the $20B AI chip factory that will reshape the auto industry
The logic behind the merger of these three entities is rooted in a supply chain crisis Musk has been signaling for over a year. At Tesla’s Q4 2025 earnings call, he warned investors that external chip capacity from TSMC, Samsung, and Micron would hit a ceiling within three to four years. “We’re very grateful to our existing supply chain, to Samsung, TSMC, Micron and others,” Musk acknowledged at the Terafab event, “but there’s a maximum rate at which they’re comfortable expanding.” Building in-house was, in his framing, not a strategic option, but a necessity.
The space angle is where the announcement becomes genuinely unprecedented. Musk said 80% of Terafab’s compute output would be directed toward space-based orbital AI satellites, arguing that solar irradiance in space is roughly 5x greater than at Earth’s surface, and that heat rejection in vacuum makes thermal scaling viable. This directly feeds the SpaceXAI vision, which is betting that within two to three years, running AI workloads in orbit will be cheaper than doing so on the ground. The satellites, powered by constant solar energy, would effectively turn low Earth orbit into the world’s largest data center.
Will Tesla join the fold? Predicting a triple merger with SpaceX and xAI
Historically, this announcement threads together every major Musk initiative of the past two years: the xAI-SpaceX merger, Tesla’s $2.9 billion solar equipment talks with Chinese suppliers, the 100 GW domestic solar manufacturing push, the Optimus humanoid robot program, and Starship’s development. TERAFAB is the capstone that ties them into a single coherent architecture — chips made on Earth, launched by SpaceX, powered by Tesla solar, run by xAI, and ultimately extended to the Moon.
“I want us to live long enough to see the mass driver on the moon, because that’s going to be incredibly epic,”Musk said during the presentation.
Announcing TERAFAB: the next step towards becoming a galactic civilization https://t.co/IDKey07mJa
— Tesla (@Tesla) March 22, 2026
News
Rolls-Royce makes shocking move on its EV future
When Rolls-Royce unveiled its first all-electric model, the Spectre, in 2022, former CEO Torsten Müller-Ötvös declared the brand would cease production of internal combustion engine vehicles by the end of the decade.
Rolls-Royce made a shocking move on its EV future after planning to go all-electric by the end of the decade. Now, the company is tempering its expectations for electric vehicles, and its CEO is aiming to lean on its legacy of high-powered combustion engines to lead it into the future.
In a significant reversal, Rolls-Royce Motor Cars has scrapped its ambitious plan to become an all-electric manufacturer by 2030. The luxury British marque announced the decision amid sustained customer demand for traditional combustion engines and shifting regulatory landscapes.
When Rolls-Royce unveiled its first all-electric model, the Spectre, in 2022, former CEO Torsten Müller-Ötvös declared the brand would cease production of internal combustion engine vehicles by the end of the decade.
The move aligned with the industry’s broader push toward electrification, promising silent, effortless power befitting the “Rolls-Royce of cars.”
However, new CEO Chris Brownridge, who assumed the role in late 2023, has reversed course. “We can respond to our client demand … we build what is ordered,” Brownridge stated.
The company will continue offering its iconic V12 engines, which remain a cornerstone of its heritage and appeal to discerning buyers who appreciate the distinctive sound and character. He noted the original pledge was “right at the time,” but “the legislation has changed.”
While not abandoning electric vehicles entirely, the Spectre remains in production, with an electric Cullinan option forthcoming; the decision marks the end of a strict all-EV timeline. Relaxed emissions regulations and slowing EV demand, evidenced by a 47 percent drop in Spectre sales to 1,002 units in 2025, forced the reconsideration.
It was a sign that perhaps Rolls-Royce owners were not inclined to believe that the company’s all-EV future was the right move.
Rolls-Royce joins a growing roster of automakers reevaluating aggressive electrification targets.
Fellow luxury brand Bentley has pushed its full electrification from 2030 to 2035, while continuing to offer hybrids and ICE models. Mercedes-Benz walked back its 2030 all-EV goal, now aiming for about 50% electrified sales while keeping combustion engines into the 2030s. Porsche has abandoned its 80% EV sales target by 2030, delaying models and extending hybrids.
Mainstream giants are following suit. Honda canceled its U.S. EV plans, including the 0-Series and Acura RSX, facing a $15.7 billion hit as it doubles down on hybrids. Ford and General Motors have incurred tens of billions in writedowns, canceling models and pivoting to hybrids amid an industry total exceeding $70 billion in charges.
This trend reflects a pragmatic shift driven by infrastructure gaps, consumer preferences, and policy changes. In the ultra-luxury segment, where emotional connection reigns, automakers are prioritizing flexibility over rigid deadlines, ensuring brands like Rolls-Royce evolve without alienating their core clientele.
News
Elon Musk teases expectations for Tesla’s AI6 self-driving chip
This optimistic timeline for tape-out—the stage where chip design is finalized before manufacturing—signals Tesla’s push to rapidly advance its silicon capabilities.
Tesla CEO Elon Musk is outlining expectations for the AI6 self-driving chip, which is still two generations away. Despite this, it is already in the plans of the company and its serial entrepreneur CEO, who has high expectations for it.
Musk provided fresh details on the company’s aggressive AI hardware roadmap, spotlighting the upcoming AI6 chip designed to supercharge Tesla’s self-driving tech, humanoid robots, and data center operations.
In a post on X dated March 19, Musk stated, “With some luck and acceleration using AI, we might be able to tape out AI6 in December.”
With some luck and acceleration using AI, we might be able to tape out AI6 in December
— Elon Musk (@elonmusk) March 19, 2026
This optimistic timeline for tape-out—the stage where chip design is finalized before manufacturing—signals Tesla’s push to rapidly advance its silicon capabilities.
The announcement builds on progress with the predecessor AI5. Earlier in January, Musk announced that the AI5 design was “in good shape” and “almost done,” describing it as an “existential” project for the company that demanded his personal attention on weekends.
He characterized AI5 as roughly equivalent to Nvidia’s Hopper class performance in a single system-on-chip (SoC) and Blackwell-level as a dual configuration, but at significantly lower cost and power usage.
Elon Musk is setting high expectations for Tesla AI5 and AI6 chips
Musk highlighted that AI5 “will punch far above its weight” thanks to Tesla’s co-designed AI software and hardware stack, making maximal use of every circuit. While capable of data center training tasks, it is primarily optimized for edge computing in Optimus robots and Robotaxi vehicles.
For AI6, Musk envisions substantial gains. “In the same half reticle and same process node, we think a single AI6 chip has the potential to match a dual SoC AI5,” he explained.
The company is targeting ambitious nine-month development cycles for future chips, allowing rapid iteration to AI7, AI8, and beyond. AI5/AI6 engineering remains Musk’s top time allocation at Tesla, with the CEO calling AI5 “good” and AI6 “great.”
Samsung is expected to manufacture the AI6 chips, following deals worth billions, while AI5 will leverage TSMC and Samsung production. These chips will form the backbone of Tesla’s Full Self-Driving system, enabling safer and more capable autonomy, alongside powering dexterous movements in Optimus bots and efficient inference in expanding data centers.
Tesla to discuss expansion of Samsung AI6 production plans: report
Musk has also restarted work on the Dojo 3 supercomputer project now that AI5 is progressing. Long-term plans include in-house manufacturing via the Terafab facility.
By accelerating chip development with AI tools, Tesla aims to reduce dependence on third-party GPUs and deliver high-performance, energy-efficient solutions tailored to its ecosystem. Success with AI6 could mark a major milestone in Tesla’s journey toward full autonomy and robotics leadership, though timelines remain subject to manufacturing realities.