A user on Reddit leaked the release notes for Tesla's next FSD Beta release
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Tesla's most recent FSD Beta, v11.4.7.3 was released almost a month ago on October 19th, but it now looks like Tesla may be looking to release another FSD Beta update.
Release notes for an alleged subsequent version, FSD Beta 11.4.8, have surfaced on Reddit. While their authenticity isn't confirmed, the release notes use the same syntax and language Tesla typically uses. Here's a breakdown of what may be included in Tesla's next FSD release.
Update: These release notes have now been confirmed and the update is rolling out to Tesla employees for further testing. The update is version 2023.27.11.
Simplified Autopilot Activation
Single-Tap Autopilot: The update reportedly allows drivers to activate Autopilot with just one press of the stalk, instead of the current two-press method. This could make engaging and disengaging Autopilot quicker and more straightforward.
This feature, along with separate audio for passengers using the rear display recently made its way to production in update 2023.38.8, which adds some credibility to these leaked release notes. This could also mean that this version of FSD Beta may be based on a more recent production branch, instead of the current version of 2023.27, which is now starting to lag in terms of features.
Advanced Video Processing
New Video Module: A new video processing component has been introduced to improve vehicle detection, movement understanding (semantics), speed (velocity), and other attributes. This improvement means the system can process visual information more efficiently and quickly, enhancing overall performance.
Enhanced Object Detection
Better Object Detection: The system's ability to notice objects crossing its path is said to be improved by 6%. Additionally, vehicle detection has become more precise due to updated data and the new video module.
Improved Vehicle Interaction
Cut-In Vehicle Detection: The precision in detecting vehicles that cut into the Tesla's lane is reportedly improved by 15%. This is crucial for safer lane changes and merges.
Accuracy in Speed and Movement
Reduced Errors in Speed and Acceleration: The system now makes fewer errors in judging other vehicles' speed (by 3%) and acceleration (by 10%). This means a more accurate response in traffic.
Faster Decision-Making
Reduced Network Latency: The update claims to reduce the delay (latency) in the vehicle's decision-making network by 15%, allowing for quicker responses without compromising performance.
Pedestrian and Cyclist Safety
Rotation Error Reduction: There's an over 8% reduction in errors related to understanding how pedestrians and cyclists are moving or turning. This could improve interactions with these road users.
Enhanced Parking Assistance
Vision Park Assist Accuracy: The geometric accuracy of the Vision Park Assist system is improved by 16%, making parking assistance more reliable by leveraging data from hardware 4 vehicles. It appears that these improvements will apply to all vehicles without ultrasonic sensors, although it's not very clear.
Smoother Lane Changes
Lane Change Accuracy: The accuracy of lane changes in response to path blockages is improved by 10%, likely leading to smoother and safer driving in complex traffic situations.
While these updates, if true, indicate a continued effort by Tesla to refine and improve FSD Beta, Tesla also continues work on the next major release of FSD Beta, version 12. V12 is expected to be 'end-to-end' neural networks, which will be the first time that neural networks are used to control the vehicle.
It's not clear when Tesla expects to release FSD v12, which is also when Musk says FSD will graduate from its beta status. Musk recently showed off FSD v12 and its capabilities in a livestream on X.
The complete release notes that were shared on Reddit are below.
FSD Beta 11.4.8 Release Notes
-Added option to activate Autopilot with a single stalk depression, instead of two, to help simplify activation and disengagement.
-Introduced a new efficient video module to the vehicle detection, semantics, velocity, and attributes networks that allowed for increased performance at lower latency.This was achieved by creating a multi-layered, hierarchical video module that caches intermediate computations to dramatically reduce the amount of compute that happens at any particular time.
-Improved distant crossing object detections by an additional 6%, and improved the precision of vehicle detection by refreshing old datasets with better autolabeling and introducing the new video module.
-Improved the precision of cut-in vehicle detection by 15%, with additional data and the changes to the video architecture that improve performance and latency.
-Reduced vehicle velocity error by 3%, and reduced vehicle acceleration error by 10%, by improving autolabeled datasets, introducing the new video module, and aligning model training and inference more closely.
-Reduced the latency of the vehicle semantics network by 15% with the new video module architecture, at no cost to performance.
-Reduced the error of pedestrian and bicycle rotation by over 8% by leveraging object kinematics more extensively when jointly optimizing pedestrian and bicycle tracks in autolabeled datasets.
-Improved geometric accuracy of Vision Park Assist predictions by 16%, by leveraging 10x more HW4 data, tripling resolution, and increasing overall stability of measurements.
-Improved path blockage lane change accuracy by 10% due to updates to static object detection networks.
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Tesla’s plan to brand its autonomous network of taxicabs has found an interesting little snag. The US Patent and Trademark Office (USPTO) has issued a “nonfinal office action” regarding Tesla’s application to trademark the term “Robotaxi” specifically in connection with autonomous electric vehicles.
This is an initial refusal by USPTO’s examining attorney and is very particular for autonomous electric automobiles. A separate trademark application by Tesla for the term “Robotaxi” as it relates to its upcoming autonomous ride-hailing service is still under examination and has not yet received a similar rebuttal.
Understanding the Refusal
A “nonfinal office action” means the USPTO has found potential issues with the trademark application, as stated, which prevents its immediate approval and subsequent granting to Tesla. Tesla now has a three-month period to file its counterarguments and address the USPTO's concerns.
If Tesla’s response satisfies the examiner, the trademark could be granted.
While the exact content of the office action isn’t detailed in the initial report, such refusals for terms like “Robotaxi” often occur if the USPTO considers the term “merely descriptive” or “generic” for the goods in question. In this particular context, “Robotaxi” could refer to any autonomous taxi vehicle.
Trademark law generally prevents the exclusive registration of terms that competitors would need to use to describe their own similar products. For a term to be trademarked, it typically needs to be distinctive and act as a brand identifier rather than just a descriptive name of the product’s class or type.
Separate Application for Ride-Hailing
Tesla still has a distinct, separate, and still pending application to register “Robotaxi” as a trademark for “transportation services, namely, autonomous ride-hailing services.” The criteria for trademarking a service can differ from those on trademarks for goods, and it’s possible Tesla may have more success securing the name for the service itself, which would allow them to brand the network as “Tesla Robotaxi.”
Why This Matters
Securing a trademark grants exclusive rights to use a brand name in conjunction with specific goods or services. This helps prevent customer confusion and to protect the brand identity.
If the refusal for the vehicle trademark becomes final, Tesla may be limited in its ability to exclusively name a good (specific vehicle) the “Tesla Robotaxi.” Other manufacturers could also potentially use “robotaxi” descriptively for their own autonomous taxi vehicles.
The ability to trademark “Robotaxi” for the ride-hailing service is arguably more critical for Tesla, as they’re working to establish a unique brand for their autonomous transportation network, which kicks off in Austin next month.
The USPTO’s office action won’t hinder Tesla’s ability to develop or deploy its own vehicles in June - instead, it’ll just impact how Tesla can brand the app and their vehicles, which could cause some last-minute delays if they have to rebrand.
Cybercab and Robovan/Robobus Trademarks
While Tesla is facing challenges with the broader Robotaxi term for vehicles, the company is also seeking to trademark “Cybercab,” “Robovan,” and “Robobus.” Securing a less descriptive name for the vehicle itself often has a higher chance of success with USPTO, as it is far more distinctive than a more general term like “robotaxi.”
Why Didn’t Tesla Do This Years Ago?
Tesla may have waited too long to file a trademark for the term “Robotaxi.” While the company has been discussing a self-driving fleet since 2016, the concept of autonomous taxis has gained a lot more traction in recent years — and competitors like Uber have also begun using the term.
We suspect there was some strategic timing behind these filings. Earlier versions of FSD — particularly those prior to V12 — may have lacked the progress needed to support Tesla’s robotaxi ambitions. Filing for a trademark that isn’t actively in use or about to be used can make it harder to defend or retain.
Moreover, while the idea of autonomous vehicles has been around for years, a clearer public understanding of Tesla’s specific plans has only emerged over the past 18 months. Filing too early can trigger speculation long before the company is ready to reveal details.
Ultimately, whether Tesla secures the rights to “Robotaxi” remains uncertain — but trademarks like “Cybercab” and “Robovan” seem much more likely to stick.
One of Tesla’s greatest weaknesses, as it has quickly become one of the world’s most ubiquitous cars on the planet has always been service. Escalating issues to managers and sometimes even reaching a Tesla Service employee can be a total coin flip, depending on your Service Center.
Tesla is continuing its push to integrate AI across its customer support channels in an effort to improve customer service. According to Raj Jegannathan, Tesla’s VP for IT, AI Infrastructure, Apps, Infosecurity, and Vehicle Service Operations (that’s a lot), Tesla is launching a pilot program for a new AI designed to improve customer interactions with Service.
Tesla Service’s new AI Agent detects comms delays, monitors sentiment, & auto-escalates to leaders. Starts tomorrow at 10 pilot locations. In 2 weeks, type “Escalate” in ‘message center’ to reach managers. Guardrails in place to prevent abuse. We’ll keep improving!
At 10 pilot service locations, this new AI agent will begin working behind the scenes at Tesla Service, to help with customer communications. It will provide three key features:
Detect Communications Delays: The AI will actively monitor service interactions to identify potential delays in communication or progress. These are often a key pain point for customers who reach out to Tesla Service and don’t receive a response for several days, as Service has nothing new to add. The AI can now step in and let the customer know Tesla is still waiting on parts or something else.
Monitor Customer Sentiment: By monitoring the tone and content of the messages between the customer and Service agents, Tesla will be able to identify situations where a customer might be dissatisfied or facing difficulties.
Auto-Escalate: If either a communications delay or negative sentiment is detected, the AI can automatically escalate issues to human managers for review. This helps to address problems before customers need to seek escalation themselves or become upset about an issue.
Customer Escalation Requests
Alongside the new AI tool, Tesla is also introducing a more direct way for customers to get higher-level attention. According to Tesla, within the next two weeks, customers can simply type “Escalate” in order to have their issue routed directly to management.
Raj’s team is currently working on implementing guardrails to prevent abuse, but this will soon make its way to improving Tesla’s service offerings. We’re glad to see Tesla taking steps to identify and correct deficiencies in the process - it has always been a sore tooth for Tesla in the last few years.
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