Tesla Expands FSD Beta v12.3; Autopilot Director Confirms Ability to Reverse is Coming Soon

By Kevin Armstrong
FSD Beta v12 is living up to hype
FSD Beta v12 is living up to hype
Not a Tesla App

Tesla's latest Full Self-Driving (FSD) Beta v12 is reaching users after an extended rollout over the weekend. This update is not just another iteration; it represents a leap in self-driving technology, primarily due to its integration of end-to-end neural networks for vehicle control. So far, it seems to be living up to the hype.

A Neural Network Driven Approach

At the core of FSD v12 is a shift from traditional programming to neural network-based decision-making. This allows the vehicle to process raw camera footage and vehicle kinematics directly into driving actions, mimicking human cognitive processes more closely than ever before. Ashok Elluswamy, Director of Autopilot Software at Tesla, highlighted the monumental effort to surpass the capabilities of the previous v11, setting a new standard for FSD's future.

Ability to Reverse Is Coming

The release has garnered widespread acclaim, with tech leaders like Michael Dell praising its capabilities and likening the car to human-like driving proficiency. Many in the Tesla community have been posting their weekend drivers, including Chuck Cook, who was amazed during one point of his drive, referring to a move as “Robo-taxi navigation.” Cook believed he was in too tight of a spot to pull a U-turn, but his Tesla pulled it off. Elluswamy commented: “Reverse coming soon when the Actually Smart Summon and the FSD models merge together over the next few releases.”

There were numerous examples of v12.3 navigating complex driving scenarios easily, showcasing significant improvements over earlier versions.

“Reverse coming soon when the Actually Smart Summon and the FSD models merge together over the next few releases.” - Ashok Elluswamy

Next-Level Capabilities on the Horizon

Elon Musk has teased that v12.4 will introduce even more advanced features, emphasizing the continuous improvement in training compute constraints. In fact, he was so thrilled with the next update that he said it could be called version 13. He posted that “V12.4 is another big jump in capabilities. Our constraint in training compute is much improved.”

Update 2023.44.30.25

FSD 12.3
Installed on 0% of fleet
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Last updated: Jul 29, 5:39 am UTC

Tesla’s FSD trajectory seems to be hitting a new level, as it appears to be headed toward approval of use on roadways in Europe. While it is taking longer than initially believed, the dream of autonomous driving seems to be getting closer to reality.

Tesla Plans Massive 10x Robotaxi Expansion: A Look at the Potential New Area

By Karan Singh
Not a Tesla App

With Tesla’s first major expansion of the Robotaxi Geofence now complete and operational, they’ve been hard at work with validation in new locations - and some are quite the drive from the current Austin Geofence.

Validation fleet vehicles have been spotted operating in a wider perimeter around the city, from rural roads in the west end to the more complex area closer to the airport. Tesla mentioned during their earnings call that the Robotaxi has already completed 7,000 miles in Austin, and it will expand its area of operation to roughly 10 times what it is now. This lines up with the validation vehicles we’ve been tracking around Austin.

Based on the spread of the new sightings, the potential next geofence could cover a staggering 450 square miles - a tenfold increase from the current service area of roughly 42 square miles. You can check this out in our map below with the sightings we’re tracking.

If Tesla decides to expand into these new areas, it would represent a tenfold increase over their current geofence, matching Tesla’s statement. The new area would cover approximately 10% of the 4,500-square-mile Austin metropolitan area. If Tesla can offer Robotaxi services in that entire area, it would prove they can tackle just about any city in the United States.

From Urban Core to Rural Roads

The locations of the validation vehicles show a clear intent to move beyond the initial urban and suburban core and prepare the Robotaxi service for a much wider range of uses.

In the west, validation fleet vehicles have been spotted as far as Marble Falls - a much more rural environment that features different road types, higher speed limits, and potentially different challenges. 

In the south, Tesla has been expanding towards Kyle, which is part of the growing Austin-San Antonio suburban corridor spanning Highway 35. San Antonio is only 80 miles (roughly a 90-minute drive) away, and could easily become part of the existing Robotaxi area if Tesla obtains regulatory approval there.

In the East, we haven’t spotted any new validation vehicles. This is likely because Tesla’s validation vehicles originate from Giga Texas, which is located East of Austin. We won’t really know if Tesla is expanding in this direction until they start pushing past Giga Texas and toward Houston.

Finally, there have been some validation vehicles spotted just North of the new expanded boundaries, meaning that Tesla isn’t done in that direction either. This direction consists of the largest suburban areas of Austin, which have so far not been serviced by any form of autonomous vehicle.

Rapid Scaling

This new, widespread validation effort confirms what we already know. Tesla is pushing for an intensive period of public data gathering and system testing in a new area, right before conducting geofence expansions. The sheer scale of this new validation zone tells us that Tesla isn’t taking this slowly - the next step is going to be a great leap instead, and they essentially confirmed this during this Q&A session on the recent call. The goal is clearly to bring the entire Austin Metropolitan area into the Robotaxi Network.

While the previous expansion showed off just how Tesla can scale the network, this new phase of validation testing is a demonstration of just how fast they can validate and expand their network. The move to validate across rural, suburban, and urban areas simultaneously shows their confidence in these new Robotaxi FSD builds.

Eventually, all these improvements from Robotaxi will make their way to customer FSD builds sometime in Q3 2025, so there is a lot to look forward to.

Caught on Video: Tesla FSD Tackles a Toll Booth — Here’s How It Pulled It Off

By Karan Singh
@DirtyTesLa on X

For years, the progress of Tesla’s FSD has been measured by smoother turns, better lane centering, and more confident unprotected left turns. But as the system matures, a new, more subtle form of intelligence is emerging - one that shifts its attention to the human nuances of navigating roads. A new video posted to X shows the most recent FSD build, V13.2.9, demonstrating this in a remarkable real-world scenario.

Toll Booth Magic

In the video, a Model Y running FSD pulls up to a toll booth and smoothly comes to a stop, allowing the driver to handle payment. The car waits patiently as the driver interacts with the attendant. Then, at the precise moment the toll booth operator finishes the transaction and says “Have a great day”, the vehicle starts moving, proceeding through the booth - all without any input from the driver.

If you notice, there’s no gate here at this toll booth. This interaction all happened naturally with FSD.

How It Really Works

While the timing was perfect, the FSD wasn’t listening to the conversation for clues (maybe one day, with Grok?) The reality, as explained by Ashok Elluswamy, Tesla’s VP of AI, is even more impressive.

FSD is simply using the cameras on the side of the vehicle to watch the exchange between the driver and attendant. The neural network has been trained on enough data that it can visually recognize the conclusion of a transaction - the exchange of money or a card and the hands pulling away - and understands that this is the trigger to proceed.

The Bigger Picture

This capability is far more significant than just a simple party trick. FSD is gaining the ability to perceive and navigate a world built for humans in the most human-like fashion possible.

If FSD can learn what a completed toll transaction looks like, it’s an example of the countless other complex scenarios it’ll be able to handle in the future. This same visual understanding could be applied to navigating a fast-food drive-thru, interacting with a parking garage attendant, passing through a security checkpoint, or boarding a ferry or vehicle train — all things we thought that would come much later.

These human-focused interactions will eventually become even more useful, as FSD becomes ever more confident in responding to humans on the road, like when a police officer tells a vehicle to go a certain direction, or a construction worker flags you through a site. These are real-world events that happen every day, and it isn’t surprising to see FSD picking up on the subtleties and nuances of human interaction.

This isn’t a pre-programmed feature for a specific toll booth. It is an emergent capability of the end-to-end AI neural nets. By learning from millions of videos across billions of miles, FSD is beginning to build a true contextual understanding of the world. The best part - with a 10x context increase on its way, this understanding will grow rapidly and become far more powerful.

These small, subtle moments of intelligence are the necessary steps to a truly robust autonomous system that can handle the messy, unpredictable nature of human society.

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