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Tesla FSD Beta V11.3 starts shipping to employees (Release Notes)

Credit: Drive in EV/Twitter

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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.

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. 

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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.

Maria--aka "M"-- is an experienced writer and book editor. She's written about several topics including health, tech, and politics. As a book editor, she's worked with authors who write Sci-Fi, Romance, and Dark Fantasy. M loves hearing from TESLARATI readers. If you have any tips or article ideas, contact her at maria@teslarati.com or via X, @Writer_01001101.

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Tesla called ‘biggest meme stock we’ve ever seen’ by Yale associate dean

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Credit: Tesla

Tesla (NASDAQ: TSLA) is being called “the biggest meme stock we’ve ever seen” by Yale School of Management Senior Associate Dean Jeff Sonnenfeld, who made the comments in a recent interview with CNBC.

Sonnenfeld’s comments echo those of many of the company’s skeptics, who argue that its price-to-earnings ratio is far too high when compared to other companies also in the tech industry. Tesla is often compared to companies like Apple, Nvidia, and Microsoft when these types of discussions come up.

Fundamentally, yes, Tesla does trade at a P/E level that is significantly above that of any comparable company.

However, it is worth mentioning that Tesla is not traded like a typical company, either.

Here’s what Sonnenfeld said regarding Tesla:

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“This is the biggest meme stock we’ve ever seen. Even at its peak, Amazon was nowhere near this level. The PE on this, well above 200, is just crazy. When you’ve got stocks like Nvidia, the price-earnings ratio is around 25 or 30, and Apple is maybe 35 or 36, Microsoft around the same. I mean, this is way out of line to be at a 220 PE. It’s crazy, and they’ve, I think, put a little too much emphasis on the magic wand of Musk.”

Many analysts have admitted in the past that they believe Tesla is an untraditional stock in the sense that many analysts trade it based on narrative and not fundamentals. Ryan Brinkman of J.P. Morgan once said:

“Tesla shares continue to strike us as having become completely divorced from the fundamentals.”

Dan Nathan, another notorious skeptic of Tesla shares, recently turned bullish on the stock because of “technicals and sentiment.” He said just last week:

“I think from a trading perspective, it looks very interesting.”

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Nathan said Tesla shares show signs of strength moving forward, including holding its 200-day moving average and holding against current resistance levels.

Sonnenfeld’s synopsis of Tesla shares points out that there might be “a little too much emphasis on the magic wand of Musk.”

Elon Musk just bought $1 billion in Tesla stock, his biggest purchase ever

This could refer to different things: perhaps his recent $1 billion stock buy, which sent the stock skyrocketing, or the fact that many Tesla investors are fans and owners who do not buy and sell on numbers, but rather on news that Musk might report himself.

Tesla is trading around $423.76 at the time of publication, as of 3:25 p.m. on the East Coast.

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Tesla makes big change to Full Self-Driving doghouse that drivers will like

Now, it is changing the timeframe of which strikes will be removed, cutting it in half. The strikes will be removed every 3.5 days, as long as no strikes are received during the time period.

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Tesla's Cabin-facing camera is used to monitor driver attentiveness. (Credit: Andy Slye/YouTube)

Tesla is making a big change to its Full Self-Driving doghouse that drivers will like.

The doghouse is a hypothetical term used to describe the penalty period that Tesla applies to drivers who receive too many infractions related to distracted driving.

Previously, Tesla implemented a seven-day ban on the use of Full Self-Driving for those who received five strikes in a vehicle equipped with a cabin camera and three strikes for those without a cabin camera.

It also forgave one strike per week of Full Self-Driving use, provided the driver did not receive any additional strikes during the seven-day period.

Now, it is changing the timeframe of which strikes will be removed, cutting it in half. The strikes will be removed every 3.5 days, as long as no strikes are received during the time period.

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The change was found by Not a Tesla App, which noticed the adjustment in the Owner’s Manual for the 2025.32 Software Update.

The system undoubtedly helps improve safety as it helps keep drivers honest. However, there are definitely workarounds, which people are using and promoting for monetary gain, and you can find them on basically any online marketplace, including TikTok shop and Amazon:

People are marketing the product as an FSD cheat device, which the cabin-facing camera will not be able to detect, allowing you to watch something on a phone or look through the windshield at the road.

The safeguards implemented by Tesla are designed to protect drivers from distractions and also protect the company itself from liability. People are still using Full Self-Driving as if it were a fully autonomous product, and it is not.

Tesla even says that the driver must pay attention and be ready to take over in any scenario:

“Yes. Autopilot is a driver assistance system that is intended to be used only with a fully attentive driver. It does not turn a Tesla into a fully autonomous vehicle.

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Before enabling Autopilot, you must agree to “keep your hands on the steering wheel at all times” and to always “maintain control and responsibility for your vehicle.” Once engaged, Autopilot will also deliver an escalating series of visual and audio warnings, reminding you to place your hands on the wheel if insufficient torque is applied or your vehicle otherwise detects you may not be attentive enough to the road ahead. If you repeatedly ignore these warnings, you will be locked out from using Autopilot during that trip.

You can override any of Autopilot’s features at any time by steering or applying the accelerator at any time.”

It is good that Tesla is rewarding those who learn from their mistakes with this shorter timeframe to lose the strikes. It won’t be needed forever, though, as eventually, the company will solve autonomy. The question is: when?

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Elon Musk teases the capabilities of the Tesla Roadster once again

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Elon Musk has once again teased the capabilities of the Tesla Roadster, fueling the anticipation that many have for the vehicle, despite it still having no public production or delivery date.

The Roadster is among the most anticipated vehicles in the automotive sector currently, and as Tesla has teased its capabilities, from a lightning-fast 1.1-second 0-60 MPH acceleration to potential hovering with cold-gas thrusters, people are eager to see it.

Although the design seemed to be finalized, there was still more work to be done. Earlier this year, as Tesla was showcasing some of the Roadster’s capabilities to Musk, he stated that it was capable of even more.

This pushed back its production date even further, much to the chagrin of those who have been waiting years for it.

Musk continues to tease us all, and as we sit here waiting hopelessly for it to be revealed, he said today that it is “something special beyond a car.”

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Musk’s words were in response to a video posted by Tesla China, showing the Roadster in a new promotional video created by a fan.

The Roadster was planned to be released in 2020, but here we are in 2025, and there is still no sign of the vehicle entering production. However, Tesla did say earlier this year that it would host a demo event for the Roadster, where the company would showcase its capabilities.

Lars Moravy said earlier this year:

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“Roadster is definitely in development. We did talk about it last Sunday night. We are gearing up for a super cool demo. It’s going to be mind-blowing; We showed Elon some cool demos last week of the tech we’ve been working on, and he got a little excited.”

Tesla exec gives big update on Roadster, confirming recent rumor

The delays have been attributed to “radically increased design goals” for the vehicle, which have, without a doubt, improved its capabilities, but at the same time, we just want to know if it’s ever going to come.

Tesla can always make it “better,” but at what point do you say, “Okay, it’s time to show this thing off.” They could always build another, even more capable supercar in the next ten years.

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