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Elon Musk says next FSD version to let drivers wear sunglasses
Tesla’s next version of Full Self-Driving (FSD) has been widely discussed in recent weeks, and a new update from CEO Elon Musk over the weekend highlights the fact that it won’t prevent drivers from wearing sunglasses anymore.
The FSD Supervised system uses a driver monitoring feature that makes sure drivers remain attentive and awake, though the system won’t allow the driver to wear sunglasses with the system engaged without nags. In response to one X user complaining about not being able to wear sunglasses while using FSD on Saturday, Musk wrote that the issue would be fixed in v12.5, to which many users in the thread expressed appreciation.
Should be fixed in 12.5
— Elon Musk (@elonmusk) July 21, 2024
Tesla FSD v12.4.1 with no nag starts rolling out to select customers
It’s still not clear exactly when Tesla plans to start deploying FSD Supervised v12.5.
Musk originally said that FSD v12.5 would be out in late June, and many are especially waiting for the update as it’s expected to finally bring FSD Supervised to the Cybertruck. Despite missing the late June target for the release, Musk has highlighted a handful of the other improvements in the version, as well as noting on Thursday that the release was in fact ready to hit the Cybertruck upon its deployment.
He also said this month that FSD Supervised v12.5 will finally merge the city and highway software stacks, as was previously done with v11, though it was apparently rolled back at some point with the arrival of v12.
Tesla started rolling out FSD Supervised v12.4.3 to some customers earlier this month, after previous versions had been delayed due to an extremely low level of interventions—and after the company essentially halted the rollout of v12.4.2.
Musk highlighted the issue of low interventions earlier this month.
The amount of testing time it takes to figure out if the new AI is better than the existing AI as measured by miles between interventions is the limiting factor on progress.
The better FSD gets the longer it takes to find interventions.
— Elon Musk (@elonmusk) July 12, 2024
He also detailed the problem during Tesla’s Annual Shareholder Meeting last month, explaining that the fewer interventions there are, the more difficult it becomes to test versions and point versions against each other to see which ones are performing best.
“And then, like I was saying earlier, it actually gets, as the system gets better, it gets harder to figure out which AI model is better, because now you know, like, ‘Okay, it’s thousands of miles between interventions.’
“How do we, as quickly as possible, figure out which AI model is better. And when you make these different AI models, they’re obviously not like super deterministic, so we have a new model that eliminates one problem but creates another problem. So we’re trying to solve this by a combination of simulation, uploading models, having them run in Shadow Mode.
“It’s actually kind of helpful that not everyone has Full Self-Driving, because we can see, we can run it in Shadow Mode and see, ‘What would this new model have done compared to what the user did?’
“So since we’ve got, you know, millions of cars that we can do this with, that gives us a delta between what the AI model predicted would do and the user would do. And if you kind of sum up the errors between them, you can see ‘Oh, there was a bigger error stack from this model versus that model,’ when you uploaded them into, each uploaded them into 100,000 cars.
“But that’s the biggest limiter right now. It’s not training, it’s not data, it’s actually testing the AI models. And then figuring out clever ways to figure out if a new model is better or not. Like there were sort of particular intersections that are difficult.”
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Tesla offers owners $1,000 off to upgrade from EAP to FSD in new car
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Elon Musk
Tesla AI Head says future FSD feature has already partially shipped
Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.
Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.
Back in October on the Q3 Earnings Call, Musk said:
“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”
Musk said in the same month:
“By v14.3, your car will feel like it is sentient.”
Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.
On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.
He added that “more and more reasoning will ship in Q1.”
🚨 Tesla’s Ashok Elluswamy reveals Nav decisions when encountering construction and parking options contain “some elements of reasoning”
More uses of reasoning will be shipped later this quarter, a big tidbit of info as we wait v14.3 https://t.co/jty8llgsKM
— TESLARATI (@Teslarati) January 9, 2026
Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).
Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
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Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.