Tesla owners are no stranger to aftermarket modifications. Whether they are performance-based or cosmetic, owners of the electric vehicles are always looking for ways to set their cars apart from the others. While the cosmetic modifications are usually pretty simple because they only change the appearance of a vehicle, the performance adjustments are a bit more complicated because they completely revise the way the system operates. Tesla decided to put a stop to the performance revisions altogether by releasing a software update that would inhibit the simple plug-in systems from functioning correctly.
Thinking about it, it reminded me of a previous newsletter that I wrote a few months ago. I talked about how Tesla was blocking salvaged vehicles from Supercharging in an attempt to make them less appealing to those who were interested in buying them and fixing them up for a discounted price. While it was a great project for some people, Tesla had to realize that salvaged vehicles are rarely fixed “perfectly” and that they usually have some small issues even after they are deemed to be functional. Tesla had to think about themselves first, and for a good reason. If someone were to crash a salvaged Tesla that was not wholly “fixed,” it would be blamed on them and not on the person who attempted to repair the vehicle. The headlines would blame the company, and it would add to a long list of misunderstandings with Tesla’s cars. It was merely smarter for them to try and make the vehicles less appealing through no Supercharging.
Tesla, when you think about it, really had to do the same thing with these aftermarket upgrades. While the company released a $2,000 Acceleration Boost for the Model 3 a few months back, they have ultimate control over what the vehicle’s new capabilities are. They decide how much extra horsepower to give the car, and how much speed the car should be capable of. This puts the risk into the company’s hands as much as the driver’s hands.
If a third-party company comes along and decides to manufacture a simple plug-in that will take the performance of a Tesla to new heights, it is sure to attract some buyers. Owners of the Performance variants of the car are surely going to be more interested in upping the already lightning-fast speeds the vehicle is capable of. While this is all good and fun for the owners, Tesla, as a company, assumes a lot of risks, and it is only reasonable to think that stopping it is the best strategy.
Think about a scenario here: Imagine a Tesla Model 3 Performance owner deciding that what their car is capable of is not enough anymore. They decide to go online and purchase a plug-in for their Model 3 that will increase acceleration and top speed, and they choose to put it to the test one evening. While traveling at speeds over 130 MPH, the driver loses control of the car and crashes into another vehicle, hurting someone in the car.
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The first thing that is synonymous with Teslas and car accidents is the overwhelming flood of people who immediately think the car was on Autopilot. Mainstream media outlets will talk about how the car could have been traveling on Autopilot and TSLAQ will immediately eat it up without any confirmation. The NHTSA would be the only agency that would be able to tell if the car was traveling on Autopilot through an investigation. However, that could take days, weeks, or even months to happen.
Then, you’d have some people complaining about Tesla’s performance standards, and why some of their cars equip unnecessary amounts of speed and acceleration. Not that it is anyone’s business, but when someone buys a car because it is fast, they more than likely know that they are putting themselves at risk, especially if they chose to drive it quickly. This argument would more than likely be small and not based off of much logic, to begin with, because fast cars exist everywhere and every car company makes them in some form or another.
However, Tesla would have to deal with the issues and speculation that would suggest that their cars are too fast for the owner’s good. The company is already under a microscope because every time a Tesla is in an accident, it seems like someone somewhere is talking about it.
These aftermarket plug-ins are also tricky because while the company that makes them probably knows what they are capable of, they are not entirely “compatible” with a Tesla powertrain to begin with. Only Tesla knows everything that goes into their cars and the software that helps them function. There really isn’t much of a reason to gamble on ruining the powertrain of a Tesla all for a few extra miles per hour, but that is just me. I would think that it is too much of a risk, and I wouldn’t want my hard-earned money going to waste, especially if a plug-in can compromise the way my vehicle works.
I think the update to keep these plug-ins from functioning is entirely understandable. Tesla is playing damage control. Ultimately, anything that happens to malfunction on the plug-in, or if the driver were to make an error and it would result in an accident, the blame would go onto Tesla.
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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.”
News
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.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
