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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News
NVIDIA Director of Robotics: Tesla FSD v14 is the first AI to pass the “Physical Turing Test”
After testing FSD v14, Fan stated that his experience with FSD felt magical at first, but it soon started to feel like a routine.
NVIDIA Director of Robotics Jim Fan has praised Tesla’s Full Self-Driving (Supervised) v14 as the first AI to pass what he described as a “Physical Turing Test.”
After testing FSD v14, Fan stated that his experience with FSD felt magical at first, but it soon started to feel like a routine. And just like smartphones today, removing it now would “actively hurt.”
Jim Fan’s hands-on FSD v14 impressions
Fan, a leading researcher in embodied AI who is currently solving Physical AI at NVIDIA and spearheading the company’s Project GR00T initiative, noted that he actually was late to the Tesla game. He was, however, one of the first to try out FSD v14.
“I was very late to own a Tesla but among the earliest to try out FSD v14. It’s perhaps the first time I experience an AI that passes the Physical Turing Test: after a long day at work, you press a button, lay back, and couldn’t tell if a neural net or a human drove you home,” Fan wrote in a post on X.
Fan added: “Despite knowing exactly how robot learning works, I still find it magical watching the steering wheel turn by itself. First it feels surreal, next it becomes routine. Then, like the smartphone, taking it away actively hurts. This is how humanity gets rewired and glued to god-like technologies.”
The Physical Turing Test
The original Turing Test was conceived by Alan Turing in 1950, and it was aimed at determining if a machine could exhibit behavior that is equivalent to or indistinguishable from a human. By focusing on text-based conversations, the original Turing Test set a high bar for natural language processing and machine learning.
This test has been passed by today’s large language models. However, the capability to converse in a humanlike manner is a completely different challenge from performing real-world problem-solving or physical interactions. Thus, Fan introduced the Physical Turing Test, which challenges AI systems to demonstrate intelligence through physical actions.
Based on Fan’s comments, Tesla has demonstrated these intelligent physical actions with FSD v14. Elon Musk agreed with the NVIDIA executive, stating in a post on X that with FSD v14, “you can sense the sentience maturing.” Musk also praised Tesla AI, calling it the best “real-world AI” today.
News
Tesla AI team burns the Christmas midnight oil by releasing FSD v14.2.2.1
The update was released just a day after FSD v14.2.2 started rolling out to customers.
Tesla is burning the midnight oil this Christmas, with the Tesla AI team quietly rolling out Full Self-Driving (Supervised) v14.2.2.1 just a day after FSD v14.2.2 started rolling out to customers.
Tesla owner shares insights on FSD v14.2.2.1
Longtime Tesla owner and FSD tester @BLKMDL3 shared some insights following several drives with FSD v14.2.2.1 in rainy Los Angeles conditions with standing water and faded lane lines. He reported zero steering hesitation or stutter, confident lane changes, and maneuvers executed with precision that evoked the performance of Tesla’s driverless Robotaxis in Austin.
Parking performance impressed, with most spots nailed perfectly, including tight, sharp turns, in single attempts without shaky steering. One minor offset happened only due to another vehicle that was parked over the line, which FSD accommodated by a few extra inches. In rain that typically erases road markings, FSD visualized lanes and turn lines better than humans, positioning itself flawlessly when entering new streets as well.
“Took it up a dark, wet, and twisty canyon road up and down the hill tonight and it went very well as to be expected. Stayed centered in the lane, kept speed well and gives a confidence inspiring steering feel where it handles these curvy roads better than the majority of human drivers,” the Tesla owner wrote in a post on X.
Tesla’s FSD v14.2.2 update
Just a day before FSD v14.2.2.1’s release, Tesla rolled out FSD v14.2.2, which was focused on smoother real-world performance, better obstacle awareness, and precise end-of-trip routing. According to the update’s release notes, FSD v14.2.2 upgrades the vision encoder neural network with higher resolution features, enhancing detection of emergency vehicles, road obstacles, and human gestures.
New Arrival Options also allowed users to select preferred drop-off styles, such as Parking Lot, Street, Driveway, Parking Garage, or Curbside, with the navigation pin automatically adjusting to the ideal spot. Other refinements include pulling over for emergency vehicles, real-time vision-based detours for blocked roads, improved gate and debris handling, and Speed Profiles for customized driving styles.
Elon Musk
Elon Musk’s Grok records lowest hallucination rate in AI reliability study
Grok achieved an 8% hallucination rate, 4.5 customer rating, 3.5 consistency, and 0.07% downtime, resulting in an overall risk score of just 6.
A December 2025 study by casino games aggregator Relum has identified Elon Musk’s Grok as one of the most reliable AI chatbots for workplace use, boasting the lowest hallucination rate at just 8% among the 10 major models tested.
In comparison, market leader ChatGPT registered one of the highest hallucination rates at 35%, just behind Google’s Gemini, which registered a high hallucination rate of 38%. The findings highlight Grok’s factual prowess despite the AI model’s lower market visibility.
Grok tops hallucination metric
The research evaluated chatbots on hallucination rate, customer ratings, response consistency, and downtime rate. The chatbots were then assigned a reliability risk score from 0 to 99, with higher scores indicating bigger problems.
Grok achieved an 8% hallucination rate, 4.5 customer rating, 3.5 consistency, and 0.07% downtime, resulting in an overall risk score of just 6. DeepSeek followed closely with 14% hallucinations and zero downtime for a stellar risk score of 4. ChatGPT’s high hallucination and downtime rates gave it the top risk score of 99, followed by Claude and Meta AI, which earned reliability risk scores of 75 and 70, respectively.

Why low hallucinations matter
Relum Chief Product Officer Razvan-Lucian Haiduc shared his thoughts about the study’s findings. “About 65% of US companies now use AI chatbots in their daily work, and nearly 45% of employees admit they’ve shared sensitive company information with these tools. These numbers show well how important chatbots have become in everyday work.
“Dependence on AI tools will likely increase even more, so companies should choose their chatbots based on how reliable and fit they are for their specific business needs. A chatbot that everyone uses isn’t necessarily the one that works best for your industry or gives accurate answers for your tasks.”
In a way, the study reveals a notable gap between AI chatbots’ popularity and performance, with Grok’s low hallucination rate positioning it as a strong choice for accuracy-critical applications. This was despite the fact that Grok is not used as much by users, at least compared to more mainstream AI applications such as ChatGPT.