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Tesla Autopilot and artificial intelligence: The unfair advantage
Serial tech entrepreneur and Tesla CEO Elon Musk has had a longstanding fear of artificial intelligence, but his company’s investments in artificial intelligence have been noted as an attempt to keep track of developments in the field of AI. In an interview for Vanity Fair in April 2017, he outright expressed his concerns with AI and claimed that one of the reasons for the development of SpaceX was that it could be an interplanetary escape route for humanity if artificial intelligence goes rogue. However, even Musk realizes the importance of AI in real-world applications, specifically for self-driving cars. At the end of June, Musk hired Andrej Karpathy as the new Director of Artificial Intelligence at Tesla, and MIT Technology Review claims it is the start of a plan to rethink automated driving at Tesla.
Karpathy comes from OpenAI, a non-profit company founded by Musk that focuses on “discovering and enacting the path to safe artificial general intelligence.” Afterwards, he moved on to intern at DeepMind, a place that spotlighted reinforcement learning with AI. Karpathy’s previous research focuses are on image understanding and recognition, which directly translates into applying proven image recognitions algorithms in Tesla’s Autopilot.
Recently, the popular question of morality was brought up in context to AI learning in Autopilot cars. It’s very interesting to consider how to teach technology to respond to an innately human moral problem. The Moral Machine, hosted by Massachusetts Institute of Technology, is a platform built to “gather human perspectives on moral decisions made by machine intelligence, such as self-driving cars.” It questions how the machine would act in human decisions such as whether to crash the driver or keep driving into a pedestrian that is crossing the street where there are no traffic regulators. How exactly do you teach a logical machine the mechanisms of ethical decision-making?
Although Musk and Tesla are the leaders in the self-driving field, a number of other companies are also entering into the competition sphere. Google, Uber, and Intel’s Mobileye have all been considering the application of reinforcement learning in the context of self-driving cars. Uber, Waymo, GM (Cruise Automation), Mobileye (camera supplier), Mercedes and Velodyne (LiDAR Supplier) could be potential competitors in the realm of self-driving vehicles. However, most of the technology does not encompass full self-driving, which is Musk’s aim. While other companies are investing heavily in autonomous fleets, Tesla far outpaces them in terms of data collection and release of finished product.
What are the differentiators for Tesla in the growing field of AI directed driverless cars?
Historically, Musk has focused on “narrow AI” which can enable the car to make decisions without driver interference. The vehicles would increasingly rely on radar as well as ultrasonic technology for sensing and data-gathering to form the basis for Tesla’s Autopilot algorithms. A technology that isn’t derived from LiDAR, the combination of radar and camera system said to outperform LiDAR especially in adverse weather conditions such as fog.
With the introduction of Autopilot 2.0 and Tesla’s “Vision” system, and billions of miles real-world driving data collected by Model S and Model X drivers, Tesla continues to create a detailed 3D map of the world that has increasingly finer resolution as more vehicles are purchased, delivered and placed onto roadways. The addition of GPS allows Tesla to put together a visual driving map for AI vehicles to follow, paving the path for newer and more advanced vehicles.
The addition of Karpathy will be a notable asset for Tesla’s Autopilot team. In specific, the team will be able to apply Karpathy’s deep knowledge of reinforcement learning systems. Reinforcement learning for AI is similar to teaching animals via repetition of a behavior until a positive outcome is yielded. This type of machine learning will allow Tesla Autopilot to navigate complex and challenging scenarios. For example, AI will allow cars to determine in real-time how to navigate a four-way stop, a busy intersection or other difficult situations present on city streets. By making cars smarter with the way they navigate drivers, Tesla will put itself ahead of the curve with a fully-thinking, fully self-driving car.
Tesla is expected to demonstrate a fully autonomous cross-country drive from California to New York by the end of this year as a showcase for its upcoming Full Self-driving Capability. If you’re buying a Tesla Model 3, or an existing Model S or Model X owner, just know that you’re contributing to a self-driving future, mile by mile.
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Tesla winter weather test: How long does it take to melt 8 inches of snow?
In Pennsylvania, we got between 10 and 12 inches of snow over the weekend as a nasty Winter storm ripped through a large portion of the country, bringing snow to some areas and nasty ice storms to others.
I have had a Model Y Performance for the week courtesy of Tesla, which got the car to me last Monday. Today was my last full day with it before I take it back to my local showroom, and with all the accumulation on it, I decided to run a cool little experiment: How long would it take for Tesla’s Defrost feature to melt 8 inches of snow?
Tesla’s Defrost feature is one of the best and most underrated that the car has in its arsenal. While every car out there has a defrost setting, Tesla’s can be activated through the Smartphone App and is one of the better-performing systems in my opinion.
It has come in handy a lot through the Fall and Winter, helping clear up my windshield more efficiently while also clearing up more of the front glass than other cars I’ve owned.
The test was simple: don’t touch any of the ice or snow with my ice scraper, and let the car do all the work, no matter how long it took. Of course, it would be quicker to just clear the ice off manually, but I really wanted to see how long it would take.
Tesla Model Y heat pump takes on Model S resistive heating in defrosting showdown
Observations
I started this test at around 10:30 a.m. It was still pretty cloudy and cold out, and I knew the latter portion of the test would get some help from the Sun as it was expected to come out around noon, maybe a little bit after.
I cranked it up and set my iPhone up on a tripod, and activated the Time Lapse feature in the Camera settings.
The rest of the test was sitting and waiting.
It didn’t take long to see some difference. In fact, by the 20-minute mark, there was some notable melting of snow and ice along the sides of the windshield near the A Pillar.
However, this test was not one that was “efficient” in any manner; it took about three hours and 40 minutes to get the snow to a point where I would feel comfortable driving out in public. In no way would I do this normally; I simply wanted to see how it would do with a massive accumulation of snow.
It did well, but in the future, I’ll stick to clearing it off manually and using the Defrost setting for clearing up some ice before the gym in the morning.
Check out the video of the test below:
❄️ How long will it take for the Tesla Model Y Performance to defrost and melt ONE FOOT of snow after a blizzard?
Let’s find out: pic.twitter.com/Zmfeveap1x
— TESLARATI (@Teslarati) January 26, 2026
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Tesla Robotaxi ride-hailing without a Safety Monitor proves to be difficult
Tesla Robotaxi ride-hailing without a Safety Monitor is proving to be a difficult task, according to some riders who made the journey to Austin to attempt to ride in one of its vehicles that has zero supervision.
Last week, Tesla officially removed Safety Monitors from some — not all — of its Robotaxi vehicles in Austin, Texas, answering skeptics who said the vehicles still needed supervision to operate safely and efficiently.
BREAKING: Tesla launches public Robotaxi rides in Austin with no Safety Monitor
Tesla aimed to remove Safety Monitors before the end of 2025, and it did, but only to company employees. It made the move last week to open the rides to the public, just a couple of weeks late to its original goal, but the accomplishment was impressive, nonetheless.
However, the small number of Robotaxis that are operating without Safety Monitors has proven difficult to hail for a ride. David Moss, who has gained notoriety recently as the person who has traveled over 10,000 miles in his Tesla on Full Self-Driving v14 without any interventions, made it to Austin last week.
He has tried to get a ride in a Safety Monitor-less Robotaxi for the better part of four days, and after 38 attempts, he still has yet to grab one:
Wow just wow!
It’s 8:30PM, 29° out ice storm hailing & Tesla Robotaxi service has turned back on!
Waymo is offline & vast majority of humans are home in the storm
Ride 38 was still supervised but by far most impressive yet pic.twitter.com/1aUnJkcYm8
— David Moss (@DavidMoss) January 25, 2026
Tesla said last week that it was rolling out a controlled test of the Safety Monitor-less Robotaxis. Ashok Elluswamy, who heads the AI program at Tesla, confirmed that the company was “starting with a few unsupervised vehicles mixed in with the broader Robotaxi fleet with Safety Monitors,” and that “the ratio will increase over time.”
This is a good strategy that prioritizes safety and keeps the company’s controlled rollout at the forefront of the Robotaxi rollout.
However, it will be interesting to see how quickly the company can scale these completely monitor-less rides. It has proven to be extremely difficult to get one, but that is understandable considering only a handful of the cars in the entire Austin fleet are operating with no supervision within the vehicle.
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Tesla gives its biggest hint that Full Self-Driving in Europe is imminent
Tesla has given its biggest hint that Full Self-Driving in Europe is imminent, as a new feature seems to show that the company is preparing for frequent border crossings.
Tesla owner and influencer BLKMDL3, also known as Zack, recently took his Tesla to the border of California and Mexico at Tijuana, and at the international crossing, Full Self-Driving showed an interesting message: “Upcoming country border — FSD (Supervised) will become unavailable.”
FSD now shows a new message when approaching an international border crossing.
Stayed engaged the whole way as we crossed the border and worked great in Mexico! pic.twitter.com/bDzyLnyq0g
— Zack (@BLKMDL3) January 26, 2026
Due to regulatory approvals, once a Tesla operating on Full Self-Driving enters a new country, it is required to comply with the laws and regulations that are applicable to that territory. Even if legal, it seems Tesla will shut off FSD temporarily, confirming it is in a location where operation is approved.
This is something that will be extremely important in Europe, as crossing borders there is like crossing states in the U.S.; it’s pretty frequent compared to life in America, Canada, and Mexico.
Tesla has been working to get FSD approved in Europe for several years, and it has been getting close to being able to offer it to owners on the continent. However, it is still working through a lot of the red tape that is necessary for European regulators to approve use of the system on their continent.
This feature seems to be one that would be extremely useful in Europe, considering the fact that crossing borders into other countries is much more frequent than here in the U.S., and would cater to an area where approvals would differ.
Tesla has been testing FSD in Spain, France, England, and other European countries, and plans to continue expanding this effort. European owners have been fighting for a very long time to utilize the functionality, but the red tape has been the biggest bottleneck in the process.
Tesla Europe builds momentum with expanding FSD demos and regional launches
Tesla operates Full Self-Driving in the United States, China, Canada, Mexico, Puerto Rico, Australia, New Zealand, and South Korea.

