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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.
Tesla has stunned by gaining yet another approval for its Full Self-Driving suite in Europe, its second in two days and its fifth overall.
Belgium will be the latest country to allow Tesla owners to utilize FSD on public roads in Europe, joining a quickly growing list that started with the Netherlands, Lithuania, and Estonia.
On Tuesday, Denmark announced its approval of the FSD suite, which has now been followed by Belgium just one day later.
The country’s Minister of Mobility, Annick De Ridder, announced the approval on her X account, stating that she had just signed the approval of Tesla FSD. It now goes to the country’s homologation department for the last step of the approval process.
De @Tesla community houdt hier al geruime tijd de vinger aan de pols over de toelating voor de FSD-technologie op onze Vlaamse en Belgische wegen.
Uit waardering voor jullie niet-aflatende interesse (en aanmoediging 😉), krijgen jullie hierbij de primeur: ik heb net de toelating… pic.twitter.com/Yrps4OHTj8— Annick De Ridder (@AnnickDeRidder) June 10, 2026
The Belgian approval is one of mighty importance because it truly shows how quickly countries in Europe could greenlight the FSD suite consecutively. Approvals are already coming in relatively quickly, which is a great sign.
Perhaps the next big development that could come from FSD approvals in Europe is an approval from a country like England, Italy, France, Spain, or Germany. It would be something to see how FSD would perform in a major European metro, such as London, Barcelona, Madrid, Paris, Rome, or Berlin.
Getting Full Self-Driving in Spain and England will be such huge milestones for Tesla. I am so excited to see how FSD performs in Madrid, Barcelona, and London, specifically.
The ultimate test will always be Mumbai or New Delhi. Excited for India’s eventual approval! https://t.co/paw9Ch1qmL pic.twitter.com/9RdDERVSSJ
— TESLARATI (@Teslarati) June 9, 2026
Full Self-Driving does an excellent job of roaming around major U.S. cities like New York and Los Angeles, but other high-profile international cities of significance would truly mark a line in the sand for Tesla, which can simply enable any vehicle in its customer-owned fleet to run FSD with the correct approvals.
SpaceX CEO Elon Musk recently confronted worries about orbital data centers and launching satellites in mass quantities in space, as some voiced concerns about crowding.
Musk’s SpaceX plans to combat the issue of needing data centers by launching them into space instead of taking up valuable real estate on Earth. It has been a major point of SpaceX’s future, including its looming IPO, which could be the largest ever.
In a recent interview filmed at SpaceX’s Starlink terminal factory in Bastrop, Texas, Elon Musk directly addressed concerns that deploying large numbers of AI satellites for orbital data centers could crowd Earth’s orbit. His message was straightforward and reassuring: space is vast beyond human intuition.
“Space is really big,” Musk said. “It’s not like space is gonna get crowded. Space is enormous. If you actually look at it relative to the Earth, the satellites are so tiny you can’t even see them.” He emphasized that even zooming in makes a satellite appear large, but from a planetary perspective, they are minuscule specks.
Elon on concerns that AI satellites will crowd space:
“Space is really big. It’s not like space is gonna get crowded. Space is enormous. If you actually look at it relative to the earth, the satellites are so tiny you can’t even see them.” https://t.co/Mvr7NpL25Q pic.twitter.com/5Fi629Rii7
— Sawyer Merritt (@SawyerMerritt) June 8, 2026
Musk pointed to SpaceX’s real-world experience operating roughly 10,000 Starlink satellites as evidence that large constellations can be managed safely. “We’ve got a pretty good idea of how to operate just really large constellations and do it safely,” he noted. SpaceX remains the only operator with meaningful experience at this scale, giving the company unique insight into tight orbital packing without compromising safety
The discussion highlighted SpaceX’s plans for “AI1” satellites—essentially orbiting racks of AI compute powered by massive solar arrays and cooled via radiative panels in space’s vacuum.
These satellites leverage proven Starlink V3 technology, making them simpler to design than communications satellites. A first-generation unit targets around 150 kW peak power, with a 70-meter wingspan for solar panels and radiators. Laser links will connect them to each other and the Starlink network, delivering low-latency access (on the order of a few milliseconds from low-Earth orbit).
FCC accepts SpaceX filing for 1 million orbital data center plan
Musk framed orbital data centers as a practical solution to Earth’s constraints on AI growth. Ground-based facilities face power shortages, water demands for cooling, and grid limitations. In space, constant sunlight (no day-night cycle), vacuum radiative cooling, and abundant solar energy offer clear advantages.
Production will ramp up at an expanded “Gigasat” factory in Bastrop, with solar manufacturing already underway and full AI satellite output expected at reasonable volume by the end of 2027. Starship’s rapid, high-volume launch capability, aiming for multiple flights per hour, will make massive deployment feasible.
Critics sometimes raise risks like space debris or Kessler syndrome, but Musk’s response underscores scale: even a million satellites would represent an imperceptible fraction of available orbital volume when viewed against Earth’s size. SpaceX’s automated collision avoidance and deorbiting designs for Starlink further mitigate concerns.
This vision ties into broader ambitions. Musk sees orbital AI compute as a step toward harnessing more of the Sun’s energy, advancing humanity on the Kardashev scale from a Type 0 civilization toward Type 1 and eventually Type 2. By moving power-hungry data centers off-planet, SpaceX aims to unlock orders-of-magnitude more compute while preserving Earth’s resources.
Musk’s comments should ease public anxiety. With proven operational expertise, incremental engineering, and the immensity of space itself, orbital data centers represent not overcrowding, but smart expansion into the final frontier.
Tesla Full Self-Driving (Supervised) is currently listed as a Level 2 suite in terms of its passenger cars. As its Robotaxi platform continues to move quickly, it has been recognized as a Level 4 ride-sharing program by the State of Texas, as Tesla recently self-certified itself.
However, a Wall Street analyst is arguing that Tesla (NASDAQ: TSLA) has effectively achieved Level 4 autonomy in most conditions in all of its vehicles, drawing on personal experience and data released by the company.
Alex Potter of Piper Sandler said in a note to investors on Wednesday that “Tesla has solved the self-driving puzzle,” pointing to decisions to offer insurance discounts for FSD-enabled policies as a signal of confidence, which is backed up by stellar safety records compared to human driving.
Investing.com initially reported on Potter’s new note.
Additionally, Potter looks at the recent start of Cybercab production at Giga Texas as a potential indication that Tesla is ready to offer some level of unsupervised driving at least in the near future. The Cybercab has no steering wheel or pedals, completely eliminating the ability for human input.
He also sees Tesla’s allocation of “several hundred million USD (if not $1B+)” as confidence internally, seeing as it would be tough to set aside that amount of capital toward a project that the company does not see as relatively near-term.
Forward thinking, especially as Cybercab has no human controls, it would make sense that Tesla is at least close to self-driving. How close is another question.
Tesla has routinely teased that unsupervised FSD is close, but there are still a lot of things it feels as if the company has to roll out some more capability, including unsupervised parking features, known as “Banish,” better operation with regional self-driving performance, and other improvements.
That is not to say that Tesla FSD is super impressive already. It has already completed coast-to-coast drives across the United States and Canada, it routinely takes the stress out of driving for most people, and it has proven through Tesla Safety Reports that it is safer and involved in accidents less frequently than humans.
🚨 These are the first-ever FSD safety statistics out of the Netherlands, showing it was over 3.5x safer than human driving on Dutch roads.
The most recent numbers out of Tesla for North America show:
-Over 5.5 million miles between accidents for Teslas using FSD
-660k miles… https://t.co/XKlRzgSGEh pic.twitter.com/HX6kzh0ZKc— TESLARATI (@Teslarati) June 9, 2026
Even Potter believes it is capable, as he used it to go from Missoula, Montana, to Minneapolis, Minnesota, back in April.
“There’s no substitute for personal experience,” he wrote.
Tesla stuns with another FSD approval in Europe, its second in two days
SpaceX’s Elon Musk relieves worries about orbital data centers
