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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 FSD fleet is nearing 7 billion total miles, including 2.5 billion city miles
As can be seen on Tesla’s official FSD webpage, vehicles equipped with the system have now navigated over 6.99 billion miles.
Tesla’s Full Self-Driving (Supervised) fleet is closing in on almost 7 billion total miles driven, as per data posted by the company on its official FSD webpage.
These figures hint at the massive scale of data fueling Tesla’s rapid FSD improvements, which have been quite notable as of late.
FSD mileage milestones
As can be seen on Tesla’s official FSD webpage, vehicles equipped with the system have now navigated over 6.99 billion miles. Tesla owner and avid FSD tester Whole Mars Catalog also shared a screenshot indicating that from the nearly 7 billion miles traveled by the FSD fleet, more than 2.5 billion miles were driven inside cities.
City miles are particularly valuable for complex urban scenarios like unprotected turns, pedestrian interactions, and traffic lights. This is also the difference-maker for FSD, as only complex solutions, such as Waymo’s self-driving taxis, operate similarly on inner-city streets. And even then, incidents such as the San Francisco blackouts have proven challenging for sensor-rich vehicles like Waymos.
Tesla’s data edge
Tesla has a number of advantages in the autonomous vehicle sector, one of which is the size of its fleet and the number of vehicles training FSD on real-world roads. Tesla’s nearly 7 billion FSD miles then allow the company to roll out updates that make its vehicles behave like they are being driven by experienced drivers, even if they are operating on their own.
So notable are Tesla’s improvements to FSD that NVIDIA Director of Robotics Jim Fan, after experiencing FSD v14, noted that the system is the first AI that passes what he described as a “Physical Turing Test.”
“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,” Fan wrote in a post on X.
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Tesla starts showing how FSD will change lives in Europe
Local officials tested the system on narrow country roads and were impressed by FSD’s smooth, human-like driving, with some calling the service a game-changer for everyday life in areas that are far from urban centers.
Tesla has launched Europe’s first public shuttle service using Full Self-Driving (Supervised) in the rural Eifelkreis Bitburg-Prüm region of Germany, demonstrating how the technology can restore independence and mobility for people who struggle with limited transport options.
Local officials tested the system on narrow country roads and were impressed by FSD’s smooth, human-like driving, with some calling the service a game-changer for everyday life in areas that are far from urban centers.
Officials see real impact on rural residents
Arzfeld Mayor Johannes Kuhl and District Administrator Andreas Kruppert personally tested the Tesla shuttle service. This allowed them to see just how well FSD navigated winding lanes and rural roads confidently. Kruppert said, “Autonomous driving sounds like science fiction to many, but we simply see here that it works totally well in rural regions too.” Kuhl, for his part, also noted that FSD “feels like a very experienced driver.”
The pilot complements the area’s “Citizen Bus” program, which provides on-demand rides for elderly residents who can no longer drive themselves. Tesla Europe shared a video of a demonstration of the service, highlighting how FSD gives people their freedom back, even in places where public transport is not as prevalent.
What the Ministry for Economic Affairs and Transport says
Rhineland-Palatinate’s Minister Daniela Schmitt supported the project, praising the collaboration that made this “first of its kind in Europe” possible. As per the ministry, the rural rollout for the service shows FSD’s potential beyond major cities, and it delivers tangible benefits like grocery runs, doctor visits, and social connections for isolated residents.
“Reliable and flexible mobility is especially vital in rural areas. With the launch of a shuttle service using self-driving vehicles (FSD supervised) by Tesla in the Eifelkreis Bitburg-Prüm, an innovative pilot project is now getting underway that complements local community bus services. It is the first project of its kind in Europe.
“The result is a real gain for rural mobility: greater accessibility, more flexibility and tangible benefits for everyday life. A strong signal for innovation, cooperation and future-oriented mobility beyond urban centers,” the ministry wrote in a LinkedIn post.
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Tesla China quietly posts Robotaxi-related job listing
Tesla China is currently seeking a Low Voltage Electrical Engineer to work on circuit board design for the company’s autonomous vehicles.
Tesla has posted a new job listing in Shanghai explicitly tied to its Robotaxi program, fueling speculation that the company is preparing to launch its dedicated autonomous ride-hailing service in China.
As noted in the listing, Tesla China is currently seeking a Low Voltage Electrical Engineer to work on circuit board design for the company’s autonomous vehicles.
Robotaxi-specific role
The listing, which was shared on social media platform X by industry watcher @tslaming, suggested that Tesla China is looking to fill the role urgently. The job listing itself specifically mentions that the person hired for the role will be working on the Low Voltage Hardware team, which would design the circuit boards that would serve as the nervous system of the Robotaxi.
Key tasks for the role, as indicated in the job listing, include collaboration with PCB layout, firmware, mechanical, program management, and validation teams, among other responsibilities. The role is based in Shanghai.
China Robotaxi launch
China represents a massive potential market for robotaxis, with its dense urban centers and supportive policies in select cities. Tesla has limited permission to roll out FSD in the country, though despite this, its vehicles have been hailed as among the best in the market when it comes to autonomous features. So far, at least, it appears that China supports Tesla’s FSD and Robotaxi rollout.
This was hinted at in November, when Tesla brought the Cybercab to the 8th China International Import Expo (CIIE) in Shanghai, marking the first time that the autonomous two-seater was brought to the Asia-Pacific region. The vehicle, despite not having a release date in China, received a significant amount of interest among the event’s attendees.
Tesla FSD fleet is nearing 7 billion total miles, including 2.5 billion city miles
Tesla starts showing how FSD will change lives in Europe
