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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.
A new report from Reuters claims that a transport authority in Sweden is pushing back against the approval of Tesla’s Full Self-Driving suite because it will travel over speed limits.
The report says the Swedish Transport Administration (TRV) recommends the European Union votes against FSD’s approval. TRV believes it should not be approved until Tesla disables FSD’s ability to speed.
TRV sent a letter to the European Union’s Technical Committee on Motor Vehicles (TCMV), which is set to meet on June 30 to discuss the potential approval of the Tesla FSD suite in the country. Tesla, which has received various approvals in Europe over the past two months, has not provided a comment.
Teslas operating on FSD do travel over the speed limit, depending on the Speed Profile that is chosen. Drivers have the ability to disengage FSD at any point; Tesla specifically states that those supervising the suite are responsible for its actions.
Let’s cut to the chase: humans operating any vehicle speed almost daily in the United States. Realistically, speed limits in the U.S. are more frequently treated as speed minimums. However, other countries are different, and driving behaviors are less aggressive.
TRV believes that “allowing automated systems to systematically exceed legal speed limits…risks undermining both the legal framework and the expected safety benefits of vehicle automation,” the report stated. It’s surprising that Tesla has not received this claim from other countries previously.
This could be a good argument to bring Max Speed back, the setting that previously allowed the driver to choose the absolute fastest the car would travel.
This would still put the responsibility of supervision in the hands of the driver. It would allow the driver to choose whether the car would travel over the speed limit or not, acknowledging that they set the speed, and if they get pulled over, there would be no ability to argue it.
However, it does not seem as if this is something Tesla will do, especially considering many U.S. drivers have requested the feature in an effort to eliminate speeding or at least tone it down. The company has not shown any interest in bringing it back.
Tesla has approvals for FSD in Europe in Estonia, Lithuania, Denmark, the Netherlands, and Belgium.
Tesla is going to let you guide Full Self-Driving with Grok in 3 months, CEO Elon Musk confirmed on X.
The response from Musk, which revealed Tesla plans to allow drivers to effectively control the car and its navigation more explicitly using Grok, puts the feature for about September.
A Tesla owner said that Full Self-Driving is great, but owners should be able to “converse with Grok like we can with an Uber driver.” She then used examples like, “Grok, turn right here,” and “Drop us off right here, we’ll walk due to traffic,” and finally,” Drop at entrance first, then park far away.”
Coincidentally, the final piece of dialogue would also mean features like Banish are potentially on the way soon.
This functionality will be there in about 3 months or so
— Elon Musk (@elonmusk) June 18, 2026
Banish is also referred to as “Reverse Summon,” and would enable the car to self-park while dropping occupants off at their destination.
This would be a great way to improve the overall experience while supervising FSD. Navigation is already a major painpoint that many owners complain about. Manual overrides when a maneuver is requested or canceled (like using the turn signal stalk to override a navigation route), do not always work.
The feature could be especially useful in street parking scenarios in a city, where spots are sometimes tough to come by. Many of us who grab dinner in a more populated area will park a street or two over from wherever we’re going, because sometimes you know that’s the best you will get. If a driver using FSD could say, “Hey Grok, turn right here on Queen St. and park in that open spot on the right,” it could save a lot of confusion FSD might have on its own.
Musk teased that a similar feature was “coming” back in February:
Tesla Full Self-Driving set to get an awesome new feature, Elon Musk says
It is certainly surprising that Tesla is doing it at this point. The company’s more recent moves have been more evident of taking control and inputs away from humans and putting them in the AI’s hands more frequently. The biggest example of this was taking away Max Speed in AI4 cars, giving us Speed Profiles, and not having any input on the fastest speed the car will travel.
Of course, giving navigation preferences to Grok is availble already in Teslas, but not at the drop of a hat. Instead, you can suggest a certain route at the beginning of your drive.
Here’s an example of that from December:
🚨🏈 I am taking my parents and Fiancee to the @Ravens game next weekend and asked @Grok to help me route my @Tesla through a specific neighborhood to reach the correct Lot we will park in.
This is a great example of the new @grok nav integration with the Tesla Holiday Update: pic.twitter.com/rPp4I7q8Yv
— TESLARATI (@Teslarati) December 13, 2025
Finally, the original post that Musk responded to mentioned a parking preference after dropping off the occupants, which describes the Banish feature that Tesla has teased for years.
We’re not sure if Musk was responding more to the ability to guide the car with Grok, or whether he also was including Banish in the three-month prediction timeframe.
A close-up image of a Cybercab engineering vehicle in Peabody, Massachusetts, reveals a compact triangular side repeater camera housing equipped with an integrated washer mechanism.
This seemingly small hardware addition could prove to be one of the most critical components for achieving reliable, unsupervised Full Self-Driving (FSD) — not just for the dedicated Robotaxi but potentially for existing AI4-equipped vehicles as well.
The washer system’s importance cannot be overstated in Tesla’s vision-only autonomy approach. Cameras are the sole sensory input for the neural networks powering FSD, constantly interpreting the environment for safe navigation. In real-world conditions, however, lenses quickly accumulate rain, snow, mud, dust, or road spray.
Many of us Tesla owners, especially those who deal with any sort of winter weather at all, know the all-too-common alert that pops up when cameras are obstructed:
Even brief obstructions can drop perception confidence, trigger safety disengagements, or force the vehicle to pull over, although these are relatively rare. Instead, most of the time, the camera will need a wipe from the owner next time they stop the car.
But unlike human drivers who can manually clear their view, a Robotaxi operating 24/7 without a steering wheel or mirrors must maintain pristine vision autonomously. The Cybercab’s side repeater washer delivers targeted cleaning bursts precisely where needed for merging, lane changes, and blind-spot monitoring — functions that demand uninterrupted visibility from the external cameras:
And this is how the side camera and washer look like on a Cybercab. This is from an Engineering vehicle in Peabody MA. pic.twitter.com/Re8VknpmLM
— Tobias Goebel (Unsupervised) (@tpgoebel) June 17, 2026
This hardware directly tackles a known pain point in current FSD deployments. Owners frequently report camera-related alerts during inclement weather, which is understandable, but needs to be solved for a true autonomous experience.
For a production Robotaxi fleet aiming for high utilization and minimal downtime, robust washer systems represent a foundational reliability upgrade; essentially, they’re a must-have. Early sightings suggest the design may extend to rear cameras as well, creating a comprehensive cleaning architecture that keeps the entire vision suite operational in harsh environments.
Without it, even the most advanced neural nets struggle when their “eyes” are compromised.
What Does This Mean for AI4 Cars?
This Cybercab detail raises timely questions for AI4 cars already on the road. While Hardware 4 delivers superior compute and camera resolution compared to earlier versions, production models typically lack dedicated side and rear washers. Tesla has included them on Model Y robotaxis that it is using in the fleet:
Tesla Robotaxi has a highly-requested hardware feature not available on typical Model Ys
As Tesla refines unsupervised FSD for broader release, the gap in environmental resilience becomes evident. Software improvements can help mitigate issues, but they cannot fully replace physical cleaning in heavy rain or muddy conditions. Analysts and owners increasingly speculate that AI4 vehicles may eventually require similar washer retrofits — or a future AI4.5 variant — to match the Cybercab’s all-weather readiness and support the same level of autonomy.
As testing progresses, the Cybercab’s washer mechanism highlights Tesla’s pragmatic focus on real-world robustness. It may well become the hardware piece that determines how quickly and reliably FSD scales from prototypes to everyday vehicles.
Tesla faces Full Self-Driving pushback in EU over ‘speeding’
Tesla teases greater Grok FSD integration and ‘Banish’ feature ‘in about 3 months’
