News
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.
For years, there have been images and videos across social media platforms that have reminded me of when I was a 15-year-old kid teased by “Xbox 720” videos on YouTube. These videos are of the supposed “Tesla Phone” that Elon Musk was secretly developing in between leading Tesla with its electric cars and SpaceX with its reusable rockets.
Would you buy a Tesla phone ? pic.twitter.com/aaTwvvIJit
— Tesla Owners Silicon Valley (@teslaownersSV) October 6, 2023
Although Musk has put those rumors to bed several times, it was never completely out of the realm that he could get involved in cell phones in some capacity. Think outside the box and more macro-level, though. Instead of reinventing the computer, Musk reinvented connectivity by developing Starlink with SpaceX.
It could be something similar, TD Cowen analyst Gregory Williams said in a note last week, where he hinted SpaceX could be gathering some steam to acquire T-Mobile.
Williams said it would be the “clear choice” for SpaceX if it decided to go through with a network acquisition. He also suggested AT&T.
The move would be possible through selling more of its own stock, which would help SpaceX raise the money to purchase T-Mobile, which would cost roughly $300 billion. It could be one of the moves SpaceX makes post-IPO in terms of an acquisition: it already acquired Cursor AI for $60 billion.
Other analysts, like Dan Ives of Wedbush, believe SpaceX and Tesla will eventually merge into one anyway, and that conglomeration could come as soon as this year, some have said.
The implications of SpaceX purchasing T-Mobile are massive. A combined entity would create a truly ubiquitous network: T-Mobile’s terrestrial 5G towers and Starlink’s growing constellation of Direct-to-Cell satellites. This would essentially eliminate dead zones across the U.S. and potentially globally.
SpaceX would instantly become a full-scale facilities-based carrier with satellite differentiation; a huge advantage. This would pressure AT&T and Verizon heavily.
There are also concerns like a potential reduction in long-term competition, and of course, a deal of that size would face intense scrutiny from government agencies.
The strategic fit is compelling due to the existing Starlink–T-Mobile partnership and complementary technologies (space + terrestrial). It could create a dominant integrated communications player. However, the regulatory, financial, and execution hurdles are enormous — this remains highly speculative with no indication SpaceX is actively pursuing it right now.
Tesla revealed a major new Cybercab detail in a guide it released for First Responders, showing new territory in its beliefs and intentions for the ride-hailing-focused vehicle that entered production in April.
The First Responders Guide is released to give fire departments, paramedics, and other emergency personnel the proper guidance on what to do in the event of an accident, entrapment, or other situation that would require immediate attention.
On one of the pages of the First Responders Guide, Tesla revealed a stark detail about the Cybercab, which could help personnel enter the vehicle more easily in case of an emergency.
Tesla Cybercab has one important piece that AI4 cars might need for FSD
It shows Tesla has no intention of releasing any Cybercab units that were initially proposed for ride-hailing services for the general public with any manual controls, meaning a steering wheel or pedals:
“A Cybercab equipped with steering wheel, brake pedal, and an acceleration pedal is typically an engineering or test vehicle, and operates at SAE Level 2 autonomy. Cybercab is not typically equipped with a steering wheel or acceleration and brake pedals.”
New official Cybercab documentation from Tesla:
“A Cybercab equipped with steering wheel, brake pedal, and an acceleration pedal is typically an engineering or test vehicle, and operates at SAE Level 2 autonomy. Cybercab is not typically equipped with a steering wheel or… https://t.co/P6ut1mZyzr pic.twitter.com/yq6skl9s2J
— Sawyer Merritt (@SawyerMerritt) June 27, 2026
This is a major development for those who continue to believe Tesla planned to release the Cybercab with any sort of manual controls so that passengers could take over if needed. However, when Tesla started manufacturing production versions of the Cybercab in Giga Texas earlier this year, they were spotted without a steering wheel or pedals.
It essentially confirms the company has no intentions of bringing manual controls to the car’s production versions. Some have argued that the likelihood of Tesla having something
There still are some Cybercab units out there with a steering wheel and pedals, and as Tesla said, these cars are engineering or test vehicles, which have Safety Monitors on board to help the car out of a precarious situation or emergency.
Tesla released the Full Self-Driving v14 ‘Lite’ suite to owners of Hardware 3 or AI3 vehicles today, adding several new features to the vehicles that were once believed to be capable of unsupervised self-driving.
Now, Tesla has released this modified suite to older Tesla vehicles, adding plenty of new features and capabilities.
Here are the full release notes for the suite:
- Distilled the intelligence from HW4 V14 into HW3. This allows HW3 to directly learn how to handle scenarios using HW4 V14 as a guide. This process unlocks the improvements that have been made to HW4 including Reinforcement Learning (RL) and offline models for HW3.
- Improved both proactive and reactive responsiveness across a wide variety of categories including navigation handling, merges and forks, pedestrian interactions, traffic lights, and vehicle cut-in scenarios.
- Improved general comfort in nominal scenarios through fewer false slowdowns, smoother steering and more consistent lane centering.
- Introduced parking, unparking, and reversing capabilities.
- Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, or at the Curbside.
- Speed Profiles are now available at all times, to further customize driving style preference.
These improvements, according to Tesla’s Head of AI, Ashok Elluswamy, help distill the driving behavior from AI4’s v14 series into both the camera and compute configurations of AI3.
Tesla Full Self-Driving v14 ‘Lite’ for older cars finally gets released
He added:
“It includes destination options and speed profiles on city roads, but more importantly significantly improved safety. We hope you’ll enjoy it, once the build ships wide.”
FSD v14 Lite is now rolling out to AI3 early-access customers. Based on the feedback, will rollout to more customers over the next few weeks.
This build distills the driving behavior from AI4’s v14 series into both the camera and compute config of AI3. It includes destination…
— Ashok Elluswamy (@aelluswamy) June 29, 2026
Tesla will continue to roll out the v14 Lite suite more widely in the coming weeks, the company said.
Tesla Phone? Not quite, but close: analyst
Tesla reveals huge Cybercab detail in new guide for First Responders
