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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 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 has finally released its Full Self-Driving v14 ‘Lite’ suite for older cars that equip the Hardware 3 or AI 3 chip, which have not been able to handle the newest versions of the company’s driver assistance software.
Tesla officially started releasing the v14 Lite suite to owners in the Early Access Program last night. The company’s Head of AI, Ashok Elluswamy, said that the rollout will continue over the next few weeks. The build distills the driving behavior from AI4’s v14 series into both the camera and compute configurations of an AI3 car.
🚨 Tesla is releasing v14 Lite for AI3 owners who are in early-access
This will give AI3 cars the ability to experience new FSD features like parking preferences. https://t.co/pp6Q5FOKoz pic.twitter.com/tqexMB8SVy
— TESLARATI (@Teslarati) June 29, 2026
It also includes a variety of new features that were available to AI4 cars running v14, including:
- Start Self-Driving from Park
- Arrival and Parking Options
- Speed Profiles
The release is highly anticipated because those owners with AI3 vehicles were early adopters into the FSD platform and were promised that their cars would be capable of achieving Full Self-Driving.
However, Tesla CEO Elon Musk admitted during the company’s recent Q1 Earnings Call that these vehicles would not be capable of achieving unsupervised Full Self-Driving, which is what Tesla had originally said.
Owners were not pleased with this answer, or the idea that their commitment to buying the suite outright for thousands of dollars would not yield the ability to drive without operating the car. Tesla gave some solutions for this, including a discount on a new car, or an upgrade to an AI4 or AI5 self-driving computer and new, upgraded cameras.
Tesla owners do not seem pleased with these options, as they require giving the company more money.
Nevertheless, it is important to note that Tesla came through for owners here by releasing v14 Lite before the end of Q2, something it had promised owners during the previous Earnings Call. Tesla has had trouble keeping up with timelines, but this is a big achievement for the team.
Tesla released what analysts believe the company will report in terms of deliveries and energy deployments for Q2, but the figures seem to confirm a long-standing theory on the company’s vehicle division.
For years, Tesla was just looked at as a car company. Now that it has established itself as a powerhouse in energy, AI, and tech as a whole, the company is now less hellbent on achieving quarterly growth, on a sequential basis, at least from a major standpoint.
Tesla topped out its annual deliveries in 2023 at 1.81 million, and in the two years since, the company has reported a decrease in deliveries for the entire 12-month term both times.
With Tesla delivering 358,023 cars in Q1, a 6.3 percent increase over Q1 2025, but falling short of Wall Street expectations at 365,000-370,000 units, the narrative around vehicle deliveries and their importance continued to change earlier this year. Some might say it is convenient, but others might say it is the typical evolution of a company that continues to change over time.
For Q2, Tesla’s delivery consensus estimates sit at 406,024 units, analysts believe. They were surveyed from Daiwa, DB, Wedbush, Cowen, Canaccord, Baird, Wolfe, BMP Paribas, Goldman Sachs, RBC, Evercore ISI, Barclays, Bank of America, Wells Fargo, Morgan Stanley, Truist, UBS, Jefferies, JPM, Needham & Co., HSBC, and William Blair.
Credit: Tesla
Tesla is also expected to report deployments of 13.8 GWh this quarter.
The change to Tesla’s overall narrative now leans less on vehicle deliveries and more on its other projects. Most notably, Tesla’s Robotaxi project has taken the priority over most of its other business ventures, and investors and the public are more concerned about the deployment of vehicles into the fleet, the operation of a driverless ride-hailing service, Cybercab production and operation, and expansion into new cities.
Tesla analyst realizes one big thing about the stock: deliveries are losing importance
This big narrative switch happened when Tesla indicated it was looking at making transportation a service by launching a ride-hailing service that will operate using Tesla’s Full Self-Driving suite. Once unsupervised operation begins, Robotaxi could be a new way for people to get around, all without a driver in their car.
Instead, they will rely on the billions of miles Tesla has accumulated from its real-world fleet.
It is important to note that Tesla remains significant in the automotive sector, and deliveries must continue as they have for years. Tesla still has a strong automotive business and needs to execute further on all facets to keep its investors happy.
Tesla Full Self-Driving v14 ‘Lite’ Release Notes: new capabilities and features
Tesla Full Self-Driving v14 ‘Lite’ for older cars finally gets released
