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Tesla Autopilot and artificial intelligence: The unfair advantage

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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.

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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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Elon Musk

Tesla FSD takes owner on a 20,000+ mile joy ride

Tesla owner David Moss just pushed his intervention free FSD streak past 20,000 miles total.

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Tesla FSD 14.3 [Credit: TESLARATI)

Tesla Model 3 owner David Moss has spent the better part of eight months turning his vehicle into a rolling stress test for Full Self-Driving, and this week he pushed his single, continuous FSD streak past 20,000 miles without a human intervening.

Moss, a Tacoma, Washington resident who sells LiDAR scanning equipment for a living, first drew wide attention in December 2025 when he logged 10,000 consecutive miles on FSD v14.2. Days later he drove from the Tesla Diner in Los Angeles to Myrtle Beach, South Carolina, covering 2,732 miles in two days and 20 hours with zero disengagements, the first verified coast to coast autonomous drive in Tesla’s history. Tesla even featured the trip as an official customer story in March. That original streak eventually reached 12,961 miles across 30 states before ending in rural Wisconsin in January, when snow and single digit temperatures forced Moss to take over.

Tesla FSD successfully completes full coast-to-coast drive with zero interventions

He started over, and this run has gone further. In late May, Moss drove 3,760 miles across Canada with two companions, from Horseshoe Bay in Vancouver to a Tesla showroom in Halifax, again without a single intervention, a trip Tesla AI software VP Ashok Elluswamy publicly congratulated him for on X. In June, he pushed the same unbroken streak south, aiming to link the Canadian border to the Mexican border, and crossed 10,000 miles on Tesla’s newly added in car streak counter along the way, the first driver to do so since Tesla began showing confetti animations for the feature.


It’s worth noting that every mile is logged through the FSD Database, a community run tracker built by Tesla influencer Omar Qazi, well known as @WholeMars on X, that pulls telemetry straight from the car and records disengagements down to a tenth of a mile. That verification is what separates Moss’s numbers from casual claims on social media.

The streak itself is a fairly recent addition to Tesla’s software. FSD v14.2 introduced a Self Driving Stats panel tracking the ratio of autonomous to manual miles, and v14.3.4 added the live streak counter in June, which resets the moment a driver brakes, wrenches the wheel or cancels navigation. Reaching 20,000 miles on that counter means a single Tesla drove itself through countless highways, city grids, construction zones and Supercharger stalls without a single reset.

Moss has said the goal was never to set a record for its own sake, but to show, mile by verified mile, what the software can already do.

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Elon Musk explains what happens when AI outsmarts all of us

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Elon Musk told The Economist that artificial intelligence will likely surpass the combined intelligence of every human on Earth within about five years, and that humans may not remain in charge once that happens. In a wide-ranging interview with editor-in-chief Zanny Minton Beddoes, recorded at Giga Texas for the outlet’s Insider series, Musk compared the widening gap between AI and human intelligence to the gap between humans and chimpanzees.

“It’s hard to imagine that the chimpanzee would be in charge,” he said, addressing what happens to human authority once AI moves far beyond us.

Elon Musk reiterates his most optimistic prediction yet with “UHI” forecast

Musk’s timeline stretches out from there. Five years for AI to out-think humanity combined, ten years before humans lose meaningful control, and by 2036, he says, money itself may stop mattering.

Musk notes that if robots and AI produce more goods and services than people could ever consume, currency loses its purpose. He told Beddoes that governments could respond with direct payments, what he called “universal high income,” a term he first used in an X post last August describing a future where “everyone will have the best medical care, food, home, transport and everything else.”

He also floated a more surprising prediction that deflation, and not inflation, would become the bigger economic problem, since expanding the supply of goods and services faster than the money supply grows would push prices down rather than up.

None of this is new territory for Musk, who has spent years describing an “age of abundance” built on Optimus and autonomous vehicles. What’s notable is the timing. The interview landed the same week Tesla shares dropped roughly 19 percent following a second quarter earnings report that beat on revenue but missed badly on profit, and as SpaceX stock continues to slide from its post-IPO peak.

Musk’s own net worth has fallen close to $700 billion since mid-June, according to the Bloomberg Billionaires Index, even as he describes a future where personal wealth stops being the point.
Musk did not dodge the risk side of the equation either. He put the odds of AI contributing to human extinction somewhere in the 10 to 20 percent range, then arrived at what he called his “philosophical conclusion” since the technology cannot realistically be stopped and the arguably better response is to keep building it and hope the outcome leans toward abundance rather than catastrophe. “I’ve gone from exhilaration to terror regarding AI,” he told Beddoes, “even intraday.”

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Tesla adds new ‘Traction Control Modes’ for better handling in any conditions

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Credit: Tesla

Tesla is adding a new “Traction Control Modes” feature to its cars for better handling in any conditions. These features will roll out to the Model 3 and Model Y, the two vehicles in Tesla’s lineup that typically do not have drive modes for various conditions.

Tesla did include this in the Model S and Model X, as well as the Cybertruck.

The new feature will roll out with the 2026 Summer Update, which Tesla announced last week and subsequently started rolling out to some owners today. The Summer Update is the latest iteration of the usual four seasonal releases the company rolls out throughout the year. These releases typically feature some owner-requested features, as well as improvements to things like the Full Self-Driving suite.

Tesla reveals 2026 Summer Update with crazy fixes to Nav and more

This release is no different. Among the changes are improvements to Navigation, new customization options with wraps and how they can be shared and stored, more functionality with the Tesla smartphone app, and new gamification with self-driving.

However, Tesla announced today that it was adding another feature to the Summer Update. Traction Control Modes will now be available with the release

Tesla describes them:

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“Choose from three updated Traction Control Modes: Auto for normal driving conditions, Slippery Surface for icy or wet roads, Stuck Assist when stuck in snow, mud, or sand. The mode resets to Auto at the start of each drive. To select, go to Controls > Dynamics > Traction Control Mode.”

The use of these modes will help improve a Tesla’s overall performance in less-than-ideal conditions. Typically, these traction control modes monitor wheel speed through sensors and track engine power to adjust responsiveness in various conditions.

These drive modes are not an ultimate solution to all driving conditions; just because there is a “Stuck Assist,” doesn’t mean your Tesla will dig itself out of a foot-and-a-half trench during a blizzard. It is important to remember that some of these scenarios also require some assistance from the driver. For example, driving in sand requires tires to be aired down significantly to increase traction and control.

However, this will be a welcome addition for those who use the Full Self-Driving suite and might not be convinced of its performance in adverse conditions. Some of us prefer to be in control in rain, snow, or ice, which is totally understandable. However, adjusting the Traction Control Mode while utilizing FSD in snow, rain, or ice could increase confidence and overall experience.

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Tesla’s Summer Update is already rolling out to some owners, so it should be making its way to most of the fleet over the next several weeks. The Spring Update rolled out at a very conservative pace, so if you don’t have it by the end of August, don’t be too upset. It might just be Tesla’s method.

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