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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.

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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 developing small, affordable SUV, report claims

This latest rumor deserves heavy scrutiny. Tesla has already walked away from a mass-market $25,000 EV once before.

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Credit: Tine Rusc

Tesla is developing a small, affordable SUV, a new report claims, speculating that the automaker is planning to add yet another vehicle to its lineup at a price point similar to the Model 3 and Model Y, but smaller and more compact.

But it does not make a whole lot of sense, especially considering a handful of things CEO Elon Musk said and the overall plan for Tesla’s future.

Reuters reported that Tesla is in the early stages of developing an all-new, smaller, cheaper electric SUV. Citing four sources familiar with the matter, the story claims the vehicle would be shorter than the Model Y, built in China, and represent a fresh platform rather than a variant of the Model 3 or Y.

Suppliers have reportedly been contacted to discuss details, though Tesla has not commented. The move appears aimed at broadening affordability amid slowing EV demand and intensifying competition, particularly from Chinese rivals.

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This latest rumor deserves heavy scrutiny. Tesla has already walked away from a mass-market $25,000 EV once before.

In 2024, the company scrapped its long-teased “Redwood” project for a budget-friendly car. Elon Musk explained the decision bluntly during an earnings call: a conventional low-cost model would be “pointless” and “completely at odds with what we believe.”

In other words, chasing a bare-bones cheap EV runs counter to Tesla’s core mission of accelerating sustainable energy through cutting-edge technology and autonomy rather than volume-driven price wars.

Musk’s own recent statements reinforce skepticism about a compact SUV pivot. Just two weeks ago, on March 25, he responded to fan requests for a minivan by posting on X: “Something way cooler than a minivan is coming.”

Elon Musk says Tesla is developing a new vehicle: ‘Way cooler than a minivan’

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The remark came in the context of family-hauling needs, with Musk highlighting the Cybertruck’s ability to seat multiple child seats. It signals Tesla’s focus is shifting toward more spacious, innovative people-movers—not shrinking its lineup.

U.S. demand data echoes this logic.

The long-wheelbase Model Y L—a six-seat, stretched variant offering extra room for families—has generated massive interest wherever offered. Fans in the U.S. have basically begged for the Model Y L to make its way to the States, or for the company to develop a full-size SUV.

The Model Y L is selling well in China, where it is manufactured.

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Delivery wait times for the Model Y L stretched into February 2026 as orders poured in. Tesla recently expanded the trim to eight new Asian markets, yet it remains unavailable in the United States, where consumer appetite for a larger, more practical SUV is reportedly strong.

American buyers have consistently favored bigger vehicles; the Model Y already outsells most competitors precisely because it delivers crossover utility without compromise. A compact model shorter than today’s bestseller would likely miss this mark entirely.

Tesla’s product strategy has long emphasized differentiation through autonomy, range, and desirability rather than racing to the bottom on price. Stripped-down variants of the Model 3 and Y have already struggled to ignite broad demand.

A new compact SUV built in China might sound logical on paper for cost-sensitive buyers, but it risks repeating past missteps—diluting brand cachet while ignoring clear signals from Musk and the market.

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History suggests Tesla talks about affordable cars more often than it delivers them. Whether this Reuters scoop evolves into metal or joins the $25k project on the scrap heap remains to be seen.

For now, the smart money is on Tesla doubling down on “way cooler” vehicles that actually fit American families—and Tesla’s ambitious vision—rather than a smaller SUV that feels like yesterday’s news.

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Tesla CEO Elon Musk says next FSD release is the one we’ve been waiting for

On Thursday, Musk teased the capabilities and next steps for Tesla’s Full Self-Driving software, focusing squarely on the incremental improvements of the current v14.3 suite, as well as the looming arrival of v15.

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Credit: Tesla

Tesla CEO Elon Musk teased the capabilities of a future Full Self-Driving release, but it seems like we are getting what Yogi Berra once called “Déjà vu all over again.”

On Thursday, Musk teased the capabilities and next steps for Tesla’s Full Self-Driving software, focusing squarely on the incremental improvements of the current v14.3 suite, as well as the looming arrival of v15.

He confirmed that upcoming point releases of v14.3 will deliver additional polish to the current build, smoothing out remaining edges in an already capable system. These iterative updates, Musk noted, are designed to refine performance without requiring a full version overhaul.

Tesla Full Self-Driving v14.3: First Impressions

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Yet the real headline was Musk’s forecast for v15.

“V15 will far exceed human levels of safety, even in completely unsupervised and complex situations,” he wrote.

He clarified that v15 will be powered by Tesla’s long-awaited large model, an AI architecture with roughly 10x the parameters of the smaller model currently in widespread use. The leap, Musk explained, stems from the unusually rapid progress of the compact model, which has advanced so quickly that the larger counterpart has yet to catch up in real-world deployment.

However, it is becoming a pattern that is, by now, familiar to anyone following Tesla’s autonomous driving roadmap.

Musk has consistently and repeatedly framed each successive major release as the one poised to deliver game-changing autonomy. Earlier versions were similarly positioned as a movement toward the final piece of the puzzle, only for attention to pivot to the next milestone once they arrived.

The refrain has become a recurring feature of FSD communication: current software is impressive, the point releases will sharpen it further, but the true breakthrough lies one major iteration ahead.

Musk’s latest comments fit squarely into that cadence. While v14.3 point releases are expected to tighten supervised driving behaviors in the coming weeks, v15 is cast as the version that finally crosses the threshold into unsupervised operation at human-or-better safety levels across demanding scenarios.

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The 10x parameter scale of the underlying large model is presented as the key technical enabler, promising richer reasoning and more robust decision-making than anything deployed to date.

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Whether v15 ultimately fulfills that promise remains to be seen. Tesla’s history shows that each new target generates fresh excitement—and occasional skepticism—about timelines.

Fans realize Musk’s timelines for FSD are exciting, but rarely met:

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For now, Musk’s message is familiar: the immediate focus is polishing v14.3 through targeted point releases, while the 10x-parameter large model in v15 represents the next decisive step toward fully unsupervised, superhuman safety.

Hopefully, Tesla can come through, but we can only believe that once v15 gets here, v16 will be the next big step toward autonomy.

Drivers can expect continued refinement in the short term and a significantly more ambitious leap once the large model is ready. The cycle continues, but the stakes, Musk insists, keep rising.

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Tesla Supercharger for Business exposes jaw-dropping ROI gap between best and worst locations

Tesla’s new Supercharger for Business calculator reveals an eye-opening all-in cost and location-based ROI projections.

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tesla v4 supercharger

Tesla has launched an online calculator for its Supercharger for Business program, giving property owners their first transparent look at what it really costs to install Superchargers on site and what kind of return they can expect.

The program itself launched in September 2025, allowing businesses to purchase and operate Supercharger hardware on their own property while Tesla handles installation, maintenance, software, and 24/7 driver support. As Teslarati reported at launch, hosts also get their logo placed on the chargers and their location integrated into Tesla’s in-car navigation, meaning drivers are actively routed there. The stalls are open to all EVs, not just Teslas.


The new online calculator, announced by Tesla on Wednesday with the note that “simplicity and transparency” have been a problem in the industry, lets any business enter a U.S. address and get a real cost and revenue model. A standard 8-stall V4 Supercharger site runs approximately $500,000 in hardware and $55,000 per post for installation, bringing an all-in price just shy of $1 million. Tesla charges a flat $0.10 per kWh fee to cover software, billing, and network operations. Businesses set their own retail price and keep the margin above that fee.

Tesla expands its branded ‘For Business’ Superchargers

 

Taking a look at Tesla’s Supercharger for Business online calculator, we can see that ROI is not uniform, and the gap between a strong location and a poor one can stretch the breakeven point by several years.

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The biggest driver is foot traffic and how long people stay. A busy rest station, hotel, or outlet mall brings in repeat visitors who need to charge while they’re already stopped, pushing utilization numbers higher and shortening payback time.

Tesla Supercharger for Business ROI calculator

Tesla Supercharger for Business ROI calculator

Local electricity rates matter just as much on the cost side. Markets like California carry some of the highest commercial electricity rates in the country, which eats into the margin between what a host pays per kWh and what they charge drivers. At the same time, dense urban areas with high EV adoption tend to support higher retail charging prices, which can offset that cost if demand is strong enough. Weather also plays a role. Cold climates reduce battery efficiency and increase charging frequency, but they can also suppress utilization in winter months if drivers avoid stopping in exposed outdoor locations. Suburban and rural sites face a different problem: lower baseline EV traffic, which means a site with cheaper power and lower operating costs can still take longer to pay back simply because the stalls sit idle more often. Tesla’s calculator uses real fleet data to pre-fill utilization estimates by ZIP code, so businesses can run their specific address against these variables rather than relying on averages.

The program has seen real adoption. Wawa, already the largest host of Tesla Superchargers with over 2,100 stalls across 223 locations, opened its first fully owned and branded site in Alachua, Florida earlier this year. Francis Energy of Oklahoma and the city of Alpharetta, Georgia have also deployed branded stations through the program, as Teslarati covered in January.

Tesla now exceeds 80,000 Supercharger stalls worldwide, and the calculator makes the economic case for accelerating that number through private investment rather than company-owned sites alone.

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