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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.

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 Semi is officially headed to Europe

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Credit: Tesla

Tesla has officially confirmed plans to bring its all-electric Semi truck to Europe, with full specifications and market-launch details set for unveiling at the IAA Transportation trade fair in Hannover, Germany.

The event runs September 15–20, with a possible press preview on September 14. The announcement, shared via Tesla’s Semi account, marks a significant expansion beyond North America nearly nine years after the truck’s original 2017 reveal.

In the United States, the Semi’s path has been gradual. Limited pilot production and customer deliveries began in late 2022, primarily to fleets such as PepsiCo. After years of refinement, high-volume manufacturing started on April 29, 2026, at a dedicated facility adjacent to Gigafactory Nevada.

The plant targets an annual capacity of 50,000 units, though the ramp is expected to be gradual, with “many thousands” of trucks projected by the end of 2026.

Demand is building, with recent orders including 500 units for Einride (deliveries starting September 2026, serving Amazon and others) and hundreds more from operators such as WattEV. Pricing stands at approximately $260,000 for the Standard Range and $290,000 for the Long Range before incentives.

Tesla Semi pricing revealed after company uncovers trim levels

Earlier in 2026, Tesla finalized production specifications that incorporated substantial updates. In February, the company detailed two variants designed for a full 82,000-pound gross combination weight.

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The Standard Range offers about 325 miles of range with a 548 kWh battery and curb weight under 20,000 pounds. The Long Range delivers roughly 500 miles with an 822 kWh pack and a 23,000-pound curb weight. Both use three independent rear-axle motors producing up to 800 kW (about 1,073 horsepower), achieve energy consumption of around 1.7 kWh per mile, and support megawatt-class charging at up to 1.2 MW—recovering about 60 percent of range in 30 minutes through the MCS standard.

Additional refinements include a roughly 1,000-pound weight reduction versus earlier prototypes, improved aerodynamics, a 48-volt electrical architecture, electric power take-off up to 25 kW for refrigerated trailers, and fleet management software with over-the-air updates.

These advances position the Semi as a competitive option against diesel trucks on operating costs and performance. For Europe, adaptations such as lighting, cab configurations (including potential sleeper options), and regulatory compliance are anticipated.

With series production underway in Nevada and major fleet commitments secured, the upcoming IAA reveal will clarify timelines, European-specific specs, and pricing, potentially accelerating electrification of heavy-duty freight on both continents.

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Tesla Robotaxi gets a massive upgrade in Nevada

Nevada regulators just approved a massive expansion of Tesla’s robotaxi fleet across the entire county.

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Concept art of a Tesla Cybercab in Las Vegas Strip as rendered via Grok

Tesla’s robotaxi footprint in Nevada just grew by roughly 500 times in a single regulatory vote.

The Nevada Transportation Authority approved Tesla’s full Autonomous Vehicle Network Company permit on Thursday, clearing the way for the company to deploy up to 5,000 driverless vehicles across Clark County over the next 12 months. The decision came during a four hour general session meeting that Tesla investor Sawyer Merritt watched live and reported on X, noting the vote replaces the interim order that had limited Tesla to just 10 robotaxis on a narrow stretch of the Las Vegas Strip.

That earlier cap, covered here after it surfaced on August 13, came with restrictions that looked stricter than what Tesla runs in Austin: a 45 mph speed ceiling, no airport pickups, and a geofence confined to the Strip corridor. The new approval extends Tesla’s operating authority to all of Clark County, with room to request an even wider geofence across the state.

Tesla representatives at the meeting said they have no intention of putting 5,000 cars on the road right away. Commercial rides are expected to start within 30 days, pending vehicle inspections, insurance filings, and fare approval, the standard steps every robotaxi operator in Nevada has had to clear.

Tesla’s own Robotaxi account replied to the news with a short line, The golden future is upon us.

The timing lines up with Tesla’s broader robotaxi push this month. The company is preparing to open Cybercab rides to the public in Austin as soon as this month, and it opened a sweepstakes for riders to win a seat at the launch event. Tesla filed its original application for a 5,000 vehicle Nevada fleet back in June, a request regulators trimmed to 10 vehicles when they issued the interim order in July. Thursday’s vote effectively grants the number Tesla asked for from the start.

Zoox, the Amazon owned robotaxi operator, has run in Nevada since 2025 and was capped at 100 vehicles before Thursday’s decision. Tesla’s new ceiling puts it well ahead of that comparison on paper, though the company has said its actual fleet size will depend on how quickly FSD v15 rolls out, the software update executives have called the gateway to scaling unsupervised robotaxi operations nationwide.

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Tesla admits to slow Model Y Robotaxi integration, but for a good reason

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Credit: Tesla

Tesla welcomed JPMorgan analysts to one of its factories earlier this month, with the Wall Street firm highlighting its findings in a new note to investors. One of the more pertinent pieces of information is that Tesla admitted to slowly integrating Model Y vehicles into its Robotaxi fleet, but it has a good reason.

JPMorgan analysts recently toured Tesla’s Fremont Factory and met with the company’s investor relations team, emerging with a clearer picture of the automaker’s Robotaxi strategy. According to the bank’s note, Tesla is intentionally limiting the addition of Model Y vehicles to its existing Robotaxi fleet.

The firm’s analysts said:

“Tesla indicated it is intentionally holding back on adding Model Y units to the robotaxi fleet, expressing confidence in its ability to scale Cybercab in the near-term. On FSD V15, Tesla views this release as a step-change in performance, comparable to the leap from V13 to V14. The V15 upgrade encompasses seven core technologies, with ~40% of those currently being tested in the robotaxi fleet, where initial feedback has been encouraging.”

Far from signaling delays or doubts about autonomy, the move reflects strong management confidence in the near-term scalability of the purpose-built Cybercab.

Tesla has operated its Robotaxi service primarily with modified Model Ys since launching in Austin and expanding to other markets. Yet the company is now deliberately holding back further Model Y conversions. The rationale is straightforward: leadership believes the Cybercab, a two-seat, steering-wheel- and pedal-free vehicle optimized for high utilization, can ramp production and deployment more efficiently in the coming months.

This dedicated form factor promises better unit economics for the majority of rides, which typically involve one or two passengers, while freeing consumer Model Y inventory for retail sales.

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Supporting this pivot is Full Self-Driving (FSD) software version 15, which Tesla describes as a genuine step-change in performance, comparable to the leap from V13 to V14. The update incorporates seven core technologies; roughly 40 percent are already undergoing real-world testing in the current Robotaxi fleet, with early feedback described as encouraging.

Tesla is carefully managing software development to minimize regressions in core driving functions as new capabilities are added. Management positions V15 as the primary gateway to scaling unsupervised FSD. Importantly, the existing AI and Hardware 4 stack is already capable of running V15 and supporting unsupervised operation.

Cybercab itself is only the first vehicle on the platform. Tesla reiterated that additional form factors will follow, pointing to concepts such as the earlier “Robovan” demonstration as examples of how the architecture can evolve.

Tesla’s mysterious Robovan makes a sneak peek with Optimus in Terafab video

Parallel progress continues on the Optimus humanoid robot, which remains on track for start of production in the coming months, with commercial sales possible as early as the second half of 2027. Generation 3 details will be revealed closer to production to preserve competitive advantages, while Generation 4 scope will draw on real-world Gen 3 experience.

JPMorgan left the meeting with a deeper appreciation for Tesla’s manufacturing automation and maintained its $475 price target. The decision to slow Model Y Robotaxi integration is therefore not a setback but a calculated prioritization of a more efficient, purpose-built solution that management believes is ready to scale.

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