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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.
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Tesla Model Y L gets biggest hint yet that it’s coming to the U.S.
Over the past week, a noticeable wave of American Tesla influencers descended on China and Australia, each posting in-depth YouTube reviews of the Model Y L within days of one another.
The Tesla Model Y L is perhaps the most wanted vehicle in the company’s lineup in the United States, especially now that it is void of a true family vehicle with the removal of the Model X.
In China, Tesla currently offers a longer, more family-friendly version of the Model Y, known as the Model Y L, which is longer in terms of its wheelbase and larger in terms of interior space, making it the perfect option for those with a need for a tad more room than what the all-electric crossover offers in its Standard, Premium, and Performance trims.
However, there seems to be a hint that the Model Y L could be on its way to the United States. Over the past week, a noticeable wave of American Tesla influencers descended on China and Australia, each posting in-depth YouTube reviews of the Model Y L within days of one another:
Not saying that this means anything more than Tesla China simply inviting a handful of American influencers to see this car….
….but this seems like a good strategy for an eventual offering in the U.S. https://t.co/XS3PyBdnNd
— TESLARATI (@Teslarati) April 27, 2026
The timing has sparked some intense speculation as to whether Tesla is quietly preparing to bring the long-wheelbase, three-row family SUV to North America after months of requests from fans.
The Model Y L stretches the wheelbase by about five inches compared to the standard Model Y.
This delivers dramatically more rear legroom, optional captain’s chairs in the second row, and a true six- or seven-seat configuration ideal for growing families. Reviewers praise its refined ride, upgraded interior features like a rear touchscreen and premium audio, and competitive range—up to roughly 466 miles in some configurations.
Many observers see the coordinated influencer trip as more than a coincidence. Tesla China appears to have hosted the group, possibly tied to the Beijing Auto Show, giving U.S.-focused creators early access to hands-on footage aimed squarely at North American audiences.
Tesla Model Y lineup expansion signals an uncomfortable reality for consumers
Tesla watchers are quick to point out this isn’t the first time such a pattern has emerged.
Just months earlier, American influencers were similarly invited to China to test-drive the refreshed Model Y Performance. Those videos dropped in the lead-up to the variant’s U.S. rollout, generating exactly the kind of pre-launch hype that helped smooth its September arrival in American showrooms.
The parallel is obviously hard to ignore, as Tesla has used overseas influencer trips before as a low-key way to build anticipation without formal announcements. With the Model Y L potentially hitting the U.S. market late this year, according to CEO Elon Musk, the timing would make sense.
Tesla Model Y L might not come to the U.S., and it’s a missed opportunity
Of course, it could still be coincidental. Tesla regularly invites creators to its Shanghai factory and events for broader promotional purposes, and the Model Y L has been on sale in China for some time. No official word has come from Tesla or Elon Musk about U.S. availability, pricing, or timing.
Import tariffs, regulatory hurdles, and production priorities at Fremont or the new Mexican Gigafactory could still delay or alter any stateside plans.
Even so, the buzz is real. U.S. families have long asked for a more spacious, three-row Tesla SUV that doesn’t require stepping up to the larger Model X.
If the influencer campaign is any indication, the Model Y L—or a close North American cousin—could finally answer that call. For now, American Tesla fans are watching closely and wondering whether this latest China trip is just good content… or the opening act for something much bigger stateside.
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Tesla begins probing owners on FSD’s navigation errors with small but mighty change
Previously lumped under “Other,” these incidents made it harder for Tesla’s AI team to isolate and prioritize map-related issues in their reinforcement learning models. There was a lot of disagreement on how certain interventions should be reported.
Tesla has started probing owners on how often its Full Self-Driving suite has Navigation errors with a small but mighty change last night.
In its latest Software Update, which is Version 2026.2.9.9 featuring Full Self-Driving (Supervised) v14.3.2, Tesla has introduced a targeted improvement to how owners will report interventions.
With the initial rollout of v14.3.2, Tesla introduced a new Intervention Menu that appears when a disengagement occurs. It allowed owners to choose from four different categories: Preference, Comfort, Critical, or Other.
Tesla has voided the Other option and replaced it with a new “Navigation” choice, which seems much more ideal given the complaints owners have had about navigation. This seemingly minor UI tweak, rolled out widely in recent days, marks another step in Tesla’s ongoing effort to refine its autonomous driving stack through precise, crowdsourced data.
“Other” has been replaced with “Navigation” in the Tesla Self-Driving intervention reasons menu pic.twitter.com/mBOi3uYs8C
— Whole Mars Catalog (@wholemars) April 28, 2026
Tesla made this change in direct response to longstanding community feedback. For years, FSD users have noted that navigation errors—such as incorrect speed limits, suboptimal routes, or directing the vehicle to a building’s rear entrance instead of the main one—frequently force interventions.
Previously lumped under “Other,” these incidents made it harder for Tesla’s AI team to isolate and prioritize map-related issues in their reinforcement learning models. There was a lot of disagreement on how certain interventions should be reported:
I chose to label this Navigation error as “Critical” while testing FSD v14.3.2
Here’s why:
✅ This intervention wasn’t “preference,” as the maneuver FSD routed was illegal
✅ If a police officer saw this maneuver, it would result in a ticket https://t.co/znhHb4haAo pic.twitter.com/bZOiLwWmQa— TESLARATI (@Teslarati) April 23, 2026
By adding a dedicated “Navigation” label, the company can now tag disengagements more accurately, feeding cleaner data into its neural networks. This supports faster iteration on routing algorithms, map accuracy, and intent-aware navigation.
Community consensus around Tesla’s navigation system has been consistent and candid. While the end-to-end AI driving behavior in v14.x earns widespread acclaim for smoothness and safety, navigation remains FSD’s clearest Achilles’ heel.
Owners frequently cite outdated map data, failure to learn from repeated corrections, and routing decisions that feel less intuitive than Google Maps or Apple Maps. Common complaints include phantom speed-limit changes, inefficient local roads, and poor point-of-interest handling.
Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much
Many drivers report intervening on navigation far more often than on core driving maneuvers, with some estimating it accounts for the majority of disengagements outside of edge cases.
Long-term users note that the same mapping glitches persist across years and software versions, despite thousands of collective miles of feedback. Yet the addition of the “Navigation” option has been met with optimism. It signals Tesla’s commitment to data-driven progress and suggests navigation improvements could arrive sooner.
For a community that already logs millions of FSD miles monthly, this small change could unlock meaningful gains in reliability and user trust—potentially accelerating the path to unsupervised autonomy.
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Tesla expands Robotaxi in a way that was long anticipated
Instead, it has to do with the consumer base it offers Robotaxi to, because it has not offered it to everyone in the past.
Tesla has expanded Robotaxi in a way that was long anticipated, and it does not have to do with a new, larger geofence in a city where it already offered its partially autonomous ride-hailing suite, or a new city altogether.
Instead, it has to do with the consumer base it offers Robotaxi to, because it has not offered it to everyone in the past.
Tesla has taken a major step forward in its autonomous ride-hailing ambitions with the official launch of the Tesla Robotaxi app for Android users. Released on the Google Play Store on April 24. Titled simply “Tesla Robotaxi,” the app is now available to download directly from Tesla.
The @Tesla Robtoaxi App has just officially launched for Android users. Go get some rides y’all!
Download: https://t.co/D2jIONXc91 pic.twitter.com/rQ6TD14zkC
— Sawyer Merritt (@SawyerMerritt) April 24, 2026
This rollout fulfills a long-anticipated expansion that opens the service to hundreds of millions of Android smartphone users who were previously unable to access it on iOS alone.
The app delivers a streamlined, driverless ride experience powered by Tesla’s automated driving technology.
Users sign in with a Tesla Account, view the current service area map within the app, enter a destination, and receive an estimated fare and arrival time before confirming the ride. When a Model Y from the Robotaxi fleet arrives, riders confirm the license plate, enter the vehicle, fasten their seatbelt, and tap “Start Ride” on either the app or the vehicle’s touchscreen.
During the trip, passengers have access to all the same controls that iOS users do, and can adjust climate settings, seat positions, and music while tracking progress on an in-app map. The interface also allows drop-off changes or support requests if needed. After the ride, users exit, close the doors, and submit feedback.
This Android availability directly broadens the rider base for Robotaxi in its initial service areas. Unfortunately, Android users are used to being subject to delayed launches of new features available to Tesla owners.
By removing the iOS-only barrier, Tesla instantly expands the addressable market, enabling far more people to summon and use the autonomous vehicles already operating on public roads.
The move is a foundational requirement for scaling ride volume and gathering the real-world data needed to refine the unsupervised Full Self-Driving system that powers every trip.
For the Robotaxi program itself, the launch signals steady operational progress. It prepares the service for higher utilization rates as the fleet grows and supports the transition from limited early deployments to a more robust network.
Tesla expands Unsupervised Robotaxi service to two new cities
Tesla has indicated that users outside current service areas can sign up at the company’s website for future notifications, pointing to a deliberate, phased geographic rollout.
Looking ahead, the company plans to incorporate Cybercab vehicles to increase fleet capacity and efficiency while continuing to expand service territories. With the Android app now live, Tesla has removed a key adoption hurdle and positioned Robotaxi for the next phase of growth in autonomous urban transportation.
The infrastructure is now in place to support significantly larger rider demand as production and deployment accelerate.
Tesla Model Y L gets biggest hint yet that it’s coming to the U.S.
Tesla begins probing owners on FSD’s navigation errors with small but mighty change
