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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.

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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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Why SpaceX is finishing another space-internet system that isn’t Starlink

SpaceX launched three final O3b mPower satellites Sunday, finishing a lesser known SES satellite network.

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SpaceX had an 87 minute window opening at 2:49 p.m. Eastern on Sunday to fly a Falcon 9 out of Cape Canaveral carrying the final three satellites for SES’s O3b mPower constellation, a project that has taken more than a decade to finish since Boeing and SES first signed SpaceX on for the work.

Unlike the thousands of Starlink satellites SpaceX has stacked into orbit over the years, O3b mPower flies in a different neighborhood entirely. The three new satellites, tagged F11, F12 and F13, are headed for medium Earth orbit at roughly 5,000 miles up, more than ten times higher than Starlink’s shell around 340 miles but still a small fraction of the 22,000 miles where old school geostationary satellites sit. That middle position is the whole point, because a satellite that far out needs far fewer siblings to blanket the globe than a low orbit constellation does. Essentially, SES only needed 13 satellites total to build a network offering quick, steady service that used to require thousands of spacecraft.

With most people having heard plenty about Starlink and almost nothing about O3b mPower, SES and SpaceX already blend the two networks for some customers. Both SpaceX and SES sell satellite broadband, but they’re aimed at different buyers. Starlink is built for volume, direct to consumers, RVs, homes, small businesses, plus a growing aviation and maritime business. O3b mPower skips consumers entirely and sells enterprise grade connectivity to airlines, cruise lines, offshore energy operators, telecoms needing backhaul, and governments, priced and provisioned more like a dedicated circuit.

A 2023 partnership lets cruise ships combine Starlink’s speed with O3b mPower’s steady capacity depending on what a ship needs at a given moment. Sunday’s completed 13 satellite constellation effectively finishes the medium orbit half of that pairing, years after.

Sunday’s mission was already a something on SpaceX’s manifest well before O3b mPower entered the picture. This flight marked its 29th trip to orbit, a history that includes two crewed Axiom missions, the European Space Agency’s Euclid telescope and 22 separate Starlink batches. SpaceX has landed boosters on the droneship A Shortfall of Gravitas so often that Sunday’s touchdown attempt, if it went as planned, was set to be the 661st successful Falcon booster landing to date.

For a company that pushed the Starlink constellation past 11,000 satellites back in August, almost entirely through bulk launches from California, Sunday’s flight was a reminder that SpaceX’s schedule still has room for someone else’s satellites too. SES gets a finished network built for a narrower set of customers, and Falcon 9 gets one more line on an already long resume.

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Tesla gives the Roadster an official “Go for launch” demonstration date

Tesla teased an October 1 Roadster reveal, reviving years of delayed SpaceX thruster hover promises.

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Concept rendering of a Tesla Roadster with SpaceX Package via Grok
Concept rendering of a Tesla Roadster with SpaceX Package via Grok

Tesla teased an October 1 event date for its next generation Roadster, posting an image on X Saturday that shows the car lit up like it is sitting on a launch pad, with the date “10.01” stamped across the bottom and the caption “Go for launch.” A countdown clock on Tesla’s Roadster order page now points to the same date, which falls on a Thursday. The company has not said where the event will happen or whether it will be streamed at the moment. Stay with us @Teslarati for live updates.


Tesla has since sent formal invitations to reservation holders confirming the event will take place in Waco, Texas, about 90 minutes north of its Austin headquarters, based on a digital ticket shared on X by Sawyer Merritt. Tesla did not name the exact venue, though Waco sits close to SpaceX’s McGregor, Texas, rocket test site, previously reported as the planned location for a Roadster thruster demonstration. The invite sets the reveal for 8:30 p.m. Eastern on October 1, requires RSVPs by midnight on September 16, and limits entry to guests 21 and older. Invitations are non-transferable.

The tease follows nine years of a project defined by unimaginable specs along with slipped dates. Musk first showed the second generation Roadster in November 2017 as a surprise reveal at the end of the Tesla Semi event, promising a 0 to 60 mph time under two seconds, a top speed above 250 mph, 620 miles of range from a 200 kWh battery, and production starting in 2020. At last November’s shareholder meeting, Musk set an April 1 demo date and joked the choice gave him “deniability” if it slipped again, which it did, moving first to late April, then to “a month or so,” then to August.

Tesla Roadster SpaceX Package’s 1.1-second 0-60 mph launch visualized in concept video

Whatever Tesla shows on October 1 is expected to center on the SpaceX developed thruster package Musk has described since 2018. Internally code named A71, a nod to the Lockheed SR-71 Blackbird, the system reportedly uses cold gas thrusters fed by a composite overwrapped pressure vessel, the same tank design SpaceX uses on Falcon 9. Musk has said a thruster equipped Roadster could hit 60 mph in about 1.1 seconds under roughly 2.75 g of launch force, well past the 1.9 second figure quoted for the standard car. That version reportedly will not be street legal and has reportedly been discussed as a limited run sold through a track only program.

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The standard Roadster is still expected to carry the original $200,000 base price and $250,000 Founders Series tier, both set when Tesla opened $50,000 and $250,000 reservations in 2017. Tesla VP of Vehicle Engineering Lars Moravy has confirmed production will happen at Gigafactory Texas, with Musk targeting 2027 or 2028, 12 to 18 months after whatever the company demonstrates next month.

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Tesla plans big safety improvements for Full Self-Driving v15

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Credit: Tesla

Tesla is planning to roll out some pretty significant safety and accident avoidance features with Full Self-Driving version 15, which will be the next major FSD deployment from the company.

Tesla AI lead Ashok Elluswamy used a near-miss this week to preview what the company says is the next leap in Full Self-Driving.

In response to a driver whose car had swerved away from another vehicle pulling out of a parking lot, Elluswamy wrote that he was glad the owner was safe and that “even earlier prediction of hazards, even faster reaction time and overall significantly better safety and collision avoidance” would arrive with FSD v15.

The comment landed as Tesla continues to treat software as the primary safety upgrade path. v15 is described internally as a larger architectural step, with a much bigger neural network and tighter coupling between prediction and control.

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The company has already begun using early v15 software in some robotaxi operations while rolling out safety features such as Automatic Collision Evasion into current customer cars, allowing the driving stack to intervene even when the driver is in manual control.

Tesla is rolling out a new FSD version with a massive safety addition

Tesla’s published telemetry is the backbone of its safety argument. In recent North American Vehicle Safety Report data, vehicles with FSD (Supervised) engaged traveled roughly 5.1 million to 5.7 million miles between major collisions, defined as airbag-deployment events.

Tesla’s estimate of the U.S. average over the same period is about 699,000 miles per comparable crash. That is the comparison Tesla often frames as roughly seven times fewer major collisions.

A tighter comparison uses the same Tesla fleet. Cars driven manually with active safety features such as automatic emergency braking still recorded a major collision about every 2.1 million miles. Against that baseline, FSD’s advantage shrinks to roughly 2.4 to 2.7 times fewer severe crashes, which independent researchers argue is the more apples-to-apples figure.

European data released in 2026 pointed in the same direction: Tesla reported FSD as 3.5 times safer than manual driving in the Netherlands and 4.1 times fewer collisions than manually driven Teslas with active safety across more than 100 million kilometers in five approved countries.

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Those numbers do not settle every debate. NHTSA’s Standing General Order still shows Tesla accounting for the large majority of U.S. Level 2 driver-assist crash reports, in part because the fleet logs far more assisted miles than rivals. Critics also note that Tesla’s “U.S. average” mixes crash definitions and driving mix.

Even so, Tesla’s own same-car comparisons, plus lower rates of automatic emergency braking and harsh maneuvers when FSD is engaged, are the evidence Elluswamy is pointing to when he says v15 will push prediction and collision avoidance further. The claim is not that software already eliminates risk. It is that each major version is meant to widen the gap between the system and an unaided human driver.

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