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Tesla’s FSD Beta is navigating through roundabouts with great confidence
Ever since Tesla rolled out its Full Self-Driving Beta last week, the lucky group of individuals who have been sharing the new system’s capabilities are proving that Autopilot has improved significantly. Previously challenging tasks for the 2.5-dimension Autopilot versions are no longer a tough task thanks to a 4D comprehension of surroundings, which are a preview of what is to come with Tesla’s upcoming “Dojo” Supercomputer.
Tesla owners who have had FSD for some time know that the capabilities of the self-driving suite were somewhat limited. Everyone who purchased FSD knew it was a work in progress, and by driving with the capability activated, it was becoming more sophisticated with the help of Tesla’s Neural Network. However, the Tesla Artificial Intelligence team knew what had to be done: the amount of information that could be processed needed to be greater, and the vehicle’s comprehension of its surroundings needed to be more complex. Therefore, Tesla is developing Dojo.
Dojo is Tesla’s Neural Network training program that aims to begin breaking down data in 4D instead of “~2.5D,” which is what the automaker’s Autopilot was previously using.
Tesla’s Elon Musk details Dojo, Autopilot’s 4D training program
Musk detailed the need for a more complex autonomy system during the Q2 2020 Earnings Call:
“Well, the actual major milestone that’s happening right now is really a transition of the autonomy system or the cars, like AI, if you will, from thinking about things in — like two-and-a-half feet. It’s like think — things like isolated pictures and doing image recognition on pictures that are harshly correlated in time but not very well and transitioning to kind of a 4D, where it’s like — which is video essentially.”
The issue with previous FSD and Autopilot builds was that not enough information was being transmitted through pictures. There needed to be timestamps and more accuracy through an increasingly fluid comprehension of the surroundings. The key was to transition from images, or 2D, as Musk called it, to video, or 4D.
“So what we’ve been doing, thus far, has really just been like 2D — mostly 2D, and like I said, well correlated in time. So just hard to convey just how much better a fully 4D system would work — does work. It’s capable of things that if you just look — looking at things as individual pictures as opposed to video — basically, like you could go from like individual pictures to surround video, so it’s fundamental. So the car will seem to have just like a giant improvement.”
Roundabout Navigation
One way to show how the new system is operating more efficiently is a Tesla’s navigation of a roundabout. Musk stated that it would be able to handle roundabouts “not perfectly at first,” but it would be able to navigate through them.
Not perfectly at first, but yes. Will take maybe a year or so to get really good at roundabouts worldwide. The world has a zillion weird corner cases.
— Elon Musk (@elonmusk) August 14, 2020
Previous versions of Autopilot have had difficulties navigating through roundabouts, and very rarely did they manage to get through one without human intervention. An example can be seen in a July 2019 video from YouTuber Dirty Tesla, who showed his Model 3 attempting to go through the tricky stretch of roadway. At the 3:25 mark of the video, you can see the Model 3 doesn’t do a great job of making it through, and the driver is forced to intervene with the vehicle.
Tesla’s FSD Beta is proving that an increase in comprehension is just what Tesla Autopilot needed to function more accurately. A video from fellow Tesla Model 3 owner James Locke, who received the FSD Beta, shows the navigation through a roundabout with relative ease. Even Locke was impressed and stated that the maneuver required no intervention from him, and Autopilot took care of the entire process independently.
Dojo’s coming release in conjunction with the new FSD Beta could prove to be the answer to all of the issues that Tesla had previously. With a new, more complex system that takes in more information on terrain, surroundings, and obstacles, Autopilot is more accurate than ever before. The increase in capability is being displayed daily as new videos of the FSD Beta are being rolled out regularly.
Elon Musk
Elon Musk proposes Grok 5 vs world’s best League of Legends team match
Musk’s proposal has received positive reception from professional players and Riot Games alike.
Elon Musk has proposed a high-profile gaming challenge for xAI’s upcoming Grok 5. As per Musk, it would be interesting to see if the large language model could beat the world’ best human League of Legends team with specific constraints.
Musk’s proposal has received positive reception from professional players and Riot Games alike, suggesting that the exciting exhibition match might indeed happen.
Musk outlines restrictions for Grok
In his post on X, Musk detailed constraints to keep the match competitive, including limiting Grok to human-level reaction times, human-speed clicking, and viewing the game only through a camera feed with standard 20/20 vision. The idea quickly circulated across the esports community, drawing commentary from former pros and AI researchers, as noted in a Dexerto report.
Former League pro Eugene “Pobelter” Park expressed enthusiasm, offering to help Musk’s team and noting the unique comparison to past AI-versus-human breakthroughs, such as OpenAI’s Dota 2 bots. AI researcher Oriol Vinyals, who previously reached Grandmaster rank in StarCraft, suggested testing Grok in RTS gameplay as well.
Musk welcomed the idea, even responding positively to Vinyals’ comment that it would be nice to see Optimus operate the mouse and keyboard.
Pros debate Grok’s chances, T1 and Riot show interest
Reactions weren’t universally optimistic. Former professional mid-laner Joedat “Voyboy” Esfahani argued that even with Grok’s rapid learning capabilities, League of Legends requires deep synergy, game-state interpretation, and team coordination that may be difficult for AI to master at top competitive levels. Yiliang “Doublelift” Peng was similarly skeptical, publicly stating he doubted Grok could beat T1, or even himself, and jokingly promised to shave his head if Grok managed to win.
T1, however, embraced the proposal, responding with a GIF of Faker and the message “We are ready,” signaling their willingness to participate. Riot Games itself also reacted, with co-founder Marc Merrill replying to Musk with “let’s discuss.” Needless to say, it appears that Riot Games in onboard with the idea.
Though no match has been confirmed, interest from players, teams, and Riot suggests the concept could materialize into a landmark AI-versus-human matchup, potentially becoming one of the most viewed League of Legends events in history. The fact that Grok 5 will be constrained to human limits would definitely add an interesting dimension to the matchup, as it could truly demonstrate how human-like the large language model could be like in real-time scenarios.
Tesla has passed a key milestone, and it was one that CEO Elon Musk initially mentioned more than nine years ago when he published Master Plan, Part Deux.
As per Tesla China in a post on its official Weibo account, the company’s Autopilot system has accumulated over 10 billion kilometers of real-world driving experience.
Tesla China’s subtle, but huge announcement
In its Weibo post, Tesla China announced that the company’s Autopilot system has accumulated 10 billion kilometers of driving experience. “In this respect, Tesla vehicles equipped with Autopilot technology can be considered to have the world’s most experienced and seasoned driver.”
Tesla AI’s handle on Weibo also highlighted a key advantage of the company’s self-driving system. “It will never drive under the influence of alcohol, be distracted, or be fatigued,” the team wrote. “We believe that advancements in Autopilot technology will save more lives.”
Tesla China did not clarify exactly what it meant by “Autopilot” in its Weibo post, though the company’s intense focus on FSD over the past years suggests that the term includes miles that were driven by FSD (Beta) and Full Self-Driving (Supervised). Either way, 10 billion cumulative miles of real-world data is something that few, if any, competitors could compete with.
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Elon Musk’s 10-billion-km estimate, way back in 2016
When Elon Musk published Master Plan Part Deux, he outlined his vision for the company’s autonomous driving system. At the time, Autopilot was still very new, though Musk was already envisioning how the system could get regulatory approval worldwide. He estimated that worldwide regulatory approval will probably require around 10 billion miles of real-world driving data, which was an impossible-sounding amount at the time.
“Even once the software is highly refined and far better than the average human driver, there will still be a significant time gap, varying widely by jurisdiction, before true self-driving is approved by regulators. We expect that worldwide regulatory approval will require something on the order of 6 billion miles (10 billion km). Current fleet learning is happening at just over 3 million miles (5 million km) per day,” Musk wrote.
It’s quite interesting but Tesla is indeed getting regulatory approval for FSD (Supervised) at a steady pace today, at a time when 10 billion miles of data has been achieved. The system has been active in the United States and has since been rolled out to other countries such as Australia, New Zealand, China, and, more recently, South Korea. Expectations are high that Tesla could secure FSD approval in Europe sometime next year as well.
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Elon Musk’s Boring Company reveals Prufrock TBM’s most disruptive feature
As it turns out, the tunneling startup, similar to other Elon Musk-backed ventures, is also dead serious about pursuing reusability.
The Boring Company has quietly revealed one of its tunnel boring machines’ (TBMs) most underrated feature. As it turns out, the tunneling startup, similar to other Elon Musk-backed ventures, is also dead serious about pursuing reusability.
Prufrock 5 leaves the factory
The Boring Company is arguably the quietest venture currently backed by Elon Musk, inspiring far fewer headlines than his other, more high-profile companies such as Tesla, SpaceX, and xAI. Still, the Boring Company’s mission is ambitious, as it is a company designed to solve the problem of congestion in cities.
To accomplish this, the Boring Company would need to develop tunnel boring machines that could dig incredibly quickly. To this end, the startup has designed Prufrock, an all-electric TBM that’s designed to eventually be fast enough as an everyday garden snail. Among TBMs, such a speed would be revolutionary.
The startup has taken a step towards this recently, when The Boring Company posted a photo of Prufrock-5 coming out of its Bastrop, Texas facility. “On a rainy day in Bastrop, Prufrock-5 has left the factory. Will begin tunneling by December 1. Hoping for a step function increase in speed,” the Boring Company wrote.
Prufrock’s quiet disruption
Interestingly enough, the Boring Company also mentioned a key feature of its Prufrock machines that makes them significantly more sustainable and reusable than conventional TBMs. As per a user on X, standard tunnel boring machines are often left underground at the conclusion of a project because retrieving them is usually more expensive and impractical than abandoning them in the location.
As per the Boring Company, however, this is not the case for its Prufrock machines, as they are retrieved, upgraded, and deployed again with improvements. “All Prufrocks are reused, usually with upgrades between launches. Prufrock-1 has now dug six tunnels,” the Boring Company wrote in its reply on X.
The Boring Company’s reply is quite exciting as it suggests that the TBMs from the tunneling startup could eventually be as reusable as SpaceX’s boosters. This is on brand for an Elon Musk-backed venture, of course, though the Boring Company’s disruption is a bit more underground.
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Tesla accused of infringing robotics patents in new lawsuit
Tesla is being accused of infringing robotics patents by a company called Perrone Robotics, which is based out of Charlottesville, Virginia.
The suit was filed in Alexandria, Virginia, and accuses Tesla of knowingly infringing upon five patents related to robotics systems for self-driving vehicles.
The company said its founder, Paul Perrone, developed general-purpose robotics operating systems for individual robots and automated devices.
Perrone Robotics claims that all Tesla vehicles utilizing the company’s Autopilot suite within the last six years infringe the five patents, according to a report from Reuters.
Tesla’s new Safety Report shows Autopilot is nine times safer than humans
One patent was something the company attempted to sell to Tesla back in 2017. The five patents cover a “General Purpose Operating System for Robotics,” otherwise known as GPROS.
The GPROS suite includes extensions for autonomous vehicle controls, path planning, and sensor fusion. One key patent, U.S. 10,331,136, was explicitly offered to Tesla by Perrone back in 2017, but the company rejected it.
The suit aims to halt any further infringements and seeks unspecified damages.
This is far from the first suit Tesla has been involved in, including one from his year with Perceptive Automata LLC, which accused Tesla of infringing on AI models to interpret pedestrian/cyclist intent via cameras without licensing. Tesla appeared in court in August, but its motion to dismiss was partially denied earlier this month.
Tesla also settled a suit with Arsus LLC, which accused Autopilot’s electronic stability features of infringing on rollover prevention tech. Tesla won via an inter partes review in September.
Most of these cases involve non-practicing entities or startups asserting broad autonomous vehicle patents against Tesla’s rapid iteration.
Tesla typically counters with those inter partes reviews, claiming invalidity. Tesla has successfully defended about 70 percent of the autonomous vehicle lawsuits it has been involved in since 2020, but settlements are common to avoid discovery costs.
The case is Perrone Robotics Inc v Tesla Inc, U.S. District Court, Eastern District of Virginia, No. 25-02156. Tesla has not yet listed an attorney for the case, according to the report.