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Tesla Autopilot impresses in 79-minute ‘Torture Test’ through long winding roads
A Tesla Model 3 owner recently tested Autopilot’s abilities on the long and winding roads of the Blue Ridge Parkway in North Carolina. The 45.9-mile trip lasted 79 minutes, giving the driver a fair amount of insight regarding Autopilot’s performance with update 2020.16.2.1.
In a later comment on Reddit, the host of Youtube’s The Tech of Tech channel stated that he decided to test Autopilot’s capabilities on rainy, foggy roads stretching across the historic Blue Ridge Parkway in North Carolina.
“I did adjust the maximum speed to accommodate visibility due to fog as Autopilot doesn’t know to just slow down- it will shut off if it can’t see far enough for the speed. However, by lowering the maximum speed to what I’d want to drive anyway, Autopilot remains engaged. Other than that, all steering, braking, acceleration, etc. is done by the car and not me,” the driver wrote.
One notable feature of the update focused on Autopilot’s capability to slow down for sharp curves, which results in safer navigation through abrupt turns. For example, on a right turn, the car will drive closer to the right edge of the pavement, which provides a safer environment if two vehicles are driving through the same curve in opposite directions.
Tech of Tech indicates that the addition of the “Slowing for Sharp Curves” feature was the only reason the car could navigate the tricky roads of the Blue Ridge Parkway, which it did in impressive fashion.
Tesla rolled out a similar feature last year, but there were some issues with its performance that made some drivers feel uncomfortable. The company continually improved the capability, which was then released with 2020.16.2.1 to owners around May 16 this year, according to TeslaFi.com.
“This update introduced new slowing behavior. Autopilot slows much more for tight curves than before, and it does so much more smoothly than the aborted slowing behavior introduced when V10 first released,” the host said.
As could be seen in the video of the torture test, Autopilot managed to navigate through the various challenging sections of the Blue Ridge Parkway for 79 straight minutes before the car took a turn a bit too sharply, which required the driver to intervene. This instance was the only mistake that the car’s software made in almost 46 miles of driving, and that’s in questionable weather conditions and on a stretch of road that challenges even human drivers.
Tesla’s Autopilot software continues to improve through the millions of miles of driving data that owners contribute to the company’s Neural Network. Tesla CEO Elon Musk indicated during the company’s Q1 2020 Earnings Call that the Neural Net’s training was coming along nicely and that contributions were being assessed to improve the safety and performance of the company’s driver-assist features.
“We are collecting data from over 1 million intersections every month at this point. This number will grow exponentially as more people get the update, and as more people start driving again. Soon, we will be collecting data from over 1 billion intersections per month. All of those confirmations are training on neural net, essentially, the driver when driving and taking action is effectively labeling — the labeling reality as they drive, and making the neural net better and better,” Musk said.
Watch The Tech of Tech‘s Tesla Model 3 navigate the Blue Ridge Parkway below.
Elon Musk
Tesla confirms that work on Dojo 3 has officially resumed
“Now that the AI5 chip design is in good shape, Tesla will restart work on Dojo 3,” Elon Musk wrote in a post on X.
Tesla has restarted work on its Dojo 3 initiative, its in-house AI training supercomputer, now that its AI5 chip design has reached a stable stage.
Tesla CEO Elon Musk confirmed the update in a recent post on X.
Tesla’s Dojo 3 initiative restarted
In a post on X, Musk said that with the AI5 chip design now “in good shape,” Tesla will resume work on Dojo 3. He added that Tesla is hiring engineers interested in working on what he expects will become the highest-volume AI chips in the world.
“Now that the AI5 chip design is in good shape, Tesla will restart work on Dojo3. If you’re interested in working on what will be the highest volume chips in the world, send a note to AI_Chips@Tesla.com with 3 bullet points on the toughest technical problems you’ve solved,” Musk wrote in his post on X.
Musk’s comment followed a series of recent posts outlining Tesla’s broader AI chip roadmap. In another update, he stated that Tesla’s AI4 chip alone would achieve self-driving safety levels well above human drivers, AI5 would make vehicles “almost perfect” while significantly enhancing Optimus, and AI6 would be focused on Optimus and data center applications.
Musk then highlighted that AI7/Dojo 3 will be designed to support space-based AI compute.
Tesla’s AI roadmap
Musk’s latest comments helped resolve some confusion that emerged last year about Project Dojo’s future. At the time, Musk stated on X that Tesla was stepping back from Dojo because it did not make sense to split resources across multiple AI chip architectures.
He suggested that clustering large numbers of Tesla AI5 and AI6 chips for training could effectively serve the same purpose as a dedicated Dojo successor. “In a supercomputer cluster, it would make sense to put many AI5/AI6 chips on a board, whether for inference or training, simply to reduce network cabling complexity & cost by a few orders of magnitude,” Musk wrote at the time.
Musk later reinforced that idea by responding positively to an X post stating that Tesla’s AI6 chip would effectively be the new Dojo. Considering his recent updates on X, however, it appears that Tesla will be using AI7, not AI6, as its dedicated Dojo successor. The CEO did state that Tesla’s AI7, AI8, and AI9 chips will be developed in short, nine-month cycles, so Dojo’s deployment might actually be sooner than expected.
Elon Musk
Elon Musk’s xAI brings 1GW Colossus 2 AI training cluster online
Elon Musk shared his update in a recent post on social media platform X.
xAI has brought its Colossus 2 supercomputer online, making it the first gigawatt-scale AI training cluster in the world, and it’s about to get even bigger in a few months.
Elon Musk shared his update in a recent post on social media platform X.
Colossus 2 goes live
The Colossus 2 supercomputer, together with its predecessor, Colossus 1, are used by xAI to primarily train and refine the company’s Grok large language model. In a post on X, Musk stated that Colossus 2 is already operational, making it the first gigawatt training cluster in the world.
But what’s even more remarkable is that it would be upgraded to 1.5 GW of power in April. Even in its current iteration, however, the Colossus 2 supercomputer already exceeds the peak demand of San Francisco.
Commentary from users of the social media platform highlighted the speed of execution behind the project. Colossus 1 went from site preparation to full operation in 122 days, while Colossus 2 went live by crossing the 1-GW barrier and is targeting a total capacity of roughly 2 GW. This far exceeds the speed of xAI’s primary rivals.
Funding fuels rapid expansion
xAI’s Colossus 2 launch follows xAI’s recently closed, upsized $20 billion Series E funding round, which exceeded its initial $15 billion target. The company said the capital will be used to accelerate infrastructure scaling and AI product development.
The round attracted a broad group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group. Strategic partners NVIDIA and Cisco also continued their support, helping xAI build what it describes as the world’s largest GPU clusters.
xAI said the funding will accelerate its infrastructure buildout, enable rapid deployment of AI products to billions of users, and support research tied to its mission of understanding the universe. The company noted that its Colossus 1 and 2 systems now represent more than one million H100 GPU equivalents, alongside recent releases including the Grok 4 series, Grok Voice, and Grok Imagine. Training is also already underway for its next flagship model, Grok 5.
Elon Musk
Tesla AI5 chip nears completion, Elon Musk teases 9-month development cadence
The Tesla CEO shared his recent insights in a post on social media platform X.
Tesla’s next-generation AI5 chip is nearly complete, and work on its successor is already underway, as per a recent update from Elon Musk.
The Tesla CEO shared his recent insights in a post on social media platform X.
Musk details AI chip roadmap
In his post, Elon Musk stated that Tesla’s AI5 chip design is “almost done,” while AI6 has already entered early development. Musk added that Tesla plans to continue iterating rapidly, with AI7, AI8, AI9, and future generations targeting a nine-month design cycle.
He also noted that Tesla’s in-house chips could become the highest-volume AI processors in the world. Musk framed his update as a recruiting message, encouraging engineers to join Tesla’s AI and chip development teams.
Tesla community member Herbert Ong highlighted the strategic importance of the timeline, noting that faster chip cycles enable quicker learning, faster iteration, and a compounding advantage in AI and autonomy that becomes increasingly difficult for competitors to close.
AI5 manufacturing takes shape
Musk’s comments align with earlier reporting on AI5’s production plans. In December, it was reported that Samsung is preparing to manufacture Tesla’s AI5 chip, accelerating hiring for experienced engineers to support U.S. production and address complex foundry challenges.
Samsung is one of two suppliers selected for AI5, alongside TSMC. The companies are expected to produce different versions of the AI5 chip, with TSMC reportedly using a 3nm process and Samsung using a 2nm process.
Musk has previously stated that while different foundries translate chip designs into physical silicon in different ways, the goal is for both versions of the Tesla AI5 chip to operate identically. AI5 will succeed Tesla’s current AI4 hardware, formerly known as Hardware 4, and is expected to support the company’s Full Self-Driving system as well as other AI-driven efforts, including Optimus.