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Tesla’s in-house Dojo chip teased by legendary engineer ahead of AI Day
Ahead of Tesla’s AI Day scheduled for August 19th, legendary mechanical engineer Dennis Hong has teased a picture of what could be Tesla’s Dojo Chip. While Dojo is a Supercomputer that Tesla Head of Autonomy Andrej Karpathy released photographs of recently, Dojo uses an in-house chip, according to Elon Musk, along with a computer architecture optimized for Neural Net Training.
Hong, who has been a professor at the University of California, Los Angeles Samueli School of Engineering for several years, has an interest in robotic platforms, autonomous vehicles, and machine design. Interestingly, in 2011, Hong presented a TED Talk about the possibilities of making a car for blind people. During the presentation, Hong told attendees about the DARPA Urban Challenge, where he and his team of engineers developed a fully autonomous car that would automatically reach its destination without intervention. In 2007, when the Urban Challenge was completed, Hong and Co. placed third in the competition, taking home a cool $500,000 prize to continue developing self-driving techniques, among other things.
Hong dished out some added anticipation to Tesla’s AI Day event by sending out a picture of what is likely the in-house chip that Musk talked about in September 2020. “Dojo uses our own chips,” Musk said. Unlike most automakers, Tesla aims to develop most of its software and hardware in-house, especially when it comes to its autonomy projects. While Hong was unwilling to confirm or deny what his professional relationship with Tesla is, his expertise could likely have contributed to the development of Dojo and the autonomous driving project that the company has worked on for years.
#Tesla #AI day
August 19, 2021
Palo Alto, CA
5 p.m. PDT pic.twitter.com/4zsP9cVxh5— Dennis Hong (@DennisHongRobot) August 3, 2021
Tesla has been developing its own chips since 2016, led by Jim Keller. Ultimately, Tesla wanted to design chips in-house so it knew all of the components and could likely sell the chip to other manufacturers later on. In 2019 at Autonomy Day, it unveiled Hardware 3.0, a chip that Elon Musk said was “objectively the best chip in the world.” Earlier this year, it was rumored that Tesla was working with Samsung to develop a new 5nm semiconductor chip that would assist with autonomous driving software.
Dojo is undoubtedly being developed in-house, but that does not mean Tesla will not attempt to gain the expertise and experience of some of the world’s most intelligent and accomplished engineers. With at least 14 years of experience in the field of self-driving cars, Hong may be the perfect candidate to help Tesla perfect and unveil the future of autonomous driving later this month. At AI Day, it is unknown what will be talked about or released as of right now, but there is obvious speculation that details regarding Tesla’s long-awaited Dojo could be released.
After announcing Dojo last year, Musk and Co. have remained relatively quiet regarding its development, but the company has continuously released updates to its Full Self-Driving Beta suite. Musk says updates will come “every 2 weeks on Friday” at midnight Pacific Standard Time.
Despite Tesla’s development and incremental improvements with nearly every software update, it is nowhere near completed. Instead, the strategy was to transition Tesla’s entire FSD strategy from what Musk called ~2.5D to 4D. Essentially, Musk wanted to transition the FSD Neural Network to a video format. Adding timestamps for more accuracy, the complexity of Dojo is likely something that will not only improve the accuracy of Tesla’s vehicles when FSD and Autopilot are operational, but it also will increase performance at a more drastic rate due to the increased rate of data capture. The massive amount of data that Dojo will comprehend requires one of the world’s strongest and most robust computer systems.
While Tesla hinted toward the release of Dojo late last year, it will not be ready until late 2021 at the earliest. It is unknown if Tesla will unveil Dojo at the event or give a simple progress update.
Elon Musk
Starlink passes 9 million active customers just weeks after hitting 8 million
The milestone highlights the accelerating growth of Starlink, which has now been adding over 20,000 new users per day.
SpaceX’s Starlink satellite internet service has continued its rapid global expansion, surpassing 9 million active customers just weeks after crossing the 8 million mark.
The milestone highlights the accelerating growth of Starlink, which has now been adding over 20,000 new users per day.
9 million customers
In a post on X, SpaceX stated that Starlink now serves over 9 million active users across 155 countries, territories, and markets. The company reached 8 million customers in early November, meaning it added roughly 1 million subscribers in under seven weeks, or about 21,275 new users on average per day.
“Starlink is connecting more than 9M active customers with high-speed internet across 155 countries, territories, and many other markets,” Starlink wrote in a post on its official X account. SpaceX President Gwynne Shotwell also celebrated the milestone on X. “A huge thank you to all of our customers and congrats to the Starlink team for such an incredible product,” she wrote.
That growth rate reflects both rising demand for broadband in underserved regions and Starlink’s expanding satellite constellation, which now includes more than 9,000 low-Earth-orbit satellites designed to deliver high-speed, low-latency internet worldwide.
Starlink’s momentum
Starlink’s momentum has been building up. SpaceX reported 4.6 million Starlink customers in December 2024, followed by 7 million by August 2025, and 8 million customers in November. Independent data also suggests Starlink usage is rising sharply, with Cloudflare reporting that global web traffic from Starlink users more than doubled in 2025, as noted in an Insider report.
Starlink’s momentum is increasingly tied to SpaceX’s broader financial outlook. Elon Musk has said the satellite network is “by far” the company’s largest revenue driver, and reports suggest SpaceX may be positioning itself for an initial public offering as soon as next year, with valuations estimated as high as $1.5 trillion. Musk has also suggested in the past that Starlink could have its own IPO in the future.
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NVIDIA Director of Robotics: Tesla FSD v14 is the first AI to pass the “Physical Turing Test”
After testing FSD v14, Fan stated that his experience with FSD felt magical at first, but it soon started to feel like a routine.
NVIDIA Director of Robotics Jim Fan has praised Tesla’s Full Self-Driving (Supervised) v14 as the first AI to pass what he described as a “Physical Turing Test.”
After testing FSD v14, Fan stated that his experience with FSD felt magical at first, but it soon started to feel like a routine. And just like smartphones today, removing it now would “actively hurt.”
Jim Fan’s hands-on FSD v14 impressions
Fan, a leading researcher in embodied AI who is currently solving Physical AI at NVIDIA and spearheading the company’s Project GR00T initiative, noted that he actually was late to the Tesla game. He was, however, one of the first to try out FSD v14.
“I was very late to own a Tesla but among the earliest to try out FSD v14. It’s perhaps the first time I experience an AI that passes the Physical Turing Test: after a long day at work, you press a button, lay back, and couldn’t tell if a neural net or a human drove you home,” Fan wrote in a post on X.
Fan added: “Despite knowing exactly how robot learning works, I still find it magical watching the steering wheel turn by itself. First it feels surreal, next it becomes routine. Then, like the smartphone, taking it away actively hurts. This is how humanity gets rewired and glued to god-like technologies.”
The Physical Turing Test
The original Turing Test was conceived by Alan Turing in 1950, and it was aimed at determining if a machine could exhibit behavior that is equivalent to or indistinguishable from a human. By focusing on text-based conversations, the original Turing Test set a high bar for natural language processing and machine learning.
This test has been passed by today’s large language models. However, the capability to converse in a humanlike manner is a completely different challenge from performing real-world problem-solving or physical interactions. Thus, Fan introduced the Physical Turing Test, which challenges AI systems to demonstrate intelligence through physical actions.
Based on Fan’s comments, Tesla has demonstrated these intelligent physical actions with FSD v14. Elon Musk agreed with the NVIDIA executive, stating in a post on X that with FSD v14, “you can sense the sentience maturing.” Musk also praised Tesla AI, calling it the best “real-world AI” today.
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Tesla AI team burns the Christmas midnight oil by releasing FSD v14.2.2.1
The update was released just a day after FSD v14.2.2 started rolling out to customers.
Tesla is burning the midnight oil this Christmas, with the Tesla AI team quietly rolling out Full Self-Driving (Supervised) v14.2.2.1 just a day after FSD v14.2.2 started rolling out to customers.
Tesla owner shares insights on FSD v14.2.2.1
Longtime Tesla owner and FSD tester @BLKMDL3 shared some insights following several drives with FSD v14.2.2.1 in rainy Los Angeles conditions with standing water and faded lane lines. He reported zero steering hesitation or stutter, confident lane changes, and maneuvers executed with precision that evoked the performance of Tesla’s driverless Robotaxis in Austin.
Parking performance impressed, with most spots nailed perfectly, including tight, sharp turns, in single attempts without shaky steering. One minor offset happened only due to another vehicle that was parked over the line, which FSD accommodated by a few extra inches. In rain that typically erases road markings, FSD visualized lanes and turn lines better than humans, positioning itself flawlessly when entering new streets as well.
“Took it up a dark, wet, and twisty canyon road up and down the hill tonight and it went very well as to be expected. Stayed centered in the lane, kept speed well and gives a confidence inspiring steering feel where it handles these curvy roads better than the majority of human drivers,” the Tesla owner wrote in a post on X.
Tesla’s FSD v14.2.2 update
Just a day before FSD v14.2.2.1’s release, Tesla rolled out FSD v14.2.2, which was focused on smoother real-world performance, better obstacle awareness, and precise end-of-trip routing. According to the update’s release notes, FSD v14.2.2 upgrades the vision encoder neural network with higher resolution features, enhancing detection of emergency vehicles, road obstacles, and human gestures.
New Arrival Options also allowed users to select preferred drop-off styles, such as Parking Lot, Street, Driveway, Parking Garage, or Curbside, with the navigation pin automatically adjusting to the ideal spot. Other refinements include pulling over for emergency vehicles, real-time vision-based detours for blocked roads, improved gate and debris handling, and Speed Profiles for customized driving styles.
Starlink passes 9 million active customers just weeks after hitting 8 million
NVIDIA Director of Robotics: Tesla FSD v14 is the first AI to pass the “Physical Turing Test”
