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SpaceX Starbase facilities already taking advantage of new “Port Connector Road”
SpaceX’s Starbase facilities appear to have immediately begun to take advantage of a brand new “South Port Connector Road” built by the Port of Brownsville.
Construction of the two-mile-long ~$26 million Connector Road began in August 2020 and has long been assumed to be directly related to – or at least catalyzed by – SpaceX’s growing presence in the region. The new road will directly connect the Port of Brownsville to Highway 4, effectively offering SpaceX a direct line of access between Starbase – a South Texas Starship factory and launch site – and the Gulf of Mexico. While it’s difficult to find praise for taking almost two years to construct a more or less straight 1.9-mile-long (~3 km) stretch of road, the Connector should nonetheless offer SpaceX a number of new options.
The simplest and most obvious benefit: ease of transport. The Connector Road should cut off around 5-10 miles of the 15-20-mile drive needed to deliver something from the Port of Brownsville to Starbase (or vice-versa). In theory, the reduction in driving distance doesn’t actually matter much. The real boon comes from the fact that the road could almost entirely negate the need for deliveries to use urban roads.
If SpaceX has the ability to at least temporarily use dock space closest to the Connector Road, future deliveries could feasibly spend just a few hundred feet on city streets. The rest of the journey would be spent on relatively spacious highways. For most shipping, that would be mostly irrelevant, but it’s invaluable for a company like SpaceX that regularly needs (or wants) to transport massive objects by road. Transporting any load that is exceptionally wide, long, or tall can be a relatively painful ordeal, often requiring close coordination with local police or transportation departments to – at the minimum – ensure that it can be done safely, shadow the delivery, and manage traffic.

In extreme cases, the roadway itself might have to be temporarily modified to avoid damage to power lines, cables, street lights, signs, and more. In particularly dense areas, that can dramatically increase the cost of road transport to the point that even extreme alternatives – like building a rocket factory in the middle of nowhere, for example – become alluring.
Seemingly demonstrating its utility, SpaceX appears to have immediately taken advantage of the Port Connector Road almost as soon as it was ready to use. Around February 23rd, days before the road’s ribbon-cutting ceremony and official opening, an official image shared by the Port of Brownsville shows one of five newly installed Starbase propellant tanks heading from the port to Highway 4. While not a particularly challenging payload, the sheer length of the tank would have made any alternative route painful and likely required significant traffic control for any turns. Instead, the Port Connector Road likely made it a straight shot requiring little more than a private escort or two.
The real question is whether the new road will enable the transport of entire Starships or Super Heavy boosters – or even just subsections of the rockets – from Texas to Florida and whether SpaceX will actually choose to do so. Even with the Port Connector Road, some power lines, signs, and lights would likely need to be temporarily removed for SpaceX to transport something as tall and wide as a Starship or Super Heavy, but the breadth of the work required has likely been reduced by at least an order of magnitude. SpaceX has already broken ground on what is expected to become a Florida Starship factory but even partially completing that facility to the point that it can start to build rockets could easily take 6-12 months.
In short, the Port Connector Road’s benefits might be enough for SpaceX to conclude that the one-off transport of a handful of Starships and Super Heavy boosters is worth the lowered cost. That will be especially true if SpaceX is effectively forced to restart Starbase’s environmental review process, in which case Florida – not Texas – could become the preferred location for Starship’s first orbital test flights.
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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.
Elon Musk
Elon Musk’s Grok records lowest hallucination rate in AI reliability study
Grok achieved an 8% hallucination rate, 4.5 customer rating, 3.5 consistency, and 0.07% downtime, resulting in an overall risk score of just 6.
A December 2025 study by casino games aggregator Relum has identified Elon Musk’s Grok as one of the most reliable AI chatbots for workplace use, boasting the lowest hallucination rate at just 8% among the 10 major models tested.
In comparison, market leader ChatGPT registered one of the highest hallucination rates at 35%, just behind Google’s Gemini, which registered a high hallucination rate of 38%. The findings highlight Grok’s factual prowess despite the AI model’s lower market visibility.
Grok tops hallucination metric
The research evaluated chatbots on hallucination rate, customer ratings, response consistency, and downtime rate. The chatbots were then assigned a reliability risk score from 0 to 99, with higher scores indicating bigger problems.
Grok achieved an 8% hallucination rate, 4.5 customer rating, 3.5 consistency, and 0.07% downtime, resulting in an overall risk score of just 6. DeepSeek followed closely with 14% hallucinations and zero downtime for a stellar risk score of 4. ChatGPT’s high hallucination and downtime rates gave it the top risk score of 99, followed by Claude and Meta AI, which earned reliability risk scores of 75 and 70, respectively.

Why low hallucinations matter
Relum Chief Product Officer Razvan-Lucian Haiduc shared his thoughts about the study’s findings. “About 65% of US companies now use AI chatbots in their daily work, and nearly 45% of employees admit they’ve shared sensitive company information with these tools. These numbers show well how important chatbots have become in everyday work.
“Dependence on AI tools will likely increase even more, so companies should choose their chatbots based on how reliable and fit they are for their specific business needs. A chatbot that everyone uses isn’t necessarily the one that works best for your industry or gives accurate answers for your tasks.”
In a way, the study reveals a notable gap between AI chatbots’ popularity and performance, with Grok’s low hallucination rate positioning it as a strong choice for accuracy-critical applications. This was despite the fact that Grok is not used as much by users, at least compared to more mainstream AI applications such as ChatGPT.