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US Department of Defense commits $2B to training AI to have “common sense”
While artificial intelligence is being painted by companies and government as the catch-all answer to many of today’s inefficiencies and problems, it currently has one glaring shortcoming: It can’t answer common sense questions.
In an effort to address this current shortcoming of AI, The U.S. Department of Defense (DoD) is committing $2 billion dollars over the next five years to its Machine Common Sense (MCS) Program. The program aims to enable computers to communicate naturally, behave reasonably in new situations, and learn from new experiences.
Thanks in part to Iron Man (and Elon Musk) fame, the Defense Advanced Research Projects Agency, aka “DARPA”, an agency within the DoD, may be one of the few alphabet soup government agencies with a future-tech-savvy reputation. That reputation is well deserved, too, if history has anything to say about it. As the agency that gave us the Internet through an extension of a defense communication project, just having a discussion online about DARPA itself is testament to the tech potential it represents. The challenge of creating true, thinking computers is perfectly aligned with what DARPA has done well with overall.

As the advancement of computer technology increases at a near exponential rate, so too has the potential relationship between them and humans. However, the possibility of a troubling disconnect is also a growing reality. In other words, humans and computers currently operate very differently from one another, and that could spell bad things for the weaker logician of the two. Yeah, that means us.
Elon Musk has famously harped about this predicted disconnect on numerous occasions, and one of the companies he’s invested in, Neuralink, is working on preemptive solutions for its coming problems. While Neuralink generally aims to help human brains work more like computers, DARPA is taking the approach of having computers work more like humans.
The term “common sense” can often be tossed around in conversations to imply a variety of shared knowledge bases, but as a federal government agency, DARPA has its own specific definition for this context: “The basic ability to perceive, understand, and judge things that are shared by nearly all people and can be reasonably expected of nearly all people without need for debate.” By mimicking the cognitive processes we go through when we are young, the agency hopes computers will develop the “fundamental building blocks of intelligence and common sense” just like a human.
With advanced neural networks making amazing (and humorous) headlines regularly, what would a “common sense” machine bring to the table in terms of advancement? One primary answer is the requirement for less initial information. To quote Dr. Brian Pierce, director of DARPA’s Innovation Office, at a recent summit, “We’d like to get away from having an enormous amount of data to train neural networks.” If a machine could use its environment to deduct answers when compared to its existing knowledge base, as humans do, it wouldn’t need to be taught to interpret data solely based on an enormous amount of data previously provided. Essentially, it could think for itself using common sense.
DARPA has now completed a “Proposers Day” wherein potential contractors were presented with the agency’s specifics for its MCS program. The next step is a “Broad Agency Announcement”, i.e., a formal invitation for proposals to work on the project with the hope of obtaining a federal contract to fulfill its aim.
If the contract winner is successful, will common sense lead to computer behavior we’d welcome rather than fear? Hopefully that will be figured out sooner rather than later.
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.