Connect with us

News

Trump aims to create framework for self-driving vehicles: report

Credit: @WholeMars/YouTube

Published

on

A report shared over the weekend claims that the transition team for President-elect Donald Trump is looking to create a federal framework for self-driving vehicles—and to make the sector a top priority in the upcoming term.

Trump’s transition team is looking to create federal rules for the rollout of autonomous vehicles, according to people familiar with the matter in a report from Bloomberg on Sunday. The news comes as Tesla and others are developing and deploying autonomous vehicles, and as Elon Musk has officially been named a co-leader of the Department of Government Efficiency (DOGE) for the Trump administration.

The sources also said that autonomy laws would be a major priority for the U.S. Department of Transportation after past efforts to increase the number of available permits for self-driving vehicles have been thwarted. According to additional people familiar with the matter who spoke under the condition of anonymity, the Trump team is also actively looking to find policy leaders to help develop the guidelines.

Currently, the National Highway Traffic Safety Administration (NHTSA) lets manufacturers deploy as many as 2,500 self-driving vehicles per year under a granted exemption, though attempts to increase allowed units to 100,000 have been unsuccessful. Self-driving vehicles without a steering wheel or accelerator pedals—such as Tesla’s recently unveiled Cybercab—aren’t currently permitted to be deployed en masse, but many think that such a move from Trump could accelerate the deployment of the technology.

Tesla, Waymo, and others developing self-driving vehicles

Currently, Tesla owners can purchase and use the company’s Supervised Full Self-Driving (FSD) to access semi-autonomous driving, though drivers are expected to be attentive and prepared to retake control of the vehicle at any moment. Tesla also unveiled its two-seat Cybercab last month, expected to be based on FSD and to enter production in 2026.

Advertisement
-->

Below you can see our first ride in the Cybercab from the We, Robot unveiling event.

While Tesla doesn’t currently operate a paid ride-hailing service like the Alphabet-owned Waymo, or others working toward this model, the company has teased an app based on an FSD ride-hailing service in the past. Additionally, many within the Tesla community claim that FSD will be more scalable than its competitors, due in part to its training of an AI neural network using millions of clips of real-time driving footage from FSD Supervised users.

Other companies such as Amazon-owned Zoox, General Motors-run (GM-run) Cruise, and still many others have also deployed driverless ride-hailing services to varying degrees of success. While California has been one of a few states where self-driving services have been able to start deployment in limited quantities, autonomous driving has also come under fire from regulators and authorities following a few cases of accidents and traffic violations.

Nonetheless, the development of a federal framework for autonomous vehicles could affect how this happens on a national level—and it will likely come to the benefit of Musk and Tesla, especially given the CEO’s closeness with Trump.

Advertisement
-->

Tesla’s next step of dominance comes from Trump EV tax credit policy: Wedbush

Elon Musk and Trump’s Department of Government Efficiency

Musk will lead Trump’s newly created DOGE division in tandem with Vivek Ramaswamy, with the department aiming to “dismantle government bureaucracy” and cut down on government spending. The Tesla CEO initially endorsed Trump in July during his presidential campaign, later forming the political action committee (PAC) America PAC in support of the now-President-elect.

In addition to the financial support, Musk was a vocal backer of Trump’s campaign at rallies and in online media appearances, saying last month that Trump “must win to preserve the Constitution and democracy.” Many have also debated whether Trump’s removal of the federal $7,500 electric vehicle (EV) tax credit would be bad for Tesla and other EV makers, though Musk has said that it will likely only benefit Tesla.

The recent support for Trump also follows an ongoing set of feuds Musk has had with President Joe Biden during his presidency, as was sparked by Tesla not being invited to the administration’s EV summit, and by Biden claiming that GM had been the leader in EV deployment. Musk said in July that Biden is “utterly controlled” by the United Automotive Workers (UAW), following multiple criticisms of the union in the past.

What are your thoughts? Let me know at zach@teslarati.com, find me on X at @zacharyvisconti, or send us tips at tips@teslarati.com.

Former Tesla executive warns of delays to European ADAS regulations
Advertisement
-->

Zach is a renewable energy reporter who has been covering electric vehicles since 2020. He grew up in Fremont, California, and he currently lives in Colorado. His work has appeared in the Chicago Tribune, KRON4 San Francisco, FOX31 Denver, InsideEVs, CleanTechnica, and many other publications. When he isn't covering Tesla or other EV companies, you can find him writing and performing music, drinking a good cup of coffee, or hanging out with his cats, Banks and Freddie. Reach out at zach@teslarati.com, find him on X at @zacharyvisconti, or send us tips at tips@teslarati.com.

Advertisement
Comments

News

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.

Published

on

Credit: Grok Imagine

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.”

Advertisement
-->

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.

Continue Reading

News

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. 

Published

on

Credit: Grok

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.

Advertisement
-->

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.

Continue Reading

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.

Published

on

UK Government, CC BY 2.0 , via Wikimedia Commons

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.”

Advertisement
-->

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. 

Continue Reading