Tesla Vehicles Megathread

Seems like TESLA crashing again , 150 Billion Dollar market cap gone
USA about to cancel Electronic Vehicle EV initiative

  1. Elon appears as temporary worker in administration
  2. Negative Publicity due to Elon's budget cutting program for few months, public opinion changes fast on Elon
  3. Attack on Tesla car across US
  4. Elon not happy about his limited duration role
  5. Elon has critical views on new budget undermines his work as temporary worker
  6. Public feud Trump and Elon $150 Billion Dollar lost in matter of days
  7. Musk's lucrative US government contract about to be cancelled cutting off any funding to fuel Elon's Mars Mission
  8. Elon floats around idea to dismantle his space progam for NASA taking supplies up in space, obviously can't make money off it anymore
Source BBC News
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Note:
I don't own Tesla , nor have any Tesla shares or position
Commentary is to reflect on current affairs of Tesla Crash and possible Bankruptcy
 
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Public feud Trump and Elon $150 Billion Dollar lost in matter of days

um....


Elon Musk​

CEO, Tesla
$393.8B

Real Time Net Worth​

as of 6/7/25
 
US version of FSD in China...robotaxi tech

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Tesla FSD China At Night - No Hesitation, Absolute Confidence​


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Is Tesla FSD Smart Enough For Shenzhen Morning Traffic?​


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Tesla FSD China Can Handle Busy City Traffic As Well As Highways!​


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Night Drive Challenge With Tesla FSD In China​


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I Let My Tesla FSD Take The Wheel In Busy Shenzhen Streets​

 
19 minutes
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Tesla FSD Drives Me to Work During Morning Rush | Real City Expressway Test | 1x​


34 minutes
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Tesla FSD Drives Me to Work During Morning Rush | Real City Expressway Test | 1x​


30 minutes
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Tesla FSD Drives Me to Work During Morning Rush | Real City Expressway Test | 1x​

 
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The big day is near


  • Tesla CEO Elon Musk said in a post on X on Tuesday that Tesla robotaxi rides in Austin, Texas, are ‘tentatively’ set to begin June 22.
  • Musk said the first driverless Tesla will make a trip from the Austin factory to a customer’s house on June 28, the tech billionaire’s birthday.
  • Musk previously said that Tesla would launch a limited robotaxi pilot in Austin in June, but he hadn’t set a specific date.

Tesla CEO Elon Musk said on Tuesday that his company’s robotaxi service is “tentatively” set to launch in Austin, Texas, on June 22.

In a post on X, Musk indicated that he’s flying from Los Angeles to Austin for the kickoff, which he previously said would occur sometime in June. When a commenter asked when public rides will start, Musk said the current plan is for June 22, and that the first driverless trip from the Tesla factory to a customer’s house will take place on his birthday, June 28.

“We are being super paranoid about safety, so the date could shift,” Musk wrote.

Earlier on Tuesday, Musk shared a video on X showing that Tesla was testing driverless vehicles on the roads of Austin without a human safety supervisor behind the wheel. The eight-second clip showed the latest version of the Model Y SUV, painted black with a white “Robotaxi” graffiti-style logo painted on it, navigating an intersection and pausing to allow pedestrians to traverse a crosswalk.

Musk recently told CNBC’s David Faber that Tesla will start with a very small rollout, including about 10 to 20 of its robotaxis, with a new, “unsupervised” version of the company’s FSD or “Full Self-Driving” technology installed. The tests will involve the Model Y, not the futuristic looking CyberCab that Tesla plans to produce next year.

Musk said Tesla will “geofence” the service, limiting where the Model Y robotaxis can initially operate, and that employees will remotely monitor the fleet.

While running Tesla, Musk is also the CEO of defense contractor SpaceX and leads artificial intelligence company xAI, which has merged with his social network X (formerly Twitter.) He is also the richest person in the world, and spent nearly $300 million to propel President Donald Trump back to the White House.


Musk recently concluded a stint leading the Department of Government Efficiency, which made sweeping cuts to federal agencies, regulations and offices tasked with oversight of Tesla and his other companies.

While fans of Musk and Tesla have expressed enthusiasm for the company’s robotaxi service pilot in Austin, others with automotive safety concerns and who stand against Musk’s political ideology and activity are planning protests.

The Dawn Project, in partnership with anti-Musk activists including Tesla Takedown and Resist Austin, said in an e-mailed statement that they plan to host a demonstration on June 12 in downtown Austin to show off safety issues with Tesla’s electric vehicles and driver assistance features which are currently marketed as Autopilot and Full Self-Driving (Supervised).

Dan O’Dowd, who is CEO of both Green Hills Software and The Dawn Project, has described the latter as a tech-safety and security education business in prior interviews with CNBC. Green Hills Software makes products which are used by direct competitors of Tesla including Ford and Toyota.
 
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Outdoorsy paves the way for a robotaxi business by ordering 100 Tesla self-driving cars​


A local startup CEO is so bullish on future of Tesla's self-driving vehicles that he's beginning to build a new business model around them. In this story, we talk with the CEO about his initial order of 100 robotaxis and how he envisions they may be offered as rental vehicles or for rideshare or taxi services. The story includes background on the startup's history of renting RVs on its platform, as well as the insurance company it created to insure those RVs, as well as autonomous vehicles.

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The big day...after almost 9 years of waiting...is coming.
Even with that long delay they have somehow still beaten every other consumer car maker to market.

Oct 21, 2016
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Tesla announces fully autonomous cars | video​



Tesla Robotaxis are becoming a common sight on Austin’s public roads​

tesla-robotaxi-spotting-no-driver.jpg

no Driver...in a stock consumer car..a Tesla Model Y.
 
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Bloomberg (after 9 years of FSD dismissal) at the 11th hour suddenly wakes up and realizes Tesla may actually corner the market if they can get FSD working on consumer grade cars.

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Why Tesla Could Have a Self-Driving Advantage​

 
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invited to Try Tesla's DRIVERLESS Robotaxi!​



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Tesla Just Invited Me To Its Robotaxi Launch​

 
More 11th hour backpedalling

Waymo and Google Confirms Tesla Was Right About Robotaxi​


There is a new paper by Google and Waymo (Scaling Laws of Motion Forecasting and Planning A Technical Report that confirmed Tesla getting more miles and compute has been the right way to solve driving.

Waymno confirms that more miles of driving data and more compute to process that data is better. Tesla has about 100 times more driving data than Waymo (6 billion miles to 70 million or 500,000 miles) and has a larger compute cluster by several times.

They study the empirical scaling laws of a family of encoder-decoder autoregressive transformer models on the task of joint motion forecasting and planning in the autonomous driving domain. Using a ∼ 500 thousand hours driving dataset, we demonstrate that, similar to language modeling, model performance improves as a power-law function of the total compute budget, and we observe a strong correlation between model training loss and model evaluation metrics. Most interestingly, closed-loop metrics also improve with scaling, which has important implications for the suitability of open-loop metrics for model development and hill climbing. We also study the optimal scaling of the number of transformer parameters and the training data size for a training compute-optimal model. We find that as the training compute budget grows, optimal scaling requires increasing the model size 1.5x as fast as the dataset size. We also study inference-time compute scaling, where we observe that sampling and clustering the output of smaller models makes them competitive with larger models, up to a crossover point beyond which a larger models becomes more inference-compute efficient. Overall, our experimental results demonstrate that optimizing the training and inference-time scaling properties of motion forecasting and planning models is a key lever for improving their performance to address a wide variety of driving scenarios. Finally, we briefly study the utility of training on general logged driving data of other agents to improve the performance of the ego-agent, an important research area to address the scarcity of robotics data for large capacity models training.

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