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Elon Musk and Tesla try to save legacy automakers from Déjà vu

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tesla interior operating on full self driving
Credit: TESLARATI

Elon Musk said in late November that he’s “tried to warn” legacy automakers and “even offered to license Tesla Full Self-Driving, but they don’t want it,” expressing frustration with companies that refuse to adopt the company’s suite, which will eventually be autonomous.

Tesla has long established itself as the leader in self-driving technology, especially in the United States. Although there are formidable competitors, Tesla’s FSD suite is the most robust and is not limited to certain areas or roadways. It operates anywhere and everywhere.

The company’s current position as the leader in self-driving tech is being ignored by legacy automakers, a parallel to what Tesla’s position was with EV development over a decade ago, which was also ignored by competitors.

The reluctance mirrors how legacy automakers initially dismissed EVs, only to scramble in catch-up mode years later–a pattern that highlights their historical underestimation of disruptive innovations from Tesla.

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Elon Musk’s Self-Driving Licensing Attempts

Musk and Tesla have tried to push Full Self-Driving to other car companies, with no true suitors, despite ongoing conversations for years. Tesla’s FSD is aiming to become more robust through comprehensive data collection and a larger fleet, something the company has tried to establish through a subscription program, free trials, and other strategies.

Tesla CEO Elon Musk sends rivals dire warning about Full Self-Driving

However, competing companies have not wanted to license FSD for a handful of speculative reasons: competitive pride, regulatory concerns, high costs, or preference for in-house development.

Déjà vu All Over Again

Tesla tried to portray the importance of EVs long ago, as in the 2010s, executives from companies like Ford and GM downplayed the importance of sustainable powertrains as niche or unprofitable.

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Musk once said in a 2014 interview that rivals woke up to electric powertrains when the Model S started to disrupt things and gained some market share. Things got really serious upon the launch of the Model 3 in 2017, as a mass-market vehicle was what Tesla was missing from its lineup.

This caused legacy companies to truly wake up; they were losing market share to Tesla’s new and exciting tech that offered less maintenance, a fresh take on passenger auto, and other advantages. They were late to the party, and although they have all launched vehicles of their own, they still lag in two major areas: sales and infrastructure, leaning on Tesla for the latter.

Musk’s past warnings have been plentiful. In 2017, he responded to critics who stated Tesla was chasing subsidies. He responded, “Few people know that we started Tesla when GM forcibly recalled all electric cars from customers in 2003 and then crushed them in a junkyard,” adding that “they would be doing nothing” on EVs without Tesla’s efforts.

Companies laughed off Tesla’s prowess with EVs, only to realize they had made a grave mistake later on.

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It looks to be happening once again.

A Pattern of Underestimation

Both EVs and self-driving tech represent major paradigm shifts that legacy players view as threats to their established business models; it’s hard to change. However, these early push-aways from new tech only result in reactive strategies later on, usually resulting in what pains they are facing now.

Ford is scaling back its EV efforts, and GM’s projects are hurting. Although they both have in-house self-driving projects, they are falling well behind the progress of Tesla and even other competitors.

It is getting to a point where short-term risk will become a long-term setback, and they may have to rely on a company to pull them out of a tough situation later on, just as it did with Tesla and EV charging infrastructure.

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Tesla has continued to innovate, while legacy automakers have lagged behind, and it has cost them dearly.

Implications and Future Outlook

Moving forward, Tesla’s progress will continue to accelerate, while a dismissive attitude by other companies will continue to penalize them, especially as time goes on. Falling further behind in self-driving could eventually lead to market share erosion, as autonomy could be a crucial part of vehicle marketing within the next few years.

Eventually, companies could be forced into joint partnerships as economic pressures mount. Some companies did this with EVs, but it has not resulted in very much.

Self-driving efforts are not only a strength for companies themselves, but they also contribute to other things, like affordability and safety.

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Tesla has exhibited data that specifically shows its self-driving tech is safer than human drivers, most recently by a considerable margin. This would help with eliminating accidents and making roads safer.

Tesla’s new Safety Report shows Autopilot is nine times safer than humans

Additionally, competition in the market is a good thing, as it drives costs down and helps innovation continue on an upward trend.

Conclusion

The parallels are unmistakable: a decade ago, legacy automakers laughed off electric vehicles as toys for tree-huggers, crushed their own EV programs, and bet everything on the internal-combustion status quo–only to watch Tesla redefine the industry while they scrambled for billions in catch-up capital.

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Today, the same companies are turning down repeated offers to license Tesla’s Full Self-Driving technology, insisting they can build better autonomy in-house, even as their own programs stumble through recalls, layoffs, and missed milestones. History is not merely rhyming; it is repeating almost note-for-note.

Elon Musk has spent twenty years warning that the auto industry’s bureaucratic inertia and short-term thinking will leave it stranded on the wrong side of technological revolutions. The question is no longer whether Tesla is ahead–it is whether the giants of Detroit, Stuttgart, and Toyota will finally listen before the next wave leaves them watching another leader pull away in the rear-view mirror.

This time, the stakes are not just market share; they are the very definition of what a car will be in the decades ahead.

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Joey has been a journalist covering electric mobility at TESLARATI since August 2019. In his spare time, Joey is playing golf, watching MMA, or cheering on any of his favorite sports teams, including the Baltimore Ravens and Orioles, Miami Heat, Washington Capitals, and Penn State Nittany Lions. You can get in touch with joey at joey@teslarati.com. He is also on X @KlenderJoey. If you're looking for great Tesla accessories, check out shop.teslarati.com

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Elon Musk

SpaceX’s newest Starmind will make earth data centers obsolete

Elon Musk confirmed Starmind as SpaceX’s AI satellite constellation name, targeting one million orbital compute nodes.

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Elon Musk confirmed that Starmind will be the official name of SpaceX’s planned AI satellite constellation, following a trademark filing by xAI that surfaced earlier this week. Starmind is what’s being described to the FCC as a constellation of up to one million AI satellites

It’s worth noting that SpaceX’s Starlink communication satellite and Starmind are built on the same orbital infrastructure concept but serve entirely different purposes. Starlink is a connectivity network, with satellites receiving and relaying data between points on Earth, and functioning as a high-speed internet backbone in space. The satellites themselves do not process or think, and move information from one place to another, the same function a fiber cable performs underground.

SpaceX just forced Verizon, AT&T and T-Mobile to team up for the first time in history

Starmind, on the other hand, is something completely different, and tather than moving data, its satellites would compute data through artificial intelligence and directly in orbit using onboard processors powered by large solar arrays. Where a Starlink satellite is essentially a very fast pipe, a Starmind satellite is a server. The practical implication is that Starmind would allow AI models to run inference, process queries, and generate outputs from space, then beam results down to users anywhere on Earth within milliseconds, and without the data ever needing to travel to a terrestrial data center.

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Starship will be able to carry 30 to 50 AI1 satellites per launch, delivering the equivalent of dozens of server racks per flight, with no land acquisition, no power grid approval, and no cooling infrastructure required on the ground.

SpaceX is pursuing this new technology as terrestrial data centers are running into hard limits such as lack of physical space, community opposition, and power and water consumption at a scale that is increasingly difficult to permit. Space has unlimited solar power, natural vacuum cooling, and no zoning boards. Musk said in a June 8 video presentation that he expects space to become the lowest-cost location to deploy AI compute within two to three years. Two AI1 prototypes are scheduled to launch in early 2027, with volume production targeted for the end of that year at a new facility called Gigasat.

The real world applications Starmind enables extend well beyond powering Grok. A constellation of orbiting AI processors could run inference workloads for any paying customer, anywhere on Earth, with latency measured in milliseconds rather than the seconds associated with ground-based cloud routing across continents. Starmind, if it scales as described, would make SpaceX the landlord of AI compute the same way Starlink made it the landlord of satellite internet.

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Elon Musk

Tesla finally clarifies fatal Texas crash, confirms driver manually overrode acceleration

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Credit: CNBC

Tesla has finally clarified the situation regarding the viral crash in Texas where a Model 3 slammed into a home.

CEO Elon Musk replied to reports on Monday that stated the crash was due to the company’s Full Self-Driving or Autopilot suite, which seemed unlikely to those who are familiar with it. Video showed the car slamming into a house at an excessive rate of speed, making it highly unlikely the crash was due to the suite’s operation, as it does not travel at those speeds in residential areas.

Musk said:

“This makes no sense. FSD drives slowly through neighborhood streets, and this was a high-speed crash!”

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Tesla’s Head of AI, Ashok Elluswamy, added context, revealing that the company’s data shows the driver “manually overrode self-driving by pressing the accelerator all the way to 100%.”

He revealed the speed reached by the car was 73 MPH, and the accelerator was still pressed “even after the crash.”

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Authorities are reportedly investigating “whether Tesla’s Autopilot system played a role after a Model 3 left the roadway…slammed through a brick house at high speed and fatally struck Matha Avila as she sat inside,” the New York Post reported.

The National Highway Traffic Safety Administration (NHTSA) is now investigating the crash. Tesla will work with the agency to provide them with whatever information they need in order to clarify the cause of the crash.

Similarly, Tesla had claims of a fatal accident in Harris County, Texas, a few years ago. Early reports indicated that Full Self-Driving was the cause of the crash. After the National Transportation Safety Board (NTSB) worked with Tesla, the agency proved there was “no use of the Autopilot system at any time during this ownership period of the vehicle, including the time frame up to the last transmitted timestamp on April 17, 2021.”

Tesla alleged “driverless” crash in Texas: What is known so far

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“Application of the accelerator pedal was found to be as high as 98.8 percent,” the NTSB said in their findings. The highest recorded speed in the five seconds leading up to the impact was 67 miles per hour. The area where the crash occurred is residential, and Texas State laws have default speed limits of 30 MPH in residential streets.

This appears to be a similar situation. However, an investigation will prove what happened for sure.

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Elon Musk

SpaceX confirms third massive compute deal at Colossus data center

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Credit: xAI Memphis

SpaceX confirmed today that it has officially signed its third massive compute deal, providing compute at its Colossus data center in Southaven, Mississippi.

Reflection AI will gain immediate access to NVIDIA GB300 chips at SpaceX’s Colossus 2 data center. In return, Reflection will pay SpaceX $150 million per month starting on July 1, with total payments reaching approximately $6.3 billion if the contract runs through its duration, which is until 2029. Either party can terminate the agreement with 90 days’ notice after the initial three-month period.

CNBC first reported the deal.

This latest partnership highlights SpaceX’s strategy of commercializing its massive Colossus supercomputing infrastructure, originally developed to power Elon Musk’s Grok AI models. The company has rapidly expanded its customer base in the AI sector following its February 2026 merger with xAI, a transaction that valued the combined entity at $1.25 trillion.

SpaceX has previously signed significant compute deals with other major players.

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It granted Anthropic exclusive access to the full capacity of its Colossus 1 data center, which exceeds 300 megawatts and includes over 220,000 NVIDIA GPUs. Details from SpaceX’s IPO filings indicate Anthropic will pay $1.25 billion per month through May 2029, potentially generating around $45 billion over the term of the deal.

Additionally, Google agreed to pay SpaceX $920 million per month for compute capacity from October 2026 through June 2029. This 32-month period will provide Google access to roughly 110,000 NVIDIA GPUs, along with supporting processors and memory. Capacity ramps up through September at a reduced fee, with termination options after the first year.

SpaceXA also established arrangements for computing power with Cursor, an AI coding startup. SpaceX acquired them in a $60 billion all-stock deal.

SpaceX makes first acquisition post-IPO

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These arrangements position SpaceX’s collective position as an AI infrastructure powerhouse with high-margin revenue potential. The Google deal alone could generate nearly $29.5 billion over its term, while the Reflection contract adds another $6.3 billion.

Combined with the Anthropic arrangement, SpaceX stands to realize tens of billions in revenue from compute leasing in the coming years, which diversifies beyond SpaceX’s traditional rocket launches and Starlink operation.

The deals underscore growing demand for advanced AI training and inference capacity amid chip shortages and surging model development needs. Reflection, valued at $25 billion and focused on “American open intelligence” with government and national security ties, cited recent restrictions on closed models as validation for open-source approaches.

For SpaceX, the partnerships transform capital-intensive data centers into flexible revenue sources while supporting its broader AI ambitions after the company has gone public.

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