Amidst a major auto industry shift to electric vehicles (EVs) and software-driven mobility, a new survey shows that almost all drivers want to have ownership over their own vehicle data—though consumer awareness on data privacy and ownership are still lacking.
As part of a survey of over 1,300 adults who lease or own vehicles that they drive at least once a week, car insurance app Jerry reported last month that 96 percent of respondents said they should be able to own any data generated by their vehicles. Similarly, 78 percent of those surveyed reported that they were either uncomfortable or extremely uncomfortable with having their data collected by automakers already.
You can see a few insights from the survey below, or check out the full report here.
Credit: Jerry Credit: Jerry Credit: Jerry
“People were nearly unanimous” in “thinking that they should own the data that is generated by their cars,” said Henry Hoenig, Jerry data journalist, in a statement to Automotive News.
The results come as many companies plan to use vehicle data as a consistent revenue stream, including manufacturers, insurance providers, and data brokers. On the consumer side, many may not be fully aware of how their vehicles are being connected to the internet, nor how their data is being used.
Data Collection in Modern Cars and Consumer Awareness
Teslarati spoke with Andy Chatham, co-founder of the connected vehicle platform Digital Infrastructure for Moving Objects (DIMO), about vehicle data ownership and privacy. He notes that modern cars include substantial amounts of data collection, such as Tesla’s 360-degree camera view around the cars as just one example. However, he also says that consumers are less likely to be aware of their vehicles’ data collection practices than they are with their cell phones.
“Generally, your vehicle is the most expensive or the second most expensive asset that you own, and traditionally people are very aware that their phones and their computers are connected to the internet,” Chatham said. “But especially with modern cars, it’s not always obvious that the car is also connected to the internet.”
Chatham says that most automakers aren’t generally following best practices surrounding cybersecurity, noting that many let third-party sub-contractors make those decisions for them, alongside other companies in the supply chain.
“Generally, [automakers are] not following best practices when it comes to how the vehicles are networked and how cybersecurity practices are implemented,” Chatham adds.
“I see a pretty big transition from the world of buying a phone and understanding that this is a device that has a lot of data collection going on, and buying a car and maybe acknowledging that once at the beginning, but never really understanding what that actually means.”
Chatham also says companies should open up their APIs for other developers to create applications using that data, and let vehicle owners access their own vehicle data and toggle permissions directly from their cars—not unlike what Tesla is currently doing.
However, even Tesla’s approach to vehicle data may leave a few things to be desired, and the company is one of many automakers to have faced legal action over the matter. Still, the DIMO co-founder estimates that Tesla is roughly three to five years ahead of the industry, perhaps except for Rivian.
Chatham also notes that as applications for car data improve more and more, and perhaps even offer certain data monetization options for consumers, owners will become more aware of vehicle connectedness. Still, the transition to this new public paradigm could be tricky for both consumers and developers.
“In order for that to even exist in the first place, there’s a chicken and egg problem, because developers don’t want to go cut separate deals with 10 different OEMs and get them to like agree to certain terms and use different APIs. They just won’t,” Chatham adds. “They just want to build to one thing, which is what they’re used to with both. It’s honestly a big enough pain in the ass to get developers to build an iOS and Android app and deal with two separate terms of service.”
“In the car world, Toyota is the biggest automaker and they’re, what, like 15 percent of cars? So it’s not the same dynamic, and then choice is the biggest thing that allows people to protect their own privacy because a lot of consumers don’t care.”
Automakers and the Use of Vehicle Data
Earlier this year, General Motors (GM) reported ceasing a partnership with one data broker, after discovering that the company had been selling customer data to insurance companies without gaining their consent. Public backlash ensued, and affected consumers said they witnessed inexplicable increases for their monthly insurance premiums, which were ultimately traced back to the telemetry program that had shared their data.
Ford and Progressive Insurance were involved in a similar case that brought data ownership and privacy to light in 2022. Last year, Mozilla said that all 25 car companies it examined as part of a study on privacy collected more personal data than necessary, even calling them “privacy nightmares.”
Unlike some companies, Tesla doesn’t sell or rent consumer data to third-party companies, though it does collect driver information on a fleet scale for its own purposes, as the company explains on its website.
“We’re committed to protecting you anytime you get behind the wheel of a Tesla vehicle. That commitment extends to your data privacy,” Tesla writes on its web page dedicated to the topic of privacy. “Our privacy protections aim to go beyond industry standards, ensuring your personal data is never sold, tracked or shared without your permission or knowledge.”
Tesla Insurance data has driven changes to vehicle design: Elon Musk
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.
SpaceX confirmed today that it has officially signed its third massive compute deal, providing compute at its Colossus data center in Southaven, Tennessee.
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.
🚨 SpaceXAI has agreed to a new compute deal with Reflection AI.
Reflection gets access to NIVIDIA GB300s, and will pay $150M per month to SpaceXAI for the compute. pic.twitter.com/bNPare8U5u
— TESLARATI (@Teslarati) June 22, 2026
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.
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.
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.
It is safe to say SpaceX won’t be going for electric rockets anytime soon.
In a characteristically blunt reply on X, SpaceX frontman Elon Musk stated, “Unfortunately, electric rockets are impossible,” following reports that MSCI had assigned SpaceX its lowest possible ESG rating of CCC.
The assessment, issued just this past week, coinciding closely with SpaceX’s public market debut, placed the company on par with nations like Russia in sustainability scoring and cited significant risks in environmental, social, and governance areas.
MSCI flagged SpaceX’s exposure to rocket emissions and other operational impacts, alongside governance concerns such as concentrated control by Musk and limited shareholder protections. Musk’s terse comment directly addressed the environmental pillar, underscoring a core physical constraint that ESG frameworks often overlook when evaluating high-thrust industries.
Unfortunately, electric rockets are impossible
— Elon Musk (@elonmusk) June 21, 2026
Electric propulsion systems do exist and are widely used in space. Ion thrusters and Hall-effect thrusters accelerate ionized propellant, typically xenon or krypton, using electric fields, achieving very high specific impulse, often exceeding 3,000 seconds compared to roughly 300–450 seconds for chemical rockets.
This efficiency makes them ideal for satellite station-keeping, orbit raising, and deep-space missions where low thrust over long durations is sufficient. SpaceX’s own Starlink satellites employ electric propulsion for these purposes.
However, launching from Earth’s surface demands something entirely different: enormous thrust delivered rapidly to overcome gravity and atmospheric drag. A typical orbital-class booster must generate thrust far exceeding its weight, often in the millions of Newtons within seconds.
Chemical rockets achieve this through exothermic combustion of dense propellants, producing high-mass-flow, high-velocity exhaust. Electric systems, by contrast, expel very small amounts of mass at extremely high speeds. Generating equivalent thrust would require impractical onboard power levels, massive energy storage or generation systems, and prohibitive added mass, rendering the approach infeasible with current or near-term technology.
Musk has previously expressed a similar sentiment, noting a desire for electric orbital rockets while acknowledging the inescapable requirements of Newton’s third law and energy delivery. The distinction is clear: electric propulsion excels once a vehicle is already in space; it cannot replace the high-thrust chemical phase required to reach orbit from the ground.
The episode illustrates broader critiques of ESG ratings. Proponents argue they incentivize better risk management and long-term sustainability. Detractors, including Musk—who has previously called ESG a “scam”—contend that such metrics can penalize essential activities when no practical alternative exists, potentially discouraging innovation in sectors like space access.
Elon Musk dubs the S&P 500 ESG as “outrageous scam” after Tesla gets booted from index
SpaceX has sought to mitigate launch-related impacts through reusability: Falcon 9 boosters have flown more than 30 times in some cases, dramatically lowering the manufacturing and emissions burden per kilogram delivered to orbit. Starship’s design further emphasizes rapid reusability and methane propellant, which can theoretically be produced via sustainable pathways.
Ultimately, Musk’s remark serves as a reminder that certain engineering realities persist regardless of scoring systems. As humanity expands its presence in space for communications, science, and exploration, balancing genuine environmental progress with technological necessity remains a central challenge.
ESG frameworks may evolve, but the fundamental limits of electric launch propulsion are unlikely to change soon.
Tesla just trademarked ‘MEGAPOD’ with the United States Patent and Trademark Office (USPTO), its latest move in what seems to be a hint that the company is incredibly focused on its AI efforts and storage needs as compute increases.
The application carries serial number 99893717 and lists the applicant as Tesla, Inc., located at 1 Tesla Road, Austin, Texas 78725.
The filing remains in ‘live pending’ status, and it is a new application waiting for assignment to an examining attorney. It has not yet been published or registered.
Tesla just trademarked MEGAPOD
Summary:
“Modular data center hardware systems for artificial intelligence computing, comprised of computer servers, computer hardware for artificial intelligence processing, computer networking hardware, electrical power distribution units, and… pic.twitter.com/3l85DsKadl— Robin (@xdNiBoR) June 19, 2026
According to the official goods and services description in the application, Tesla describes ‘MEGAPOD’ as:
“Modular data center hardware systems for artificial intelligence computing, comprised of computer servers, computer hardware for artificial intelligence processing, computer networking hardware, electrical power distribution units, and cooling systems, sold as a unit; self-contained modular computing hardware systems for artificial intelligence workloads; integrated computer hardware platforms for artificial intelligence computing, namely, enclosures containing computer hardware, power distribution hardware, and cooling hardware, sold as a unit; downloadable software for monitoring, managing, optimizing, and regulating modular artificial intelligence computing hardware systems.”
This description specifies complete, self-contained modular units that integrate servers and specialized AI processing hardware with networking components, power distribution, and cooling systems. It also includes associated downloadable software for oversight and optimization of these systems. The language emphasizes hardware sold “as a unit” and enclosures that combine the necessary elements for AI computing workloads.
Tesla has an established history of developing and commercializing modular hardware systems. Its Megapack product line, for example, consists of utility-scale battery energy storage systems designed as containerized units for grid applications. The MEGAPOD filing follows a similar pattern of protecting a name for modular, integrated hardware platforms, this time focused on artificial intelligence computing infrastructure.
This could be an early move, especially as Tesla did not have trademark rights to the word ‘Cybercab,’ the name of its self-driving, ride-hailing-focused vehicle.
Trademark applications of this type allow companies to secure priority rights to a name for defined categories of goods and services. The USPTO examines applications for compliance with legal requirements, including distinctiveness and absence of conflicts with prior marks. If the application proceeds successfully through examination, publication, and any opposition period, it could result in a federal trademark registration providing nationwide protection. This is what Tesla’s obvious intention is with ‘MEGAPOD.’
Public reports and analysis suggest MEGAPOD could represent modular, container-style AI computing pods designed for easy deployment. These would bundle servers, AI accelerators, power systems, and cooling into self-contained units suitable for distributed AI workloads. This approach aligns with Tesla’s announced AI compute strategy.
In March 2026, Elon Musk outlined plans for “Digital Optimus” (also referred to as Macrohard), a joint Tesla-xAI project for AI agents capable of handling complex digital tasks. The plans include running these agents on Tesla’s AI4 hardware in parked vehicles as well as dedicated compute units installed at Supercharger stations, which collectively offer substantial unused electrical capacity.
What is Digital Optimus? The new Tesla and xAI project explained
A modular hardware platform like the one described in the ‘MEGAPOD’ filing would support scalable, rapid deployment of such distributed compute resources. It could complement Tesla’s other AI infrastructure efforts, including the Dojo supercomputer used for training models and the development of AI systems for autonomous driving and robotics, by enabling edge or regional AI inference without reliance on traditional centralized data centers.
SpaceX confirms third massive compute deal at Colossus data center
Elon Musk responds to SpaceX’s ESG rating and says its rockets won’t go electric
