News
No, Tesla wasn’t “cheated” in the Model 3 headlight safety test by the IIHS
With the Insurance Institute for Highway Safety’s release of initial crash test information for the Tesla Model 3 came cries from many in the electric vehicle community that Tesla was “being cheated.” This isn’t entirely true as the new IIHS test removes a lot of cars out of the Top Safety Pick+ rating, the highest accolade the independent safety tester will give a car.
The Insurance Institute for Highway Safety (IIHS) is an independent testing organization funded by insurance companies and some of the banks who back them. The IIHS purchases every car it tests–usually several of each–and tests these vehicles in their highest-available safety configuration. These crash tests usually destroy the vehicles in question, of course, but give an independent, third-party result not otherwise available.
When the IIHS’ initial safety results for the Tesla Model 3 were released, they included ratings for only two of the seven total ratings given to a vehicle. Those ratings, posted to the IIHS.org website, created a lot of response from the community regarding the failure of the Model 3’s headlamps to pass muster.
The tests so far include only the non-invasive, non-destructive tests normally conducted by the IIHS. Namely to crash mitigation systems and headlamps. It’s likely that the next test to see release on the Model 3 will be for LATCH child safety system use, another non-destructive test. From there, crash testing will begin. For that, IIHS needs to receive more Model 3 vehicles (5 in all), the rest of which are on order and expected later this year. Like any other Model 3 buyer, delays in manufacturing have put the IIHS’ ownership of the cars for evaluation on hold.
How the IIHS Conducts Headlight Tests, and Why
The IIHS conducts headlamps tests because, according to the organization, about half of all fatal crashes in the U.S. occur in the dark and many of those are on unlit roads where headlamps are the only thing illuminating whatever’s in front of the car. Although headlights are mandatory and minimum illumination requirements are required by law for all street-legal vehicles, there is a wide variance in how much (and how useful) that illumination can be. Especially with the advent of new lighting technologies.
“Headlight technology has been developing rapidly in recent years. LED and high-intensity discharge (HID) lamps have begun to replace the traditional halogen ones,” IIHS explains on its website. “Many automakers offer curve-adaptive headlights, which respond to steering and swivel according to the direction of travel. Many also offer high-beam assist, a feature that can increase the use of high beams..” These and other variables mean that headlights of the same type on one vehicle can be much worse than they can on another. Even little things like how the lights are focused, what type of light they emit, etc. can change effectiveness.
[Credit: Parker Smith via YouTube]
For those reasons, the IIHS instituted a headlight testing methodology in 2016. Starting this year (2018), these test results directly affect a vehicle’s eligibility for Top Safety Pick+ status. So far in 2018, only a handful of models have received TSP+ ratings. Somewhat surprising for luxury and high-end car buyers is the fact that almost all of those TSP+ vehicles are lower-end vehicles from makes like Hyundai and Subaru.
Testing for headlamps is conducted using a multi-part evaluation using a hypothetical, clear, two-lane road. The tests include measurements in a straightaway, measuring both the length and amount of illumination as well as the amount of glare the lights create for oncoming drivers. Then a gradual left- and right-hand turn and a steeper left- and right-hand curve are measured for a total of five directions in all.
Results are taken from varied distances at 10 inches high and 3-feet, 7-inches high (from the ground) to mimic where the driver is looking (out and down) and where oncoming vehicle drivers are seeing from (higher up). Ratings are then assigned according to how these measurements line up with a hypothetical ideal headlight system. Both low and high beams are tested the same way with the low beams being weighted for scoring as they are used most often in the real world. Vehicles with automatic high beam systems are given more points as the high beams will be used more often.
The Controversy Surrounding the IIHS Headlight Test
The inherent weakness in this IIHS test is similar to that of most of its advanced testing: it’s only tested on the ideal vehicle trim level and options. In other words, the testing is most likely happening on the most expensive model being sold, not necessarily on the most mainstream version of the vehicle. This becomes obvious when the bulk of the Top Safety Pick+ list is comprised of vehicles like the 2018 Subaru WRX.
The WRX is a great car, sure; a personal favorite in fact. But its winning of a TSP+ badge is a little misleading. The volume-selling model WRX is the mid-tier Premium trim, which doesn’t include the LED headlights or the automatic high beam control tested by the IIHS. To get those, one has to go up to the more expensive Limited trim point and add the EyeSight system. That latter point can only come if the buyer of this driver’s car is willing to drop their manual transmission for a CVT. That’s another sticking point as the WRX has a large percentage of buyers who want to shift the gears themselves.
What all of this means is that the 2018 WRX is a great car, but it’s not likely to be purchased in the configuration which the IIHS used to test its headlamps with. Other cars on the TSP+ list are much the same.
The interesting note here is that unlike actual crash tests, the slightly more subjective headlamp tests of the IIHS fall into the non-destructive tests for other safety equipment that, while respected, are also flawed for the same reason: only top-end models tend to have all of that equipment on them. Unlike those other safety items, however, the headlamp tests can hurt higher-end models while lower-end options would ace them. Why? Because LED headlamps, which consistently appear to fail most of the glare testing that the IIHS does, are generally only found on top-end models or luxury vehicles. There could be a lot of reasons for that, but my personal theory is that it has to do with automakers having to find a median between maximum safe illumination and glare due to how reflective LED lamps are designed.
The current IIHS Top Safety Pick+ list includes no midsize luxury cars (which the Model 3 is considered), though the overall midsize car category has five entries. All of them with caveats as to what must be included (usually top trim point items or options). Last year, under the old rules, most midsize and midsize luxury cars made the TSP+ list and Tesla’s Model S failed to make the list in part, again, for headlights.
It’s difficult to say what will happen with the Insurance Institute’s testing going forward. Likely manufacturers will come up with solutions to receive better scores on the headlamps test, perhaps by changing LED lighting designs or gaming the IIHS tests (as they have in the past with the small front overlap).
Tesla has some smart engineers and could probably figure out a way to remedy the lighting problem that’s kept their vehicles from rating high on IIHS tests in recent years. With a mainstream attempt like the Model 3, that could become a very important goal as buyers in the midsize sedan category tend to be safety conscious consumers.
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
