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Tesla’s Elon Musk details Model Y manufacturing improvements, insight on design
Tesla CEO Elon Musk recently revealed improvements the all-electric car maker has made to its production process for the Model Y crossover SUV. In an interview on Ride the Lightning podcast, hosted by Ryan McCaffrey, Musk discussed lessons learned from Tesla’s prior transition from the Model S to the Model X as applicable to the Model Y, as well as decisions made from the vehicle’s outgrowth of the Model 3. He additionally provided some insight on the design decisions behind the Model 3, which also carry over to the Model Y’s design.
Musk and McCaffrey’s discussion about the Model Y production process began with the question, “What are the biggest lessons learned from the Model 3 program that you’re applying to the Model Y?” However, Musk indicated that a more relative learning comparison came from Tesla’s design of the Model X and its departure from the Model S.
“The Model X ended up being a radical departure from the S…with the Model Y, we wanted to avoid the technology bandwagon we had with the X. It should have been easy going from S to X, but instead, it was hell because of so many new technologies…It would be too risky to the company to do that with the Y,” Musk explained.
I'm celebrating episode 200 of Ride the Lightning, my weekly @Tesla podcast, in THE BEST way possible: a 1-hour interview with @elonmusk himself! 🥳 I can't wait to share our conversation with all of you! It airs this Sunday, June 2 @ 9am ET/6am PT on major podcast services. 🚗⚡️ pic.twitter.com/V0nFrU03Ir
— Ryan McCaffrey (@DMC_Ryan) May 30, 2019
The Model Y crossover needed to address the flexibility expected of vehicles in its class such as cargo capacity, seating for 6 or 7 people, and more ride height than a sedan. Tesla addressed these features while also keeping in mind the effect on battery range a larger vehicle might have, according to Musk.
“We tried to make the car as similar to the [Model 3] as possible except in the case where a change was necessary to achieve SUV functionality…[all] while still having a low drag coefficient and not increasing the frontal area too much,” he detailed. Overall, Musk concluded that CdA (automobile drag coefficient) and mass of the Model Y only affect 8-10% of the battery range when compared to the Model 3.
The design of Tesla’s Model Y and lessons learned from Model 3 production also led to some manufacturing improvements for the electric crossover. Musk detailed how the Model Y underbody was switched to aluminum casting instead of stamped steel and aluminum pieces, which greatly simplifies the moving parts involved in making the vehicle.
This change effectively means that initially, using two castings to make the structure will take the process from 70 parts to 4 (castings plus joiners), and once the “big” casting machine comes into operation, the process will have brought the process from 70 parts to 1 (casting only). Using casting over stamping reduces the weight of the Model Y, improves MHB (heat produced), lowers cost due to the smaller number of parts necessary, and significantly drops capital expenditure on robots.
As for the manufacturing location of the Model Y, Musk said the decision was not quite final, but the default place was Tesla’s factory in Fremont, California, with the runner-up being Gigafactory 1 in Sparks, Nevada. Producing the Model Y in Fremont would be the fastest way to bring the crossover SUV into production, according to Musk. “One choice isn’t natural over other,” he said. Freemont is producing the Model 3 and the two vehicles share 75% of their components, but Gigafactory 1’s location has a lower cost of living, meaning an overall better value for Tesla.
The similarities between the Model Y and Model 3 being what they are, Musk also discussed with McCaffrey some of the design decisions that initially went into creating the Model 3. In response to the question, “What’s the toughest design decision you had to make on Model 3?”, the CEO cited two primary factors that went into the midsize sedan’s creation: the touchscreen and the nose design.
Reducing the number of screens from two in the Model S to one in the Model 3 came with some pushback, Musk explained. However, he felt that owners would prefer an open view of the road, and everything needed while driving could be fit onto one screen.
This background brought up community rumors about a heads-up display (HUD) being included in Tesla’s vehicles. On the subject, Musk set the record straight – there was never any plan to include a HUD, nor will one be added in the future. He simply doesn’t like them, and the move to self-driving makes them pointless. “We discussed it, but I’ve tried various heads up displays and found they were annoying,” he said. “We felt the car would increasingly go to self-driving…As things are approaching autonomy, why project things you don’t even care about on the screen?”
Something that customers do care about, though, is the look of their car. Musk detailed the difficulties in making an attractive design for the Model 3, which wasn’t easy thanks to the lack of a front grill on the vehicle. “You don’t want to have the nose to look like Voldemort…You’ve got to get some character or it does not look good.”
Also mentioned was the decision to reduce the width of the Model 3 to 185 cm over the 195 cm of the Model S to help sell more cars in Japan. The country’s parking machines only accept cars up to 195.4 cm wide, which leaves very little wiggle room in the manufacturing process to meet. The change to 185 cm meant that any Tesla Model 3 could fit in any parking garage in Japan.
The Model Y is set to begin production in 2020, and reservations are currently open on Tesla’s website.
Listen to McCaffrey’s full Ride the Lightning podcast interview here.
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
