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Tesla takes a step towards the Model Y’s single-piece cast with 410-ton machine purchase
When Elon Musk was interviewed in an episode of the Third Row Podcast earlier this year, he noted that the Model Y crossover’s rear underbody would eventually be built with a single-piece casting. This is quite a bold target, and one that can make the Model Y into one of the most cost-effective vehicles on the market today, electric or otherwise.
“The current version of Model Y has basically two big high-pressure diecast [HPDC] aluminum castings that are joined and there’s still a bunch of other bits that are attached. Later this year. We’ll transition to the rear underbody being a single-piece casting that also integrates the rear crash rails,” Musk remarked.
There are many advantages to using a single-piece cast for the Model Y. The vehicle could be built in a relatively simple manner by using fewer parts, helping the company optimize its production costs. Developing such a design only takes a lot of time and effort, as indicated by Elon Musk in the podcast.
“It gets better. The current castings, because you’ve got to interface with so many different things, we have to CNC-machine the interfaces and there’s a bunch of things that have to be joined; they have datums on them and that kind of thing. The single-piece casting has no CNC machining – it doesn’t even have datums. It took us a lot of iterations, by the way, to get there,” the CEO added.
It appears that Tesla is now at a point where it is ready to pursue the Model Y’s single-piece cast. As indicated in a recent report on SAE Automotive Engineering, Tesla has purchased a machine from the IDRA Group, an Italian firm that makes HPDC equipment. What is rather interesting is that the machine that Tesla purchased is a gargantuan piece of equipment capable of producing the Model Y’s special components.
The machine that Tesla purchased, called the IDRA OL6100 CS, features an upgraded locking force that’s specially designed for the Model Y’s castings. Interestingly enough, the OL6100 CS is fondly dubbed as the “Giga Press” due to its size and power. The machine is 64 feet long and 17 feet high, and it weighs a whopping 410 tons. That’s roughly as heavy as five Space Shuttles.
Laurie Harbour, president at Harbour Results Inc., a manufacturing consultancy firm, noted that the new machine could effectively optimize the Model Y’s production process. With the Giga Press in use, Harbour estimates that Tesla could save about 20% on labor cost.
“Even with a big cycle time, you eliminate all the labor to assemble pieces and subcomponents. You’re saving on automation cells, you’re saving on people. It would be tough to put dollars to it, but think of multiple suppliers doing stampings, you could save maybe 20% on labor cost. And reduction in footprint is major. My guess is that it’s a net-net efficiency gain,” she said.
What is particularly interesting is that the Model Y was already highly optimized to begin with. Unlike the early production Model 3, which featured over 70 pieces in its rear underbody, early production Model Ys only had two large casts at the rear. This was confirmed by automotive teardown expert Sandy Munro, who conducted a thorough teardown of the Tesla Model Y from top to bottom.
Reflecting on the Model Y’s current casts, Munro noted that the vehicle had “two of the biggest castings we’ve ever seen in a car,” especially one in a consumer vehicle the size of the all-electric crossover. The teardown expert stated that other companies, such as BMW and Audi, have all used castings, but nothing comes close to the one that Tesla currently uses in the Model Y. And once Tesla moves to a single-piece casting system for the vehicle, Munro noted that the American electric car maker could “win the price.”
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
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Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
