News
Tesla is primed for Formula E while its rivals are working in reverse
Tesla and Formula E: Will it ever happen? Probably not. At least, that’s what Elon Musk says, and he believes that production and scalability are more important. For the global EV scene, they certainly are, while professional motorsports are really just a trivial part of what Tesla does. While the company does build and create some of the fastest and highest-performing cars on Earth, it has no intentions of bringing them to a track or becoming a car company dedicated to winning shiny trophies. However, this didn’t stop other car companies from adopting different strategies.
Some companies, like BMW and Audi, for example, did their work in reverse. Years ago, when the Formula E Series became a real thing, these two companies were among the first to build a single-seat, all-electric powertrain that was extremely similar to the blazing fast F1 circuit. The only difference was that these new, sustainable racecars weren’t blaring loud motors for everyone to hear.
Instead of developing mass-market vehicles that would benefit the company in a multitude of ways, these automakers chose to work in reverse. Not focusing on building a reliable EV software infrastructure or production facilities to manufacture them in, German car companies went to their roots and focused o a few fast cars that would compete on the weekends at some of the toughest circuits in the world. But the problem is, they could have killed two birds with one stone by doing things in the correct order, which brings me to my next point: Tesla is already primed for Formula E, and it never had any intentions of competing.
A recent article from Bloomberg shows that BMW has decided to officially scrap its Formula E team at the end of this season, shifting its focus from racing and toward an intensifying EV market. The money it will save from not focusing on turning out fast laps at world-famous circuits will now be dedicated to developing EVs for consumers.
In the time that BMW has been racing in Formula E, it has only released one car: the i3, a boxy, widely unpopular car aesthetically. With plans to launch the iX, which it unveiled just last month, there are plenty of opportunities to establish a competitive lineup of all-electric cars in the future. But the focus has been all wrong from the start.
BMW didn’t have an overwhelmingly successful time in Formula E. Since it started racing in the series, which held its first race seasons ago, it has won only four races. But the company stated that it has “exhausted the opportunities to transfer Formula E’s pioneering racing technologies into passenger models.”
This is where the order of development may have been more advantageous for BMW. Now that their Formula E run is over, they have nothing to base passenger models off of, which pretty much puts them at square 1 if you take into account the i3 is not a widely popular or successful EV, to begin with.
This is where Tesla gains a real advantage in a hypothetical scenario where it would build cars for a racing series. Tesla has passenger vehicles now that could compete in several racing series, and other cars that actually have competed in racing forums like the Pikes Peak Hill Climb.
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For example, the Roadster is 0-60 in 1.9 seconds, has a quarter-mile acceleration of 8.8 seconds, and seats four people. The powertrain is already powerful enough to compete in some racing circuits, but if Tesla were to refine it slightly and build a new, more reliable chassis that would benefit racing scenarios, there is no reason that the Next-Gen Roadster wouldn’t be extremely competitive in some racing series.
The Model S Plaid is another example. It has broken multiple records, including one at the Nürburgring in Germany (which is unconfirmed) and the Laguna Seca Raceway in California. It already has the handling, speed, and downforce to take on tough tracks that are windy and difficult to maneuver. It would just take some minor refinements to make it a “racecar.”
This is where Tesla gains a significant advantage in its structure. It is irrelevant whether the company will actually race some of its cars or not, but it would be ready today if it chose to. Meanwhile, other car companies decided to build racecars first, and after seven years of R&D, they have nothing that would contribute to a highly-effective passenger car. It is like baking a cake before putting any of the ingredients together.
It doesn’t bode well for these foreign automakers, either. Unfortunately for them, Tesla is pulling away. Every day, it seems like the company is improving in range or performance or battery tech that makes its lead in the EV sector a little bit bigger than before. Now, it has four passenger cars on the road: Two sedans, a crossover, and an SUV. It has a Supercar on the way, a truck coming in the next year, a Semi that will be launched shortly. The list goes on and on, it seems, and if Tesla wanted to race a car this weekend and be competitive, it could.
It almost sounds like the priorities of these highly-complex German car companies were simply out of line. They chose to do the fun stuff first instead of focusing on the real task at hand: Getting gas cars off the road and putting electric ones on it. Instead of worrying about the issues surrounding the manufacturing processes of EVs, which took Tesla several years to figure out (and it is still a work in progress), BMW will be forced to make a full-scale commitment if it wants to be competitive within the next ten years. The decision it made could be detrimental to the future development of the company’s EV fleet. It certainly has its work cut out for it.
And if you’re wondering, Musk said Tesla would not get into racing. The big picture deals with manufacturing and scalability, and racing is really the last of the CEO’s concerns.
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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.”
News
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.