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How Tesla’s new Roadster can benefit from Maxwell’s supercapacitors
The new Tesla Roadster is the very definition of a halo car. Embodying all the innovations that Tesla has developed and mastered over the years, the next-gen Roadster is intended, as Elon Musk put it, to give a “hardcore smackdown” to gasoline cars. During the CEO’s appearance at the Ride the Lightning podcast, Musk even candidly mentioned that the upcoming vehicle will have capabilities that are practically “unfair” to its internal combustion-powered competition.
It has been almost two years since the vehicle was unveiled, and over this time, Tesla has made headway in its electric vehicle tech. Earlier this year, Tesla completed the acquisition of Maxwell Technologies, a company that specializes in supercapacitors and the development of dry battery electrode technology. These innovations, which Tesla has complete access to, are a perfect fit for the next-generation Roadster.
Munro and Associates Sr. Associate Mark Ellis recently noted during an interview with Tesla owner-enthusiast Sean Mitchell that Maxwell’s tech have immense potential in the electric vehicle segment. “The dry battery technology is game-changing if it comes to pass and they can put it in a car,” he said. Ellis also explained that supercapacitor technology could greatly help electric vehicles in terms of their battery management.
“One of the issues with the battery is, when I step on the throttle hard, I’m pulling a lot of energy from the battery. And then, when I brake hard, I’m pulling a lot of energy out of the regen, but the batteries can’t take it fast enough. The batteries get really stressed when you try to pull it up too much, so if I had supercapacitors that I could use as a cushion; so when I need energy quickly, (I can) pull it from the supercapacitors and then fill the supercapacitors back up with the battery slowly; and then when I brake, I can capture more of that regen energy and do the supercapacitors faster. I think that just makes logical sense, because now all of a sudden I’ve got a sponge in front of my main energy source and I’m not stressing (the battery) so much,” he said.
This “sponge” that Ellis mentioned will be greatly beneficial for vehicles like the next-generation Roadster, which is designed to accelerate at incredibly rapid speeds. The Roadster will be insanely quick on a straight line with its 0-60 mph time of 1.9 seconds, and based on Musk’s previous statements about the vehicle, the all-electric supercar will be able to take on track driving as well. This means that the next-generation Roadster will be a monster of a supercar, and it will require serious refinement in terms of its battery and electric motors to maintain its optimum performance.
Tesla is a far more experienced carmaker today than it was when Elon Musk unveiled the next-generation Roadster in 2017. Considering that Tesla is a company with a culture of innovation, it is almost certain that the new Roadster, once it is released, will be a far more refined vehicle than the already-game-changing supercar that shocked the auto industry nearly two years ago. Elon Musk, if any, has mentioned some of these updates, one of which is a SpaceX package that will utilize cold gas thrusters (the same technology used in SpaceX’s Falcon 9 rockets) to help the vehicle’s acceleration, braking, and maneuverability.
The impending arrival of the next-generation Roadster appears to have started a disruption in the hypercar market. Since the vehicle’s unveiling, other carmakers have introduced all-electric monsters of their own. Among these is the ~$2.5 million, 1,900 hp Pininfarina Battista, the ~$2 million, 1,973 hp Lotus Evija, and the $2.1 million, 1,914 hp Rimac C_Two. Considering that the Roadster will start at around $200,000, the vehicle will likely be closer in price to upcoming premium sports EVs like the Taycan Turbo S, which is expected to command a notably higher price compared to the ~$130,000 Taycan Turbo.
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
