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Tesla Model 3 driven by the father of Track Mode breaks Plaid Model S’ lap record

(Credit: Ben Schaffer/Unplugged Performance)

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Last year, Tesla shocked the electric vehicle world when it revealed that it had a Plaid Model S prototype that could be taken and pushed to its limits at the track. The vehicle, which was driven by a member of the Tesla development team, absolutely crushed the previous records set by four-door sedans at Laguna Seca, completing the tricky course in just 1:36.555. 

This record, set by the formidable Plaid Model S, has now been broken. Surprisingly enough, the record was actually beaten by an upgraded version of its little brother, the Model 3 Performance. The Model 3 Performance definitely lacked the raw power of the tri-motor Model S, but it sure made up for it with clever mods and a master driver behind the wheel. The Model 3’s driver was Randy Pobst, a professional racer driver and, in a way, the father of Track Mode. 

Back in October 2018, the Tesla Model 3’s development version of Track Mode was driven by Pobst against the Jaguar I-PACE EV400 and one of the best ICE cars available then, the Alfa Romeo Giulia Quadrifoglio. The development version of Track Mode performed well, and it toppled the I-PACE EV400 easily enough. It was, however, not enough to beat the Alfa Q4. Tesla then spent the next weeks working with Pobst to refine Track Mode’s setting and features, which were later rolled out as the release version of the special setting. With Track Mode’s release version, the Model 3 Performance was able to crush the Alfa Romeo Q4’s time easily. 

Perhaps it is this experience and his intimate knowledge of the Model 3 Performance’s capabilities that allowed Randy Pobst to push the all-electric sedan to its absolute limits. Or perhaps it is the vehicle’s modifications from EV tuning house Unplugged Performance, which equipped the vehicle with both consumer and prototype parts from its Ascension-R package. Either way, the Model 3, driven by the driver who tuned its BMW M3-killing feature, completed a lap around the Laguna Seca raceway in 1:35.790. 

What is even more interesting is that the Model 3 Performance was not specifically tuned for Laguna Seca. The vehicle is actually being prepared for the Pikes Peak Hill Climb, so its runs at Laguna Seca were simply a way to test the vehicle’s capabilities. The Model 3 even had a weight penalty during its record-breaking run, since it was equipped with a 160-lb roll cage that was mandatory for Pikes Peak. Even Pobst himself only flew in from the East Coast for 24 hours to test the vehicle. 

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In a statement to Teslarati, Unplugged Performance CEO Ben Schaffer expressed his excitement at the results of the Model 3 Performance’s Plaid-breaking lap. “Our expectations at Laguna Seca were simply to validate the car with Randy and to make sure we are safely dialed in for Pikes Peak. It definitely shocked us all when we beat the lap time of the mighty Plaid Model S prototype in our Model 3. The crazy thing is that we still have a lot of additional modifications being prepared and we’ve not come near the car’s full potential with our upgrades yet!” he said. 

(Credit: The Kilowatts/Twitter)

Now, one has to imagine just how fast the Plaid Model S could go around Laguna Seca with a professional driver like Randy Pobst behind its wheel. That run would likely be one for the books. 

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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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.” 

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Credit: @BLKMDL3/X

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. 

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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.

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Credit: Tesla China

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.

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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.

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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.

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Gage Skidmore, CC BY-SA 4.0 , via Wikimedia Commons

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.

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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.

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