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Tesla Model S Plaid races two of the world’s quickest sedans. The results were not close
There was a time when the Porsche Taycan Turbo S was considered extremely quick. Being one of the few cars that could beat the Tesla Model S P100D with Ludicrous Mode in the drag strip, the Taycan was the car that proved that veteran carmakers should not be ignored in the electric vehicle race. It’s a beautiful vehicle, it handles like a Porsche, and it’s devilishly fast.
But that was before the arrival of the Tesla Model S Plaid. With three electric motors and over 1,000 horsepower, the Model S Plaid was a completely different animal. And even with new competitors like the Lucid Air Dream Edition, which was recently tested to be capable of completing the quarter-mile 10.21 seconds at 143.37 mph, the Plaid seems like it exists in a league of its own.
And this, ultimately, was proven in a recently posted video from Brooks Weisblat of the DragTimes YouTube channel. After featuring the Lucid Air in three videos so far, the veteran drag racer opted to race the newcomer against both the Tesla Model S Plaid and the Porsche Taycan Turbo S. A triple-threat race is always fun, but when it involves three of the world’s quickest sedans, then things become very interesting.
The three vehicles are pretty different on paper. The Lucid Air Performance Dream Edition is listed with two electric motors that make 1,111 horsepower and a weight of 5,236 pounds. It also costs a hefty $170,000. The Taycan Turbo S is a Porsche through and through, with its two electric motors that make 750 horsepower, 2-speed transmission, and its weight of 5,300 pounds. It’s also the most expensive of the three at $218,000 for the specific trim featured in the video.
Compared to its two competitors, the Tesla Model S Plaid seems to be a completely different beast. It features three electric motors that make 1,020 horsepower and it weighs 4,833 pounds, making it the lightest of the three. This is quite interesting since the vehicle is a full-sized family sedan. It’s also the most affordable at just around $130,000 before options. Also interesting was that the Plaid had the lowest state of charge during the race with its 82% battery. The Lucid Air had 86% of its battery left, and the Taycan Turbo S had 90%.
The three vehicles engaged each other in three separate races: two standing drag races and one rolling race. And in each bout, the Tesla Model S Plaid completely dominated its competition. It’s pretty amazing to see in DragTimes‘ video, but the Plaid almost made the Lucid Air look moderately quick, and the Taycan Turbo S look like it was standing still. Based on these results, it would seem like the only vehicle that could soundly beat the Model S Plaid today for now is the Rimac Nevera, and that’s an all-electric hypercar worth millions of dollars. Among fellow performance sedans in its price range, it seems that the Tesla Model S Plaid is near-untouchable.
Watch the Tesla Model S Plaid battle with the Lucid Air and the Porsche Taycan in the video below.
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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.”
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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
