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Porsche explains Mission E Cross Turismo design and concept

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Porsche recently published a video discussing its long-range, all-electric vehicle — the Mission E Cross Turismo — discussing the vehicle’s concept and design. Unveiled last month at the Geneva Motor Show, the Mission E Cross Turismo is expected to enter the market early in the next decade.

According to Porsche’s most recent video, the Mission E variant is the product of the company’s attempt to make an electric car that fits in perfectly with the rest of the company’s lineup. Michael Mauer, Porsche’s Vice President of Style, highlighted the Cross Turismo’s unique features. The design executive, for one, took particular notice of the car’s aerodynamics and airflow, which is enhanced by the vehicle’s shape and vents on its sides. Its pop-up door handles, which are similar to the Tesla Model S, also improve its aerodynamics.

As noted in a Motor1 report, the German legacy automaker appears to have adopted a “less is more” approach to the interior of the electric car, though not as radical as the Tesla Model 3. As could be seen in images of the Cross Turismo’s interior, the dashboard is fitted with a generous binnacle in front of the steering wheel and an expansive touchscreen on the passenger side. This is quite a departure from Porsche’s tendency to place a generous number of knobs and switches in some of its other vehicles.

The seats of the Mission E Cross Turismo are also noteworthy, with their rather thin design. This appears to be aimed at maximizing the interior space of the vehicle, as could be seen in the liberal amount of legroom in the second row.

Just last month, Porsche took one of its Mission E sedan prototypes to one of Germany’s most challenging and most iconic tracks — the Nurburgring. Based on a brief clip of the vehicle as it passed through the exit of Brunnchen, Porsche definitely seems to be refining the all-electric car’s performance. As noted by Porsche VP of Product Line BEV Stefan Weckbach, the Mission E would be a car that can perform at its optimum for extended periods of time, unlike Tesla’s Model S, which gets its performance limited when driven hard on the track.

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Despite Tesla’s lack of involvement in motorsports so far, signs are starting to emerge that the Elon Musk-led company is refining its vehicles’ capabilities. In a previous report, we covered how a long-range RWD Tesla Model 3 was able to complete several laps in the Laguna Seca Raceway without a drop in performance. During the Model 3’s track session, it was able to go flat out for four laps before its brake pads were worn down. Despite this, however, the electric car’s driver was still able to complete several more laps around the racetrack using the car’s regenerative braking.

Watch Porsche’s video on the Mission E Cross Turismo in the video below.

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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Tesla AI Head says future FSD feature has already partially shipped

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Credit: Tesla

Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.

Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.

Back in October on the Q3 Earnings Call, Musk said:

“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”

Musk said in the same month:

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“By v14.3, your car will feel like it is sentient.”

Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.

On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.

He added that “more and more reasoning will ship in Q1.”

Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.

Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad

As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).

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Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.

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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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