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Tesla Full Self-Driving changes your perception of travel — long or short
Tesla Full Self-Driving will ruin controlling your vehicle manually.
Tesla does not tell you what Full Self-Driving will do to your perception of travel. Whether your next trip is a two-minute ride up the street to the grocery store or a 1,500-mile trip across multiple states, you’ll never look at driving the same way.
This past weekend, I was lucky enough to have a new Tesla Model Y for the weekend. Equipped with the company’s Hardware 4 computer, the latest software version, and all of the new Model Y’s improvements from the legacy iteration, I knew much of my weekend would be spent testing FSD, as I have never had an extended experience with it.
By the time the weekend was over and it was time to pick up my non-Tesla car, I realized I was not ready to let go. Having the car drive me around from location to location all weekend was something I truly enjoyed, but it was more than just a convenience thing. I felt impressed, relaxed, and even, in some instances, safer.
🚨 The final leg of our trip here: FSD did a great job of navigating through this parking lot and getting us onto a highway with a very short on-ramp (a very typical part of living and driving in Pennsylvania).
Also, Autopark did a great job! I would like to see it improve by… pic.twitter.com/OBefKZKDCo
— TESLARATI (@Teslarati) May 5, 2025
What Tesla Full Self-Driving Did Well
Now, before I truly begin, I do want to say that I don’t think I’ll ever feel safer than when I’m in ultimate control of the vehicle. However, a lot of things that give me stress during a drive were handled with relative ease by the car — and I was happy I didn’t have to deal with it.
One instance was merging onto a busy highway with a very short merge lane. Full Self-Driving took a no-holds-barred approach, taking the space it was given and grabbing a spot in the right lane quickly.
It was not willing to be passive, but it was also not willing to sacrifice safety. It will not wait for others to pull the trigger and go at intersections or four-way stops. If there are a few seconds of stagnation from the car and another driver in that instance, it will go, of course, proceeding safely.
It even did a handful of things I didn’t expect it to do. It would stay in the right lane if multiple on-ramps were approaching. I took it on a stretch of highway where three on-ramps are all within a mile of one another.
It passed a tractor-trailer just before we made it to the first of those three on-ramps. It stayed in that left lane after overtaking the 18-wheeler, as Driver Visualization showed more cars approaching to merge. It was one of those moments that, even though I have written about this topic for several years, was unbelievably impressive.
It not only drives people safely, but it is also considerate of other drivers, which is very impressive.
I was incredibly surprised to see my Fiancè have so much ease when it was operating.
🚨 Tesla Full Self-Driving takes my Fiancé and I to Target
Flawless drive! We’ll document the rest of our errands today! pic.twitter.com/TAx3mWmVgh
— TESLARATI (@Teslarati) May 4, 2025
I figured, just because she is not as familiar with what Tesla does to make FSD better and how it works, that she would be very on edge during our rides. This was the opposite. She felt comfortable enough to look away from the road while in the passenger seat. Scrolling her phone or looking out at the blooming flowers was what she did in the car. It was no different from when I’m driving, and I think that was what was most impressive to me.
Driving after FSD
I found that picking up my car and driving manually back home truly brought me back to real life. Everyone with a Tesla and Full Self-Driving says that when you go back to another car, you feel like you’re stuck in the past.
I really did feel that way. Not only because of the aesthetic of the interior, but just because I was doing something that I just realized could be done for me with the right vehicle.
🚨 100% the truth!
Once you go FSD, you never go back! https://t.co/uq7qkgAbtA pic.twitter.com/lUN3rT2Kkl
— TESLARATI (@Teslarati) May 8, 2025
While I love the car I own now, I’m still deciding whether I love it enough to keep it. To be completely honest, I have hopped around with the idea of trading in my car for the new Model Y. Whether I will or not truly depends on the next few weeks and how I feel, but I know that I will be considering it for the next few months easily.
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.