Walter Isaacson’s Elon Musk biography is set to be published on Tuesday, and a new preview of the book illustrates details about Tesla’s development of the upcoming Full Self-Driving (FSD) version 12.
In an additional preview of his Musk biography for CNBC, Isaacson discusses the use of AI in the development of Tesla’s FSD v12, in a shift that took place within the last several months. Isaacson talks about Tesla’s recent development of the upcoming FSD v12, which he and Tesla demonstrate has moved away from a “rules-based” approach.
Notably, FSD v12 is expected to use billions of video frames from real-world driving incidents to train its neural network rather than using thousands of lines of code like previous versions. In a conversation with Musk last December, Tesla Autopilot employee Dhaval Shroff had likened the concept to the popular chatbot ChatGPT, instead for use with driving.
“It’s like ChatGPT, but for cars,” Shroff said. “We process an enormous amount of data on how real human drivers acted in a complex driving situation, and then we train a computer’s neural network to mimic that.”
Surprisingly enough, Tesla only shifted toward this “neural network planner” approach recently. By the beginning of this year, however, the neural network had already analyzed 10 million video clips based on the best-case-scenario drivers the system had access to. Musk instructed employees at the company’s Buffalo, New York facility who were in charge of analyzing the footage to train the AI on things “a five-star Uber driver would do.”
Moving from a rules-based to a network-path-based AI approach allowed FSD to use human driving data to avoid obstacles, even if breaking some rules was necessary. Shroff helped demonstrate the idea to Musk with a demo featuring trash bins, debris, and upturned traffic cones, which the car handled surprisingly well.
“Here’s what happens when we move from rules-based to network-path-based,” Shroff explained. “The car will never get into a collision if you turn this thing on, even in unstructured environments.”
Musk quickly took to the idea, as can be seen in a recent livestream of Tesla’s FSD v12 software in Palo Alto with Autopilot software director Ashok Elluswamy. He has repeatedly spoken about the upcoming software version’s impressive driving results, despite one small moment in the drive where the car almost ran a red light.
In any case, Musk could argue that the red-light moment is a good case for the need for self-driving software to continually learn. Given that it will constantly be trained from the video data generated by camera footage from real-world drivers, it should theoretically make it safer over time, according to Musk.
During development, Musk also reportedly latched onto the fact that it took over a million video clips for the neural network to begin performing well, though he looks forward to what significantly more data will do for FSD.
Still, critics and regulators have expressed concerns about the faults of human drivers training AI-based driving systems, and Tesla has repeatedly been questioned by the National Highway Traffic Safety Administration (NHTSA) about its Autopilot and FSD beta systems.
According to Isaacson, Tesla plans to release FSD v12 as soon as regulators approve it. Meanwhile, an ongoing study by the National Highway Safety Board is looking to determine if self-driving cars should be permitted to imitate human driving actions that blur traffic rules, such as creeping up at stop signs.
Musk said in April that he expects Tesla to reach full autonomy within a year, though he has also been known to share ambitious targets for the software in the past.
You can read Walter Isaacson’s full account of the development of Tesla FSD v12 here, in a CNBC preview of the upcoming Elon Musk biography.
What are your thoughts? Let me know at zach@teslarati.com, find me on X at @zacharyvisconti, or send your tips to us at tips@teslarati.com.
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Tesla workers push back against Giga Berlin unionization
“IG Metall did not succeed in Giga Berlin‘s works council election earlier today. The union share was reduced from nearly 40% in 2024 to 31% in 2026! This is a clear message by the Giga Berlin team towards an independent co-determination! The list called Giga United, led by the current chairwoman, Michaela Schmitz, received the most votes with more than 40%! Good news for Giga Berlin!”
Tesla workers pushed back against unionization efforts at Gigafactory Berlin, and over the past few years, there has been a dramatic decrease in interest to unionize at the German plant.
Gigafactory Berlin Plant Manager André Thierig announced on Wednesday that IG Metall, the European union group, saw its share reduce from 40 to 31 percent in 2026 as employees eligible to vote on the issue. Instead, the Giga Berlin team, known as Giga United, received the most votes with more than 40 percent.
BREAKING! 🚨
IG Metall did not succeed in Giga Berlin‘s works council election earlier today. The union share was reduced from nearly 40% in 2024 to 31% in 2026!
This is a clear message by theGiga Berlin team towards an independent co-determination!
The list called Giga…
— André Thierig (@AndrThie) March 4, 2026
Thierig gave specific details in a post on X:
“IG Metall did not succeed in Giga Berlin‘s works council election earlier today. The union share was reduced from nearly 40% in 2024 to 31% in 2026! This is a clear message by the Giga Berlin team towards an independent co-determination! The list called Giga United, led by the current chairwoman, Michaela Schmitz, received the most votes with more than 40%! Good news for Giga Berlin!”
There were over 10,700 total employees who were eligible to vote, with 87 percent of them turning out to cast what they wanted. There were three key outcomes: Giga United, IG Metall, and other notable groups, with the most popular being the Polish Initiative.
The 37-seat council remains dominated by non-unionized representatives, preserving Giga Berlin as Germany’s only major auto plant without a collective bargaining agreement.
Thierig and Tesla framed the outcome as employee support for an “independent, flexible, and unbureaucratic” future, enabling acceleration on projects like potential expansions or new models. IG Metall expressed disappointment, accusing management of intimidation tactics and an “unfair” campaign.
The first election of this nature happened back in 2022. In 2024, IG Metall emerged as the largest single faction with 39.4 percent, but non-union lists coalesced for a majority.
But this year was different. There was some extra tension at Giga Berlin this year, as just two weeks ago, an IG Metall rep was accused by Tesla of secretly recording a council meeting. The group countersued for defamation.
Tesla Giga Berlin plant manager faces defamation probe after IG Metall union complaint
This result from the 2026 vote reinforced Tesla’s model of direct employee-management alignment over traditional German union structures, amid ongoing debates about working conditions. IG Metall views it as a setback but continues advocacy. Tesla sees it as validation of its approach in a competitive EV market.
This outcome may influence future labor dynamics at Giga Berlin, including any revival of expansion plans or product lines, which Musk has talked about recently.
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SpaceX President Gwynne Shotwell details xAI power pledge at White House event
The commitment was announced during an event with United States President Donald Trump.
SpaceX President Gwynne Shotwell stated that xAI will develop 1.2 gigawatts of power at its Memphis-area AI supercomputer site as part of the White House’s new “Ratepayer Protection Pledge.”
The commitment was announced during an event with United States President Donald Trump.
During the White House event, Shotwell stated that xAI’s AI data center near Memphis would include a major energy installation designed to support the facility’s power needs.
“As you know, xAI builds huge supercomputers and data centers and we build them fast. Currently, we’re building one on the Tennessee-Mississippi state line. As part of today’s commitment, we will take extensive additional steps to continue to reduce the costs of electricity for our neighbors…
“xAI will therefore commit to develop 1.2 GW of power as our supercomputer’s primary power source. That will be for every additional data center as well. We will expand what is already the largest global Megapack power installation in the world,” Shotwell said.
She added that the system would provide significant backup power capacity.
“The installation will provide enough backup power to power the city of Memphis, and more than sufficient energy to power the town of Southaven, Mississippi where the data center resides. We will build new substations and invest in electrical infrastructure to provide stability to the area’s grid.”
Shotwell also noted that xAI will be supporting the area’s water supply as well.
“We haven’t talked about it yet, but this is actually quite important. We will build state-of-the-art water recycling plants that will protect approximately 4.7 billion gallons of water from the Memphis aquifer each year. And we will employ thousands of American workers from around the city of Memphis on both sides of the TN-MS border,” she noted.
The Ratepayer Protection Pledge was introduced as part of the federal government’s effort to address concerns about rising electricity costs tied to large AI data centers, as noted in an Insider report. Under the agreement, companies developing major AI infrastructure projects committed to covering their own power generation needs and avoiding additional costs for local ratepayers.
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Tesla Full Self-Driving v14.2.2.5 might be the most confusing release ever
With each Full Self-Driving release, I am realistic. I know some things are going to get better, and I know some things will regress slightly. However, these instances of improvements are relatively mild, as are the regressions. Yet, this version has shown me that it contains extremes of both.
Tesla Full Self-Driving v14.2.2.5 hit my car back on Valentine’s Day, February 14, and since I’ve had it, it has become, in my opinion, the most confusing release I’ve ever had.
With each Full Self-Driving release, I am realistic. I know some things are going to get better, and I know some things will regress slightly. However, these instances of improvements are relatively mild, as are the regressions. Yet, this version has shown me that it contains extremes of both.
It has been about three weeks of driving on v14.2.2.5; I’ve used it for nearly every mile traveled since it hit my car. I’ve taken short trips of 10 minutes or less, I’ve taken medium trips of an hour or less, and I’ve taken longer trips that are over 100 miles per leg and are over two hours of driving time one way.
These are my thoughts on it thus far:
Speed Profiles Are a Mixed Bag
Speed Profiles are something Tesla seems to tinker with quite frequently, and each version tends to show a drastic difference in how each one behaves compared to the previous version.
I do a vast majority of my FSD travel using Standard and Hurry modes, although in bad weather, I will scale it back to Chill, and when it’s a congested city on a weekend or during rush hour, I’ll throw it into Mad Max so it takes what it needs.
Early on, Speed Profiles really felt great. This is one of those really subjective parts of the FSD where someone might think one mode travels too quickly, whereas another person might see the identical performance as too slow or just right.
To me, I would like to see more consistency from release to release on them, but overall, things are pretty good. There are no real complaints on my end, as I had with previous releases.
In a past release, Mad Max traveled under the speed limit quite frequently, and I only had that experience because Hurry was acting the same way. I’ve had no instances of that with v14.2.2.5.
Strange Turn Signal Behavior
This is the first Full Self-Driving version where I’ve had so many weird things happen with the turn signals.
Two things come to mind: Using a turn signal on a sharp turn, and ignoring the navigation while putting the wrong turn signal on. I’ve encountered both things on v14.2.2.5.
On my way to the Supercharger, I take a road that has one semi-sharp right-hand turn with a driveway entrance right at the beginning of the turn.
Only recently, with the introduction of v14.2.2.5, have I had FSD put on the right turn signal when going around this turn. It’s obviously a minor issue, but it still happens, and it’s not standard practice:
How can we get Full Self-Driving to stop these turn signals?
There’s no need to use one here; the straight path is a driveway, not a public road. The right turn signal here is unnecessary pic.twitter.com/7uLDHnqCfv
— TESLARATI (@Teslarati) February 28, 2026
When sharing this on X, I had Tesla fans (the ones who refuse to acknowledge that the company can make mistakes) tell me that it’s a “valid” behavior that would be taught to anyone who has been “professionally trained” to drive.
Apparently, if you complain about this turn signal, you are also claiming you know more than Tesla engineers…okay.
Nobody in their right mind has ever gone around a sharp turn when driving their car and put on a signal when continuing on the same road. You would put a left turn signal on to indicate you were turning into that driveway if that’s what your intention was.
Like I said, it’s a totally minor issue. However, it’s not really needed, and nor is it normal. If I were in the car with someone who was taking a simple turn on a road they were traveling, and they signaled because the turn was sharp, I’d be scratching my head.
I’ve also had three separate instances of the car completely ignoring the navigation and putting on a signal that is opposite to what the routing says. Really quite strange.
Parking Performance is Still Underwhelming
Parking has been a complaint of mine with FSD for a long time, so much so that it is pretty rare that I allow the vehicle to park itself. More often than not, it is because I want to pick a spot that is relatively isolated.
However, in the times I allow it to pull into a spot, it still does some pretty head-scratching things.
Recently, it tried to back into a spot that was ~60% covered in plowed snow. The snow was piled about six feet high in a Target parking lot.
A few days later, it tried backing into a spot where someone failed the universal litmus test of returning their shopping cart. Both choices were baffling and required me to manually move the car to a different portion of the lot.
I used Autopark on both occasions, and it did a great job of getting into the spot. I notice that the parking performance when I manually choose the spot is much better than when the car does the entire parking process, meaning choosing the spot and parking in it.
It’s Doing Things (For Me) It’s Never Done Before
Two things that FSD has never done before, at least for me, are slow down in School Zones and avoid deer. The first is something I usually take over manually, and the second I surprisingly have not had to deal with yet.
I had my Tesla slow down at a school zone yesterday for the first time, traveling at 20 MPH and not 15 MPH as the sign suggested, but at the speed of other cars in the School Zone. This was impressive and the first time I experienced it.
I would like to see this more consistently, and I think School Zones should be one of those areas where, no matter what, FSD will only travel the speed limit.
Last night, FSD v14.2.2.5 recognized a deer in a roadside field and slowed down for it:
🚨 Cruising home on a rainy, foggy evening and my Tesla on Full Self-Driving begins to slow down suddenly
FSD just wanted Mr. Deer to make it home to his deer family ❤️ pic.twitter.com/cAeqVDgXo5
— TESLARATI (@Teslarati) March 4, 2026
Navigation Still SUCKS
Navigation will be a complaint until Tesla proves it can fix it. For now, it’s just terrible.
It still has not figured out how to leave my neighborhood. I give it the opportunity to prove me wrong each time I leave my house, and it just can’t do it.
It always tries to go out of the primary entrance/exit of the neighborhood when the route needs to take me left, even though that exit is a right turn only. I always leave a voice prompt for Tesla about it.
It still picks incredibly baffling routes for simple navigation. It’s the one thing I still really want Tesla to fix.