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Tesla FSD improvements in China continues with Baidu’s help

Tesla is working with Baidu to improve FSD in China, as strict data laws prevent Tesla from training its AI locally.

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Credit: Tesla China/Weibo

Baidu is helping Tesla Full Self-Driving (FSD) improve in China.

Engineers from Baidu, a leading AI company in China, are helping Tesla with its FSD Version 13 software.

According to Reuters’ sources, Baidu recently dispatched engineers from its mapping team to Tesla’s Beijing office. The engineers are working on integrating Baidu’s navigation map information with Tesla’s FSD V13 software.

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Tesla’s way of improving FSD V13 in China differs from the methods used in the United States. In the U.S., Tesla trains FSD to improve navigation techniques and learn about roads. In contrast, Tesla cannot train FSD in China due to the country’s data laws.

“Then China, which is a gigantic market, we do have some challenges because they currently don’t allow us to transfer training videos outside of China. And then the US government won’t let us do training in China. So, we’re in a bit of a there. It’s like a quandary,” noted Elon Musk during the last earnings call.

“So, we were solving then is by literally looking at videos of streets in China that are available on the Internet to understand and then feeding that into our training so that publicly available video of street signs and traffic rules in China can be used for training and then also putting it in a very accurate simulator. And so, it will train using SIM for bus lanes in China,” he added.

Tesla has rolled out FSD (Supervised) in Mexico and started the process to release it in parts of Europe. Despite a few regulatory issues, Musk is optimistic that FSD (Unsupervised) will be available in more countries this year.

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“But I think we’ll have unsupervised FSD in almost every market this year, limited simply by regulatory issues, not technical capability. And then unsupervised FSD in the U.S. this year, in many cities but nationwide next year. And hopefully, we have unsupervised FSD in most countries by the end of next year,” he noted during the Q4 and Full Year 2024 earnings call.

Maria--aka "M"-- is an experienced writer and book editor. She's written about several topics including health, tech, and politics. As a book editor, she's worked with authors who write Sci-Fi, Romance, and Dark Fantasy. M loves hearing from TESLARATI readers. If you have any tips or article ideas, contact her at maria@teslarati.com or via X, @Writer_01001101.

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Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much

There were two new lines of improvements in the release notes: one addressing Actually Smart Summon (ASS), and another that now allows drivers to choose a reason for an intervention via a small menu during disengagement.

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(Photo: Hector Perez/YouTube)

Tesla Full Self-Driving v14.3.2 began rolling out to some owners earlier this week, and there are some notable improvements that came with this update.

There were two new lines of improvements in the release notes: one addressing Actually Smart Summon (ASS), and another that now allows drivers to choose a reason for an intervention via a small menu during disengagement.

Overall operation saw a handful of slight improvements, especially with parking performance, which has been the most notable difference with the arrival of FSD v14.3. However, there are still some very notable shortcomings, most notably with region-specific signage and navigation.

Tesla Assisted Smart Summon (ASS) improvements

There are noticeable improvements to ASS operation, which has definitely been inconsistent in terms of performance. Tesla wrote in the release notes for v14.3.2:

“Unified the model between Actually Smart Summon, FSD, and Robotaxi for more capable and reliable behavior.”
As recently as this month, I used Summon with no success. It had pulled around the parking lot I was in incorrectly, leaving the range at which Summon can be operated and losing a signal while moving in the middle of the lot.

This caused me to sprint across the lot to retrieve the vehicle:

Unfortunately, Summon was not dependable or accurate enough to use regularly. It appears Tesla might have bridged the gap needed to make it an effective feature, as two tests in parking lots proved that Summon was more responsive and faster to navigate to the location chosen.

It also did so without hesitation, confidently, and at a comfortable speed. I was able to test it twice at different distances:

I plan to test this more thoroughly and regularly through the next few weeks, and I avoided using it in a congested parking lot initially because I have not had overwhelming success with Summon in the past. I wanted to set a low baseline for it to see if it could simply pull up to the place I pinned in the Tesla app.

It was two for two, which is a big improvement because I don’t think I ever had successful Summon attempts back-to-back. It just seems more confident than ever before.

New Disengagement Categories

This is a really good idea from Tesla, but there are some issues with it. The categories you can select are Critical, Comfort, Preference, and Other.

I think the reasons why people choose to take over would be a better way to prompt drivers, like, “Traveling Too Fast,” “Incorrect Maneuver,” “Navigation Error,” would be more beneficial.

I say this because it seems that how we each categorize things might be different. For example, I shared a video of an intervention because the car had navigated to an exit to a parking lot and put its left blinker on, despite left turns not being allowed there.

I disengaged and chose Critical as the reason; it’s not a comfort issue, it’s not a preference, it’s quite literally an illegal turn, and it’s also dangerous because it cuts across several lanes of traffic and is 180 degrees.

Some said I should not have labeled this as Critical, but that’s the description I best characterized the disengagement as.

Categorizing interventions is a good thing, but it’s kind of hard to determine how to label them correctly.

Inconsistency with Regional Traffic Patterns

Tesla Full Self-Driving is pretty inconsistent with how it handles regional or local traffic patterns and road rules. The most frequent example I like to use is that of the “Except Right Turn” stop sign, which has become a notorious sighting on our social media platforms.

In the initial rollout of v14.3, my Model Y successfully navigated through one of these stop signs with no issues. However, testing at two of these stop signs yesterday proved it is still not sure how to read signs and navigate through them properly.

Off camera, I approached another one of these signs and felt the car coming to a stop, so I nudged it forward with the accelerator pedal pressed.

This helped the car go through the sign without stopping, but I could feel the bucking of the vehicle as the car really wanted to stop.

Musk said on the earnings call earlier this week that unsupervised FSD would probably be available in some regions before others, including a state-to-state basis in the U.S.

“It’s difficult to release this like to everyone everywhere all at once because we do want to make sure that they’re not unique situations in a city that particularly complex intersection or — actually, they tend to be places where people get into accidents a lot because they’re just — perhaps there’s — and like I said, an unsafe intersection or bad road markings or a lot of weather challenges. So I think we would release unsupervised gradually to the customer fleet as we feel like a particular geography is confirmed to be safe.”
This could be one of those examples that Tesla just has to figure out.

Highway Operation

Full Self-Driving is already pretty good at routine roadway navigation, so I don’t have too much to report here.

However, I was happy with FSD’s decision-making at several points, including its choice not to pass a slightly slower car and remain in the right lane as we approached the off-ramp:

Better Maneuvering at Stop Signs

Many FSD users report some strange operations at stop signs, especially four-way intersections where there is a stop sign and a line on the road, and they’re not even with one another.

I experienced this quite frequently and found that FSD would actually double stop: once at the stop sign and again at the line.

This created some interesting scenarios for me and I had many cars honk at me when the second stop would happen. Other vehicles that had waved me on to proceed through the intersection would become frustrated at the second stop.

FSD seems to have worked through this particular maneuver:

FSD should know to go to the more appropriate location (whichever provides better visibility), and proceed when it is the car’s turn to move. The double stop really ruined the flow of traffic at times and generally caused some frustration from other drivers.

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Tesla plans to resolve its angriest bunch of owners: here’s how

Since the rollout of the AI4 chip in Tesla vehicles, owners with the last generation self-driving chip, known as Hardware 3, have been persistent in their quest for a solution to their issue: they were told their cars were capable of unsupervised Full Self-Driving. It turns out the cars are not.

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Credit: Tesla Asia/Twitter

Tesla has a plan to make Hardware 3 owners whole after CEO Elon Musk admitted that those with that self-driving chip in their cars will not have access to unsupervised Full Self-Driving.

The company’s strategy is so crazy that it is sort of hard to believe.

Since the rollout of the AI4 chip in Tesla vehicles, owners with the last generation self-driving chip, known as Hardware 3, have been persistent in their quest for a solution to their issue: they were told their cars were capable of unsupervised Full Self-Driving. It turns out the cars are not.

During the Tesla Q1 earnings call on Wednesday, Musk finally clarified what the company’s plans are for Hardware 3 owners, what they will be offered, and what Tesla will have to do internally to prepare for it.

The answer was somewhat mind-boggling.

Musk said:

“Unfortunately, Hardware 3 — I wish it were otherwise, but Hardware 3 simply does not have the capability to achieve unsupervised FSD. We did think at one point it would have that, but relative to Hardware 4, it has only 1/8 of the memory bandwidth of Hardware 4. And memory bandwidth is one of the key elements needed for unsupervised FSD.”
He continued, stating that HW3 owners would have the opportunity to trade their cars in at a discounted rate in order to get the AI4 chip:

“So for customers that have bought FSD, what we’re offering is essentially a trade-in — like a discounted trade-in for cars that have AI4 hardware, and we’ll also be offering the ability to upgrade the car, to replace the computer. And you also need to replace the cameras, unfortunately, to go to Hardware 4.”
Obviously, Tesla has a lot of people to work with and make this whole thing right. Musk was adamant that HW3 would be capable of FSD, and now that the company has finally admitted that it is not, there are some things that could come of this.

There has been open talk about some sort of class action lawsuit against Tesla. The promises that Tesla made previously could be considered a breach of contract or even false advertising, and that’s according to Grok, Musk’s own AI program.

Musk went on to say that Tesla would likely have to establish new microfactories to effectively and efficiently replace HW3 computers and cameras:

…So to do this efficiently, we’re going to have to set up, like kind of micro factories or small factories in major metropolitan areas in order to do it efficiently. Because if it’s done just at the service center, it is extremely slow to do so and inefficient. So we basically need like many production lines to make the change.”
This is going to be an extremely costly process, especially if Tesla has to buy real estate, properties, and equipment to complete this work. Additionally, there was no wording on pricing, but Musk never said it would be free. It will likely come with some kind of price tag, and HW3 owners, after being left hanging for so long, will have something to say about that.

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Tesla pulls back the curtain on Cybercab mass production

Tesla’s Cybercab drives itself off the Gigafactory Texas line in a striking new production video.

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Tesla Cybercab production units rolling off the factory line in Gigafactory Texas (Credit: Tesla)

Tesla has provided a first look from inside a production Cybercab as it drove itself off the assembly line at Gigafactory Texas. The video footage, posted on X, opens on the factory floor with robotic arms and assembly equipment visible through the Cybercab windshield, and follows the car through a branded tunnel marked “Cybercab”, before autonomously navigating itself to a holding lot.

The first Cybercab rolled off the Giga Texas production line on February 17, 2026, with Musk writing on X, “Congratulations to the Tesla team on making the first production Cybercab.” April marked the official shift to volume production. The Giga Texas line is being prepared to produce hundreds of units per week, with 60 units already spotted on the Gigafactory campus earlier this month.


The Cybercab was first revealed publicly at Tesla’s “We, Robot” event in October 2024 at Warner Bros. Studios in Burbank, California, where 20 pre-production units gave attendees rides around the studio lot. Musk said he believed the average operating cost would be around $0.20 per mile, and that buyers would be able to purchase one for under $30,000. The two-seat design is deliberate. Musk noted that 90 percent of miles driven involve one or two people, making a compact two-passenger vehicle the most efficient configuration for a fleet-scale robotaxi. Eliminating rear seats also removes complexity and cost, supporting that sub-$30,000 target.

Tesla’s annual production goal is 2 million Cybercabs per year once several factories reach full design capacity. The Cybercab has no steering wheel, no pedals, and relies entirely on Tesla’s vision-based FSD system. What the video shows is the first evidence of that system working not as a demo, but as a production reality, driving itself off the line and into the world.

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