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Tesla patents virtualization and machine learning software to improve FSD

Credit: Drive in EV/Twitter

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Tesla has applied for a set of patents that are set to significantly improve virtualization, recognition, and Full Self Driving overall.

Tesla has worked tirelessly to improve full self-driving technology in the first two months of the year. Most recently, Tesla pushed its most significant improvement to employees, v11.3. Still, with new patented technology, the software is set to continue to improve dramatically this year. The two patents, focusing on virtualization and machine learning, appeared in the U.S. Patent Office database late last week.

The first patent, “Vision-Based Machine Learning Model for Autonomous Driving with Adjustable Virtual Camera,” is likely simply a reworking of a previous system but changed to fit Tesla’s new visual-only autonomous driving system. The second patent, “Vision-Based Machine Learning Model for Aggregation of Static Objects and Systems for Autonomous Driving,” focuses more on improving the virtualization seen on screen while in the vehicle.

The first patent’s abstract describes a system that looks similar to the one already available in Tesla vehicles but has been adapted to remove non-visual sensors. However, it does include an added “adjustable virtual camera,” potentially indicating that Tesla is working to give drivers more control of looking out of their car with the camera system or improved virtualization interaction.

“Systems and methods for a vision-based machine learning model for autonomous driving with adjustable virtual camera. An example method includes obtaining images from a multitude of image sensors positioned about a vehicle. Features associated with the images are determined, with the features being output based on a forward pass through a first portion of a machine learning model. The features are projected into a vector space associated with a virtual camera at a particular height. The projected features are aggregated with other projected features associated with prior images.”

The second, significantly more extensive patent is described in its abstract, focusing on the “aggregation of static objects” by the vehicle:

“Systems and methods for a vision-based machine learning model for aggregation of static objects and systems for autonomous driving. An example method includes obtaining images from image sensors positioned about a vehicle. Features associated with the images are determined, with the features being output based on a forward pass through a machine learning model. The features are projected into a vector space associated with a birds-eye view based on the machine learning model.”

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If anything, the new patents from Tesla show just how dedicated it is to its visual-only system. Nowhere in either of the patents does the automaker address other sensor inputs, which seems to line up with recent discoveries showing upcoming vehicles without ultrasonic sensors.

Further, with Tesla’s increasing focus on making vehicles more AI capable, implementing improved machine learning also matches its design goals.

It remains unclear whether these improvements have been implemented in upcoming software versions or have already been placed in cars via recent software updates. Still, they nonetheless indicate that the company is making continuous progress in its pursuit.

As more and more automakers enter the autonomous driving competition, Tesla’s lead becomes ever more apparent. And while many have mocked the company for its dedication to AI over just vehicles, that investment is proving to be a fantastic one. Hopefully, it will result in an increasingly better Tesla driving experience in the coming years.

What do you think of the article? Do you have any comments, questions, or concerns? Shoot me an email at william@teslarati.com. You can also reach me on Twitter @WilliamWritin. If you have news tips, email us at tips@teslarati.com!

Will is an auto enthusiast, a gear head, and an EV enthusiast above all. From racing, to industry data, to the most advanced EV tech on earth, he now covers it at Teslarati.

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Tesla Full Self-Driving v14.3.6 review: a rare regression, but some bright spots

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Credit: Tesla

Tesla released Full Self-Driving version 14.3.6 last week, and after what was potentially one of the best FSD releases in v14.3.5, there has been a bit of a regression. While there are some bright spots, the changes made to v14.3.6 seem to have backtracked some behaviors.

Overall, it is hard to really complain about FSD in any sense; it has revolutionized how I travel literally anywhere. According to my self-driving app, the last time I went a day without using it was 59 days ago.

However, I think it’s also important to recognize when things are just plain bad with FSD. There are times it does truly mind-boggling things, and I’ll dive into those here. Additionally, I only had these issues on local roads, not on highways. Highway operation, generally, is always incredible other than the occasional complaint about speed or left lane camping.

With those things being said, my personal experience may not represent others’ experiences. A handful of people have said they have had a similar experience on v14.3.6, while others have said it is more than normal.

Turning Hesitancy, Inaccuracy

I’ve noticed more inaccuracy turning into multi-lane stretches of road than in any version I can remember. I’ve had at least three instances of FSD turning into a stretch of roadway that has two or more lanes, and not selecting a lane confidently as it has in past versions.

Instead, the car will drive over one of the dashed road lines, and the steering wheel will jerk back and forth before picking the lane. It should be said that it has always picked the correct lane when choosing based on the navigation, but it is still very indecisive. The steering wheel jerking is reminiscent of some of the later versions of v13.

I admit I really hate to see the steering wheel jerking come back. However, I think when Tesla releases v14.3.7, it won’t be present. When there are occurrences of it in FSD versions, it is usually resolved by the following release.

FSD Disregards Manual Turn Signals

This is my biggest bone to pick with FSD other than Navigation issues, but this one seems like it would be such an easy fix.

If Tesla is going to put the word “Supervised” on the end of “Full Self-Driving,” then when I tell the car to do something, it should do it. If I input an increase in speed by pressing the accelerator, the car will immediately respond. It does not disregard my input because it feels it is traveling at the right speed.

FSD should never disobey and turn off turn signals that the driver inputs. Trying to direct the car into the correct lane, I had initiated the left turn signal not once, not twice, but three times, with the car turning it off all three times and continuing in a lane that would end in just one block. The only solution at this point would be to zipper merge.

This goes back to the fact that self-driving’s biggest bottleneck might be rider preference. A zipper merge might have been more than reasonable, might have saved me time that I spent sitting through an additional light cycle, and might be something many drivers would do. I was in no hurry, I traditionally do not try to zipper merge because it feels inconsiderate, and lastly, the car should have just followed my input.

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This caused me to disengage and drive manually the rest of the way home. Sometimes I just do not need FSD to try to pass every car it can at intersections.

Bird Braking is a Thing of the Past

The big complaint with recent versions of Full Self-Driving has been what we’ve coined as “bird braking,” which is when the car will brake suddenly as a bird flies past.

There have been zero issues with this so far in v14.3.6, which is an excellent improvement.

FSD Might Already Be Taking Note of Driver Preferences

Another thing I have noticed over the past few days is that v14.3.6 seems to already be taking my preferences with navigation into account.

This is something that is supposed to be rolling out with the Summer Update, but I have a hunch it’s already present and might have been included in this v14.3.6 build. On Friday, FSD pulled into an entrance to a local convenience store that it had never attempted to go into before.

Typically, I manually pull into this entrance because it avoids heavy cross traffic at the main entrance. FSD has always chosen that congested main entrance.

Additionally, FSD has pulled into my assigned parking spot at my townhouse community on multiple occasions with this release. This is something that used to happen ocassionally, but not consistently.

It also navigated back to the same convenience store last night, drove through crazy cars scrambling to gas pumps, navigated out of the parking lot correctly, drove me home, and, once again, parked in my assigned spot.

As previously stated, this release just seems to have a few things that need to be brought to Tesla’s attention, and also to make others who use FSD aware of some things that I’ve experienced. I look forward to the next release that will remedy these issues, just as Tesla has always done in the past.

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Musk’s massive Terafab project will get final location soon

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Credit: SpaceX

Elon Musk’s massive Terafab project, which will be the first true conglomeration between each of his major entities, is set to get its final location soon, the CEO said on Tesla’s recent earnings call.

“The Terafab, we expect to announce a location soon, and provide more details about our plans in that regard. We’ll leave that to the product, the launch announcement rather than try to squeeze it into an earnings call,” Musk said last Wednesday.

Tesla Terafab set for launch: Inside the $20B AI chip factory that will reshape the auto industry

Terafab was announced by Musk back in March and was essentially a massive, vertically integrated semiconductor manufacturing project that would provide all the chips the three companies needed for their AI initiatives without needing third-party companies.

The plant will produce over 1 terawatt of AI compute each year, and will help back up projects like Optimus, Full Self-Driving, and other AI-based projects that Musk’s companies are working on.

In April, less than a month after the project was launched, Intel announced it would join the project, contributing manufacturing expertise and consulting to Terafab as a whole. Intel is one of three chip manufacturers that produce sub-5 nanometer chips at scale. TSMC and Samsung are the other two.

However, there was no true indication of where Terafab would end up, but most believe it will likely be somewhere in Texas. Business Insider has reported that SpaceX plans to build out Terafab in Grimes County, Texas, but this is unconfirmed.

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Musk confirmed recently that it would not be on Giga Texas property, as it is simply too large.

Terafab holds much of Musk’s grand ambitions for the future within its construct. It holds so much responsibility for the future and the biggest projects that Musk’s companies can imagine.

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“I think this is a very big announcement and it deserves to have its own day in the spotlight and not be squeezed into an earnings call,” he said. “I do think Terafab is going to be an amazing initiative and a necessary one, and one without which we will be constrained in our ability to scale Optimus production, because we simply won’t have enough AI chips.”

He continued by stating that Terafab is necessary for scaling Optimus, which Musk said could be the biggest product of any kind of all time. “It’s crucial to solve that, and we’ll have to solve memory, logic, and packaging in order to scale Optimus.”

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Elon Musk reveals SpaceX performed secret Starship test on Flight 13

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Credit: SpaceX

SpaceX performed a secret test on a specific portion of Starship with its recent 13th test flight last week, CEO Elon Musk revealed.

Starship’s 13th test flight took place last Friday, and in many aspects, it was one of the most overwhelmingly successful launches in the project’s history.

All of the mission objectives were met without incident, both the Super Heavy Booster and Ship managed to perform safe splashdowns in the Gulf of America and the Indian Ocean, respectively, and the deployment of Starlink satellites came and went without any complications.

However, there was more on the agenda for SpaceX with Flight 13. Musk revealed an internal test of the ship’s heat shield tiles, as the space exploration company wanted to push them to the limits after previous issues.

Many noticed that Starship’s initial launch seemed to be more accelerated than normal, and that was not a mistake. Musk revealed that SpaceX decided to give Flight 13 an intentionally aggressive acceleration rate in an effort to test how well the tiles would remain attached to the ship:

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SpaceX had issues with some of the heat shield tiles remaining attached early on in the Starship program. The first six test flights presented some kind of anomaly with them, so the company’s big focus with them was to figure out a way to keep them intact through the duration of the flight.

Things truly improved as Flight 10 showed that ceramic tiles generally stayed attached to the ship far better due to refined attachment, as SpaceX utilized pins instead of adhesives. Flights 10 through 13 truly showed some clear progress with the heat shield tiles, and this latest test seems to be where some real progress was noticed, especially by Musk.

The 13th Starship launch last Friday was the second with Starship V3, SpaceX’s latest and greatest iteration of the spacecraft. Goals and ambitions are getting even grander as the project continues to progress. Musk has already hinted that SpaceX will likely try to catch Starship with Flight 14.

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