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Tesla is patenting a clever way to train Autopilot with augmented camera images

Tesla Autopilot construction zone lane (Credit: YouTube/Cf Tesla)

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Tesla is currently tackling what could only be described as its biggest challenge to date. In his Master Plan, Part Deux, CEO Elon Musk envisioned a fleet of zero-emissions vehicles that are capable of driving on their own. Tesla has made steps towards this goal with improvements and refinements to its Autopilot and Full Self-Driving suites, but a lot of work remains to be done.

As noted by Tesla during its Autonomy Day presentation last year, attaining Full Self-Driving is largely a matter of training the neural networks used by the company. Tesla adopts what could be described as a somewhat organic approach for autonomy, with the company using a system that is centered on cameras and artificial intelligence — the equivalent of a human primarily using the eyes and brain to drive.

Tesla’s camera-centric approach may be quite controversial due to Elon Musk’s strong stance against LiDAR, but it is gaining ground, with other autonomous vehicle companies such as MobilEye developing FSD systems that rely primarily on visual data and a trained neural network. This approach does come with its challenges, as training neural networks requires tons of data. Tesla emphasized this point as much during its Autonomy Day presentation.

With this in mind, it is pertinent for the electric car maker to train its neural networks in a way that is as efficient as possible with zero compromises. To help accomplish this, Tesla seems to be looking into the utilization of augmented data, as described in a recently published patent titled “Systems and Methods for Training Machine Models with Augmented Data.”

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A block diagram of an environment for computer model training. (Credit: Patentscope.wipo.int)

Teslas are equipped with a suite of cameras that provide 360-degree visual coverage for the vehicle. In the patent’s description, Tesla noted that images used for neural network training are usually captured by various sensors, which, at times, have different characteristics. An example of this may lie in a Tesla’s three forward-facing cameras, each of which has a different field of view and range as the other two.

Tesla’s recent patent describes a system that allows the company to process these images in an optimized manner. Part of how this is done is through augmentation, which opens the doors to flexible and widespread neural network training, even when it involves vehicles equipped with differently-specced cameras. The electric car maker describes this process as such:

“Augmentation may provide generalization and greater robustness to the model prediction, particularly when images are clouded, occluded, or otherwise do not provide clear views of the detectable objects. These approaches may be particularly useful for object detection and in autonomous vehicles. This approach may also be beneficial for other situations in which the same camera configurations may be deployed to many devices. Since these devices may have a consistent set of sensors in a consistent orientation, the training data may be collected with a given configuration, a model may be trained with augmented data from the collected training data, and the trained model may be deployed to devices having the same configuration.”

Among the most notable aspects of Tesla’s recent patent is the use of “cutouts,” which allow Tesla’s neural networks to be trained using an optimized set of images. This was something that was discussed by former Tesla Autopilot engineer Eshak Mir in a Third Row Podcast interview, where he hinted at a system adopted in the electric car maker’s ongoing Autopilot rewrite that helped lay out “all the camera images” from a vehicle “into one view.” Such a process has the potential to help Tesla with 3D labeling, especially since the images used for neural network training are stitched together. Tesla’s patent seems to reference a system that is very similar to that described by the former Autopilot engineer.

“As a further example, the images may be augmented with a“cutout” function that removes a portion of the original image. The removed portion of the image may then be replaced with other image content, such as a specified color, blur, noise, or from another image. The number, size, region, and replacement content for cutouts may be varied and may be based on the label of the image (e.g., the region of interest in the image, or a bounding box for an object).”

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Tesla is aiming to release a feature-complete version of its Full Self-Driving suite as soon as possible. Elon Musk remains optimistic about this, despite the company missing its initial timeline that was set at the end of 2019. That being said, Elon Musk did mention previously that Tesla is working on a foundational rewrite of Autopilot. In a tweet early last month, Musk stated that an essential part of the rewrite involves work on Autopilot’s core foundation code and 3D labeling. Once done, the CEO indicated that additional functionalities could be rolled out quickly. This recent patent, if any, seems to give a glimpse at how these improvements are being done.

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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Investor's Corner

Lucid denies rumors of bankruptcy after over 40% stock drop

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Credit: Lucid

Electric vehicle maker Lucid Group has denied rumors of an imminent bankruptcy after a report from this morning sent the stock on a dramatic drop on Wall Street, seeing losses of more than 40 percent during trading hours.

Lucid’s Director of Communications, Nick Twork, responded to the report from Eletric-Vehicles.com, which stated the company’s restructuring advisor, AlixPartners, was asked to review two decisions: taking Lucid shares private or filing for Chapter 11 bankruptcy protection.

The report also claims AlixPartners told the Lucid board to “concentrate on Gravity production while improving its quality, and to temporarily hold back the Lucid Air, the sedan that has defined the company since its launch.”

Twork said:

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Shares rebounded after the response to the report, halving its losses as the trading day neared 3 p.m. Eastern.

Lucid has struggled to get its sales off the ground and into more respectable numbers, but the company is in its early years, when things are hard to begin with. It is also backed by several notable investors, including the Saudi Public Investment Fund (PIF), which has nearly limitless money and likely would not ditch an investment of this size so soon.

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Lucid shares were down just 14 percent at the time of publication, a far cry from the 55 percent its losses topped out at during the day.

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Tesla owner attempts resale of Model S Signature Edition for over $260k

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Credit: Tesla

A Tesla owner who purchased a Model S Signature Edition, one of the final 250 units of the all-electric flagship vehicle that the company discontinued earlier this year, is attempting to sell the car despite a no-resale clause that prohibits reselling for the first year.

The car is being sold by J&S Autohaus in Ewing, New Jersey, and is priced at $260,490, well above the $159,420 that Tesla sold it for earlier this year.

To those who do not know, the Model S Signature was a highly exclusive, limited-run farewell variant of the Model S Plaid that was produced this year to mark the end of production of both the Model S and Model X, Tesla’s two flagship vehicles.

Limited to just 250 units with invite-only sales, it serves as a collector’s item celebrating the legacy of the Model S, which helped pioneer Tesla’s electric vehicle success since its 2012 launch.

It bundles top-tier performance with bespoke cosmetic and luxury upgrades, plus Tesla’s Luxe Package. Here’s what the Model S Signature has over the typical Model S Plaid:

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  • Exclusive Exterior – Unique Garnet Red Paint, matching door handles, gold Tesla “T” badges upfront, gold Plaid and Signature badging at the rear.
  • Premium Interior – White Alcantara upholstery with gold piping/accents, gold Plaid seat badges, Signature-marked door sills, individually numbered dashboard plaque, gold puddle lights, special interior lighting sequence, and a custom Signature key fob.
  • Performance Upgrades – Carbon-ceramic brakes with gold calipers
  • Bundled Luxe Package – Full Self-Driving (Supervised), four years of Premium Connectivity, free lifetime Supercharging
  • Performance Metrics – ~1,020 horsepower, sub-2-second 0-60 MPH, ~390-mile range

Tesla quickly introduced a No Resale Agreement for the Signature Editions of the Model S and Model X, which would penalize the seller for “the amount of $50,000 or the value received as consideration for the sale or transfer, whichever is greater.”

The company continues:

“If you sell or otherwise transfer the ownership of your Model S or Model X, the remainder of the Recommended Maintenance, Wheel and Tire Protection Plan, and Windshield Protection Plan will transfer automatically to the buyer. The Full Self-Driving (Supervised), Free Supercharging and Premium Connectivity will not transfer with the vehicle and will terminate once the ownership of the Model S or Model X is transferred.”

Tesla will likely come after the seller, especially as it has been about two months since Tesla launched deliveries.

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Tesla Full Self-Driving v14.3.5 Early Impressions: new features and early performance

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Credit: TESLARATI

Tesla rolled out Full Self-Driving (Supervised) v14.3.5 yesterday, and about fifty miles of driving on the new version has given me enough time to highlight what seems to be strong about the release and what is not.

Additionally, Tesla has added a few new features with this specific update, which we’ll highlight as well.

Tesla Full Self-Driving v14.3.5 Performance

The new update is business as usual. Things seem to be running completely normal and necessary, but there are a few things that we’ve seemed to pick up on based on our own experience with v14.3.5, as well as what other users are seeing.

Initially, it seems to be more aware of its surroundings, making moves that are incredibly courteous to other drives and operating just a tad more reserved than what the suite might have done previously.

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We had two instances where it showed this, the first being FSD needing to pass a Flagger Force vehicle that was placing down signage for the day. Their work truck was right at the front corner of a right-hand turn; typically where most cars travel when they take that turn.

FSD v14.3.5 recognized this, slowed down, and took the turn wide with no issues:

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Additionally, v14.3.5 backed up for a semi truck that was making a wide turn onto a road my car was on. This is not new, but it seemed to be backing up for courtesy; it didn’t seem completely necessary, but it might have put some peace of mind in the truck driver’s head:

X user Mike P, also a Pennsylvania native like myself, shared three clips of his Tesla running v14.3.5 performing similar maneuvers. He said:

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“FSD turns right into a small alley that only fits one car at a time, sees oncoming car, reverses out of alley to make space, realizes oncoming car is actually parking, re-enters alley.”

Check it out here:

It seems like Speed Profiles are still in need of some tweaking; I am adjusting what Speed Profile I’m in frequently, constantly changing it to get it to travel at the correct speed. This was an issue for me on v14.3.4. It seems like they’re just a little inconsistent.

Terrible Parking

Parking attempts on v14.3.5 were not good. There are quite a few people who have said this:

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David Moss, the Tesla owner who has taken multiple coast-to-coast drives without any interventions, also has had some issues with parking early on with v14.3.5:

New Features

Tesla has added the ability to open Camera Preview at any time. Previously, it was only available in Park. Here’s what that feature looks like in action:

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Check back later this week for a longer review of what we’ve noticed on Full Self-Driving v14.3.5.

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