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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.”

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.”

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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).”

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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Google just picked SpaceX for its first step into orbital AI

Google will launch its first Project Suncatcher AI satellite on SpaceX’s Transporter-18 rideshare next week.

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Google is about to put its own AI chips into orbit for the first time, and it is paying SpaceX to get them there.

The company said Thursday that the first in-orbit test of Project Suncatcher, its research effort to find out whether space can host large-scale AI computing, will fly next week on SpaceX’s Transporter-18 rideshare mission.

The satellite, called MVP, is about the size of a refrigerator and carries four of Google’s Tensor Processing Units, the same chips Google runs in its ground data centers. Google originally planned to launch two custom satellites in 2027, but chose to move faster by integrating its chips into a satellite.

MVP’s solar panels supply about one kilowatt of power, and Google will run Gemini models on the TPUs only in bursts of roughly 15 minutes before the chips shut down so the radiators can shed heat. In a blog post, Google said its Trillium TPUs survived vibration testing that mimicked sustained launch loads of up to 10g, with individual components seeing 50 to 100g, and handled a radiation dose greater than a five year mission would deliver.

SpaceX and Google mull massive partnership on Musk’s orbital data dream: report

Next week’s flight, slated for October 1, follows a relationship that became public in May, when Teslarati reported that Google was in talks with SpaceX for a launch deal tied to orbital data centers. Google also holds a stake of roughly 6% in SpaceX.

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The two companies are chasing the same idea from very different starting points. SpaceX’s own orbital compute program is built around the AI1 satellite, a roughly 70 meter structure derived from Starlink V3 hardware that is designed for 150 kW of peak compute, about 150 times the power MVP will draw. Elon Musk has brushed off concerns about crowding orbit with those satellites, and SpaceX is building its Gigasat factory in Bastrop, Texas, to produce them, targeting an annualized rate of about 1 GW of space compute by the end of 2027.

Musk also posted on X on Thursday that “the amount of compute in space will obviously round up to 100% of all compute.”

Google has been more cautious in public. Its research estimates that launch prices need to fall below about $200 per kilogram before an orbital data center can compete with a ground facility on energy cost, a threshold the company believes could be reached around the mid 2030s. The Suncatcher team has said it expects the effort to remain a project rather than a product for years, which leaves the first real test of its hardware riding on a rocket from the company with the most aggressive timeline in the field.

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Tesla Cybercab gets initial tie-in to localized, in-house cathode plant

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Credit: Tesla

Tesla has taken another concrete step toward owning its battery supply chain, and it’s doing so with what is perhaps the most important vehicle in its short-but-storied history.

On September 23, Tesla announced that it has officially built the first Cybercab with cathode material produced in-house at the company’s first cathode plant in the U.S., and the first in the U.S. overall.

Active cathode material is the most expensive piece of a lithium-ion battery cell, and it often accounts for more than a third of cell cost. For years, the industry sourced a majority of it from Asia, but Tesla’s decision to make it in the United States bodes well for the Cybercab project. This is the latest chapter in Tesla’s vertical integration strategy, which began in public at Battery Day in 2020.

At the Battery Day Event, Elon Musk said the company would build a North American cathode plant and overhaul the process to cut costs and waste, while also making some of the most powerful and long-lasting cells in the industry.

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The Austin facility took years to appear. Tesla filed permits for “Project Cathode” in 2022 on land near Giga Texas. By mid-2022, the building frame was up and Tesla later invested hundreds of millions of dollars as part of a larger expansion of the Giga Texas plant. The company stated it was operating the first large-scale cathode production facility in North America to supplement 4680 cell production.

One month later, that material reached a finished Cybercab.

The timing of this breakthrough is monumental for the Cybercab program. As Tesla officially launched the first Cybercab rides to the public earlier this month, production of the ride-hailing-geared vehicle is moving forward on the planned S-curve that CEO Elon Musk told everyone to expect.

Nevertheless, packs of Cybercab units have been spotted throughout the United States, in an effort to potentially activate the fleet as soon as the company gains regulatory approval in various geographic areas.

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On top of that, Tesla owning the cathode step and pairing it with its own in-house lithium from the Gulf Coast refinery shortens the supply chain that once stretched thousands of miles and subjects every pack to fewer external price shocks and geopolitical risks.

Tesla is not yet independent of all of its foreign suppliers, as some precursor metals come from mines and chemical plants. But the first in-house cathode Cybercab shows the company is closing the most expensive and most concentrated gap in its battery production efforts. For a vehicle like Cybercab to operate at a high utilization within the Robotaxi network, that control over cost is so crucial.

It is arguably as important as the software that drives it.

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Tesla leaks Semi customers ahead of handover event

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Credit: Tesla

Tesla is set to inaugurate its dedicated Semi factory in Sparks, Nevada, this evening, but drone footage has already started to show who is expected on the handover stage.

Zanegler, a drone operator who regularly documents Tesla Semi operations in Nevada, filmed a row of new-generation Semi units parked outside of the plant with customer branding applied. The liveries visible in the video include companies like PepsiCo, U.S. Foods, Einride, DHL, WattEV, and others that have committed to utilizing Tesla’s Class 8 electric truck in their fleets.

Several of those company names already sit within Tesla’s public ordering book, including PepsiCo, which has been the program’s primary anchor customer since the first Semi deliveries in December 2022. PepsiCo now runs dozens of Tesla Semi units in daily service, with drivers completing regional routes.

Einride placed a 500-unit order in August, which was, at the time, the largest single Semi commitment. First deployments of their Semi units are planned for this month and will eventually span across California, Texas, New Jersey, Illinois, and Georgia. Meanwhile, IMC Logistics announced a 50-truck California order this week.

Tesla Semi lands the biggest electric truck deal in U.S. history

Other names, like LTS, OK Produce, and HMD, have not been widely confirmed as firm buyers, but their presence on the lot is perhaps the clearest signal that Tesla intends to expand on that list this evening at the event.

Tesla first unveiled the Semi back in 2017 with a 2019 production target.

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Limited pilot builds reached PepsiCo in late 2022, and high-volume production began at the new 1.7-million-square-foot plant that sits logically positioned next to Tesla’s Gigafactory Nevada. Tesla Semi program director Dan Priestley has said that Tesla expects to build “many thousands” of Semi units this year, but as with every Tesla release, there have been set expectations of an S-curve ramp.

Outside estimates still put 2026 deliveries in the 5,000-to-15,000 range, but it will ultimately depend on Tesla’s readiness to put those units out, as well as how smoothly production is moving internally.

Tesla’s Semi Rollout event is set to start tonight at the Sparks factory, and it will be livestreamed on X starting at 6 p.m. PDT / 9 p.m. ET.

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