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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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Tesla Cybercab specs revealed: range, curb weight, range ratings, and more

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(Credit: Teslarati)

Tesla’s Cybercab has taken a significant step toward production with new technical details emerging from 2026 EPA certification documents.

The filings, which include a Certificate of Conformity issued in late May, provide the most comprehensive public look yet at the purpose-built autonomous vehicle designed for high-volume, low-cost ride-hailing operations.

At its core, the Cybercab is a front-wheel-drive electric vehicle powered by a single 163 kW (219 horsepower) AC permanent magnet motor. Despite its modest output, prioritizing efficiency and cost over neck-snapping acceleration, the vehicle boasts a strong power-to-weight ratio thanks to its lightweight curb weight of 3,113 pounds and a GVWR of 3,730 pounds.

It operates on a 326-volt electrical architecture with a compact ~48 kWh lithium-ion battery pack. The standout revelation is the vehicle’s exceptional efficiency, which Tesla has routinely flexed in the past.

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EPA lab tests list an equivalent all-electric range of 418 miles combined and 375 miles on the highway. Tesla has previously targeted around 300 miles of real-world range, and analysts expect the final EPA-rated figure to land near 280-300 miles after adjustment factors.

At a certified 165 Wh/mi in earlier testing, the Cybercab is reportedly the most efficient EV ever produced, significantly outperforming vehicles like the Lucid Air Pure.

This efficiency stems from deliberate design choices tailored for robotaxi duty. The two-seater features a highly aerodynamic shape, minimal weight, which is aided by structural battery integration of what are likely 4680 cells, and no steering wheel or pedals in its fully autonomous configuration.

For ride-hailing fleets, where average trips are short, and can be just five or ten miles, the smaller battery enables faster charging cycles, lower material costs, and reduced vehicle price, a key to Tesla’s goal of a ~$30,000 production cost.

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Implications for Autonomous Mobility

These specs underscore Tesla’s strategy: maximize utilization and minimize operating expenses. A ~48 kWh pack could support dozens of short rides per charge, with energy costs potentially dropping below 20 cents per mile at scale. Front-wheel drive simplifies manufacturing and maintenance compared to dual-motor AWD setups in passenger Teslas.

The 219 hp motor provides ample performance for urban and highway speeds without excess, addressing questions about why such power is needed in a “slow” autonomous vehicle. Quick merges and hill climbing still matter for safety and passenger comfort.

Production has already begun at Giga Texas, with EPA certification clearing the path for U.S. deployment. While unsupervised Full Self-Driving remains the critical hurdle, these details paint a compelling picture of a vehicle engineered from the ground up for the robotaxi future: affordable to build, cheap to run, and capable of delivering strong range on a fraction of the battery capacity found in today’s EVs.

As Tesla ramps toward volume output, the Cybercab could reshape urban transportation economics.

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Tesla Cybercab snags huge regulatory green light that readies it for public roads

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Credit: Tesla

Tesla Cybercab, the all-electric ride-hailing-geared vehicle void of a steering wheel and pedals, has achieved a significant regulatory milestone. The vehicle has officially secured an EPA Certificate of Conformity for the 2026 Cybercab, classifying it as a battery electric Zero Emission Vehicle (ZEV).

This certification confirms full compliance with federal Clean Air Act emission standards, paving the way for legal sales and operation across the United States.

A Certificate of Conformity (CoC) is a critical document issued by the U.S. Environmental Protection Agency (EPA) to vehicle manufacturers. It certifies that a specific class of vehicles meets all applicable federal emission requirements for the model year.

We have reported on several of them in the past, and it’s a good sign that a vehicle is close to being available to the public.

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Every vehicle sold in the U.S. must carry this approval, which covers exhaust emissions, evaporative emissions, and refueling standards. For battery electric vehicles like the Cybercab, it verifies zero tailpipe emissions and compliance with stringent testing protocols. The certificate, issued and effective May 26, 2026, was part of the EPA’s recent bi-weekly upload, detailing the Cybercab’s evaporative/refueling family and exhaust compliance.

It also revealed some other very important information, as the Cybercab’s “Charge Depleting Range” was rated at just over 418 miles. This was for city driving, while the highway range depletion test revealed just over 375 miles of range:

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This EPA approval is a foundational step for Tesla’s autonomous ambitions. While emission certification is standard for any new EV, it signals that the Cybercab is progressing through the full federal compliance process.

Tesla has already equipped prototypes with federal compliance stickers affirming adherence to safety, bumper, and theft-prevention standards via self-certification under FMVSS rules. This bypasses the traditional 2,500-vehicle exemption cap that previously constrained low-volume autonomous testing.

Production of the Cybercab ramped up at Giga Texas starting in early 2026, with volume targets aiming for hundreds of units per week and long-term ambitions of millions annually. The two-seater, steer-by-wire vehicle, lacking a steering wheel and pedals, features a sleek, minimalist design optimized for Robotaxi service.

Tesla Cybercab gets crazy change as mass production begins

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Priced under $30,000 at unveiling, it promises operating costs as low as $0.20–$0.40 per mile once scaled. Tesla has routinely flexed it as one of the most efficient vehicles of all time.

Regulatory progress extends beyond the EPA. The NHTSA has streamlined approvals for control-free vehicles, benefiting the Cybercab. Tesla operates supervised and unsupervised Robotaxi services in Texas cities like Austin, Dallas, and Houston using its fleet. California recently updated rules for driverless operations, including enforcement mechanisms for violations. Additional state-by-state approvals will be needed for nationwide rollout.

This EPA green light reduces a key barrier, building confidence among regulators, partners, and investors.

It underscores Tesla’s strategy of designing the Cybercab from the ground up for full compliance rather than retrofitting existing platforms. Challenges remain in scaling unsupervised autonomy, mapping approvals, and public acceptance, but the certification marks tangible momentum toward transforming urban mobility.

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With prototypes already testing on public roads and production accelerating, the Cybercab edges closer to redefining transportation. Tesla’s integrated approach—combining hardware simplicity, software prowess, and regulatory diligence—positions it uniquely in the robotaxi race.

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SpaceX soars with its first launch as a public company, marking a new era

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Credit: SpaceX

SpaceX executed its first Falcon 9 launch since going public on June 15, a routine yet symbolically powerful Starlink mission from Vandenberg Space Force Base in California.

Liftoff of the Falcon 9 booster B1093, on its 14th flight, occurred at approximately 8:34 a.m. PDT from Space Launch Complex 4E (SLC-4E), deploying 24 Starlink V2 Mini Optimized satellites into low-Earth orbit.

The first stage successfully landed on the droneship “Of Course I Still Love You” in the Pacific Ocean, underscoring the company’s unmatched reusability track record.

This mission comes just three days after SpaceX’s historic IPO on June 12, which shattered records as the largest ever. The company raised $75 billion by pricing shares at $135, with trading under ticker SPCX on Nasdaq opening at $150 and closing at $160.95—a 19 percent gain—valuing SpaceX at over $2.1 trillion.

The launch highlights the seamless transition from private innovator to public powerhouse. SpaceX, founded in 2002, has revolutionized access to space with over 650 Falcon 9 flights and a massive Starlink constellation now serving millions globally.

As a public company, it faces new pressures: quarterly earnings, shareholder scrutiny, and expectations to accelerate Starship development for Mars ambitions and deeper NASA partnerships. Yet the market response signals strong confidence in its dominance, as launch costs are slashed by 95 percent, rapid satellite deployment, and a backlog of government and commercial contracts.

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SpaceX maintains bold advertising push for Starlink, contrasting Tesla’s minimalistic approach

Analysts view today’s flight as business as usual, but it carries extra weight. With shares volatile in early trading days, successful operations reassure investors that core capabilities remain unaffected by public status.

SpaceX now operates under heightened transparency, potentially unlocking capital for ambitious goals like Starship orbital tests and global broadband expansion.

Challenges loom, including regulatory hurdles for megaconstellations, competition in reusable rockets, and orbital debris concerns. Nevertheless, this morning’s flawless execution reinforces SpaceX’s trajectory.

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As Musk often notes, the company’s mission—to make humanity multiplanetary—now aligns with Wall Street’s growth demands. The stars, it seems, are aligning for both.

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