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Tesla is patenting a clever way to train Autopilot with augmented camera images
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.”
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).”
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.
The Tesla Model Y became the first-ever car to reach a legendary Norwegian milestone, surpassing 100,000 new registrations after gaining a reputation as one of the most popular vehicles in the country and the world.
As of May 20, Norwegian authorities have registered 100,224 units of the electric SUV, according to data from local outlet Opplysningsrådet for veitrafikken (OFV).
By population, roughly one in every 29 passenger cars on Norwegian roads is now a Model Y, underscoring its rapid rise as a national favorite.
Since the first deliveries in August 2021, the Model Y has transformed from a newcomer to a staple in Norwegian traffic.
Tesla back on top as Norway’s EV market surges to 98% share in February
Geir Inge Stokke, the Managing Director of OFV, described the achievement as “remarkable,” noting that few single models have gained such traction so quickly. “Tesla Model Y has hit the Norwegian market spot on, and the numbers illustrate how fast the EV market has developed here,” Stokke said.
The Model Y’s success reflects Norway’s aggressive push toward electrification. Nearly nine out of ten units, 87.6 percent, to be exact, are privately registered, with the remaining 12.4 percent on company plates. Owners span the country, from major cities to smaller municipalities, proving it is no longer just an urban or niche vehicle but a true “people’s car.
Who is Buying Tesla Model Ys in Norway?
Typical Model Y drivers are men in their early 40s. The average registered user age is 44, with 83 percent male and 17 percent female. Stokke noted that household usage often extends beyond the primary registrant, broadening the vehicle’s real-world appeal.
Geographically, adoption concentrates in urban centers with strong charging infrastructure. Oslo leads with 16,861 registrations (16.82 percent of the national total), followed by Bergen (7,450), Bærum (4,313), and Trondheim (4,240).
The top five municipalities—Oslo, Bergen, Bærum, Trondheim, and Asker—account for 35,463 units, or about 35 percent of all Model Ys. Yet the vehicle’s presence outside big cities highlights its broad acceptance.
Growth Trajectory and Popularity
Tesla built a lot of sales momentum in a short amount of time. In 2021, registrations closed out at 8,267, but more than doubled to more than 17,000 units in 2022 and more than 23,000 units in 2023. 2025 was the company’s strongest year yet, as Tesla managed to record 27,621 registrations.
Through 2026, Tesla already has 7,036 registrations.
Tesla’s Global Success with the Model Y
Tesla has tasted so much success with the Model Y; it has been the best-selling car in the world three times, it has dominated EV sales in numerous countries, and contributed to a mass adoption of electric vehicles across the planet.
As Stokke emphasized, the Model Y’s journey from newcomer to icon mirrors Norway’s broader success story. With robust incentives that push sales, excellent infrastructure, and consumer eagerness to transition to sustainable powertrains, the country continues setting global benchmarks in sustainable mobility.
The Tesla Model Y stands as a shining example of how quickly change can happen when conditions align.
SpaceX has disclosed the full financial details of its groundbreaking agreement with Anthropic, confirming that the AI company will pay $1.25 billion per month for dedicated high-performance computing resources.
The revelation came through SpaceX’s latest securities filing in preparation for its initial public offering, shedding light on one of the largest compute deals in the artificial intelligence sector to date. The prospectus was released last night, as SpaceX is heading toward its IPO.
This arrangement underscores the fierce demand for specialized infrastructure as frontier AI models require unprecedented levels of processing power to train and operate effectively. Industry analysts see the disclosure as a significant milestone, highlighting how top AI labs are locking in massive capacity to stay ahead in a rapidly accelerating field.
For SpaceX, it feels like a massive move that pushes its perception as a company from space exploration to artificial intelligence.
SpaceX is following in Tesla’s footsteps in a way nobody expected
The comprehensive deal grants Anthropic exclusive access to SpaceX’s Colossus clusters, encompassing Colossus I and the substantially expanded Colossus II, which together deliver hundreds of megawatts of power along with more than 200,000 NVIDIA GPUs.
Payments extend through May 2029, totaling nearly $45 billion overall; capacity is scheduled to ramp up during May and June 2026 at an initial discounted rate to facilitate seamless integration. Both companies retain the option to terminate the agreement with ninety days’ notice, so there is definitely some flexibility for both.
This pact not only enhances Anthropic’s ability to scale usage limits for Claude users but also injects substantial recurring revenue into SpaceX, bolstering its expansion into advanced data center operations and future orbital computing initiatives.
Observers describe the collaboration between the two companies as strategically advantageous because it gives Anthropic cutting-edge AI development the opportunity to collaborate with SpaceX’s expertise in rapid, large-scale infrastructure deployment.
This disclosure arrives at a pivotal moment when computing resources have become the primary bottleneck for AI progress.
As leading organizations compete to build more powerful systems, securing reliable, high-density facilities has emerged as a key differentiator.
SpaceX’s sites, such as those in Memphis, offer superior power availability and advanced cooling solutions that set them apart from conventional providers. For Anthropic, the added capacity is expected to deliver tangible improvements, including extended context windows, quicker inference times, and innovative features that appeal to both enterprise clients and individual users.
Looking ahead, the partnership paves the way for ambitious joint projects, including potential space-based AI compute platforms designed to overcome terrestrial limitations on energy and thermal management. Such efforts could redefine sustainable computing at massive scales.
Financially, the deal solidifies SpaceX’s diverse revenue profile ahead of its public market debut, extending beyond traditional aerospace activities. The massive check SpaceX will cash each month opens up the idea that additional
While some experts question the sustainability of these enormous expenditures given ongoing efficiency gains in AI architectures, the commitment reflects a strong belief in sustained demand growth.
The agreement also exemplifies productive synergies across sectors, with aerospace engineering insights optimizing AI hardware performance. As global attention on technology concentration increases, arrangements of this nature may help shape equitable access to critical resources.
Elon Musk
SpaceX just filed for the IPO everyone was waiting for
SpaceX filed its public S-1, revealing $18.7 billion in revenue and billions in losses.
SpaceX publicly filed its S-1 registration statement with the Securities and Exchange Commission on May 20, 2026, making its financial details available to the public for the first time ahead of what could be the largest IPO in history.
An S-1 is the formal document a company must submit to the SEC before going public. It includes audited financials, risk factors, business descriptions, and how the company plans to use the money it raises. Companies are required to file one before selling shares to the public, and it must be published at least 15 days before the investor roadshow begins. SpaceX had already submitted a confidential draft to the SEC in April, which allowed regulators to review the filing privately before it went public.
The S-1 reveals that SpaceX generated $18.7 billion in consolidated revenue in 2025, driven largely by its Starlink satellite internet division, which posted $11.4 billion in revenue, growing nearly 50% year over year. Despite that growth, the company lost about $4.9 billion in 2025 and has burned through more than $37 billion since its founding.
SpaceX just forced Verizon, AT&T and T-Mobile to team up for the first time in history
A significant portion of those losses trace back to xAI, Elon Musk’s artificial intelligence company, which was recently merged into SpaceX. SpaceX directed roughly 60% of its capital spending in 2025 to its AI division, totaling around $20 billion, yet that division lost billions and grew revenue by only about 22%.
SpaceX plans to list its Class A common stock on Nasdaq under the ticker SPCX, with Goldman Sachs, Morgan Stanley, and Bank of America leading the offering. The dual-class share structure means going public will not meaningfully reduce Musk’s control, as Class B shares he holds carry 10 votes per share compared to one vote for public Class A shares.
The company is targeting a raise of around $75 billion at a valuation of roughly $1.75 trillion, which would make it the largest IPO ever. The investor roadshow is reportedly planned for June 5.
Tesla Model Y becomes first-ever car to reach legendary milestone
SpaceX reveals what Anthropic will pay for massive compute deal
