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Google’s DeepMind unit develops AI that predicts 3D layouts from partial images

[Credit: Google DeepMind]

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Google’s DeepMind unit, the same division that created AlphaGo, an AI that outplayed the best Go player in the world, has created a neural network capable of rendering an accurate 3D environment from just a few still images, filling in the gaps with an AI form of perceptual intuition.

According to Google’s official DeepMind blog, the goal of its recent AI project is to make neural networks easier and simpler to train. Today’s most advanced AI-powered visual recognition systems are trained through the use of large datasets comprised of images that are human-annotated. This makes training a very tedious, lengthy, and expensive process, as every aspect of every object in each scene in the dataset has to be labeled by a person.

The DeepMind team’s new AI, dubbed the Generative Query Network (GQN) is designed to remove this dependency on human-annotated data, as the GQN is designed to infer a space’s three-dimensional layout and features despite being provided with only partial images of a space.

Similar to babies and animals, DeepMind’s GQN learns by making observations of the world around it. By doing so, DeepMind’s new AI learns about plausible scenes and their geometrical properties even without human labeling. The GQN is comprised of two parts — a representation network that produces a vector describing a scene and a generation network that “imagines” the scene from a previously unobserved viewpoint. So far, the results of DeepMind’s training for the AI have been encouraging, with the GQN being able to create representations of objects and rooms based on just a single image.

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As noted by the DeepMind team, however, the training methods that have been used for the development of the GQN are still limited compared to traditional computer vision techniques. The AI creators, however, remain optimistic that as new sources of data become available and as improvements in hardware get introduced, the applications for the GQN framework could move over to higher-resolution images of real-world scenes. Ultimately, the DeepMind team believes that the GQN could be a useful system in technologies such as augmented reality and self-driving vehicles by giving them a form of perceptual intuition – extremely desirable for companies focused on autonomy, like Tesla.

Google DeepMind’s GQN AI in action. [Credit: Google DeepMind]

In a talk at Train AI 2018 last May, Tesla’s head of AI Andrej Karpathy discussed the challenges involved in training the company’s Autopilot system. Tesla trains Autopilot by feeding the system with massive data sets from the company’s fleet of vehicles. This data is collected through means such as Shadow Mode, which allows the company to gather statistical data to show false positives and false negatives of Autopilot software.

During his talk, Karpathy discussed how features such as blinker detection become challenging for Tesla’s neural network to learn, considering that vehicles on the road have their turn signals off most of the time and blinkers have a high variability from one car brand to another. Karpathy also discussed how Tesla has transitioned a huge portion of its AI team to labeling roles, doing the human annotation that Google DeepMind explicitly wants to avoid with the GQN. 

Musk also mentioned that its upcoming all-electric supercar — the next-generation Tesla Roadster — would feature an “Augmented Mode” that would enhance drivers’ capability to operate the high-performance vehicle. With Tesla’s flagship supercar seemingly set on embracing AR technology, the emergence of new techniques for training AI such as Google DeepMind’s GQN would be a perfect fit for the next generation of vehicles about to enter the automotive market.

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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 Model Y becomes first-ever car to reach legendary milestone

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Credit: Tesla Manufacturing

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.

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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.

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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.

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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.

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SpaceX reveals what Anthropic will pay for massive compute deal

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Rendering of Elon Musk overlooking a Starship fleet (Credit: Grok)
Rendering of Elon Musk overlooking a Starship fleet (Credit: Grok)

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.

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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.

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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.

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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.

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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.

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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

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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.

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