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Google’s DeepMind unit develops AI that predicts 3D layouts from partial images
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.
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.Â
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.
In a major development that will inevitably strengthen Tesla’s dominant position in the American EV market, Polestar has been effectively banned from selling new vehicles in the United States, starting with the 2027 model year.
The U.S. Department of Commerce denied Polestar authorization under the Connected Vehicle Rule, which prohibits vehicles containing certain connected technologies (Cellular, Wi-Fi, Bluetooth, etc.) linked to China or Russia due to national security risks, including potential data collection on American drivers.
🚨 A Tesla competitor goes down
Polestar will no longer sell new vehicles in the United States starting with the 2027 model year.
The U.S. Department of Commerce denied the brand authorization under the Connected Vehicle Rule, which restricts the sale of cars with software and… pic.twitter.com/TrwnQeoiES
— TESLARATI (@Teslarati) June 25, 2026
Polestar, which is majority-owned by China’s Geely Holding, could not obtain the required exemption despite producing some models domestically.
Polestar confirmed it will sell off any remaining inventory of the Polestar 3 and Polestar 4 models, while continuing service and warranty support for existing customers. No new models or major refreshes will reach U.S. buyers, and the company is pivoting its growth strategy to Europe, where it already generates the vast majority of its sales.
The outcome removes a direct premium EV competitor that had positioned itself as a stylish, performance-oriented alternative to Tesla’s lineup. The Polestar 2 challenged the Model 3, while the Polestar 3 and 4 targeted segments overlapping with the Model Y and upcoming Tesla offerings. Polestar’s U.S. sales had already been sluggish amid intense competition and slower demand, representing just 6 percent of its global volume in the first quarter of 2026.
While Polestar was not on Tesla’s level in the U.S., it still places a dent in the evergrowing field of Tesla competitors in the country, where it has long dominated EV sales.
Tesla faces none of these hurdles. As a U.S.-founded and U.S.-headquartered company with major manufacturing in Fremont, Austin, and Nevada, Tesla’s vehicles are built with compliant domestic and allied supply chains. Its Full Self-Driving technology, over-the-air software updates, and vertically integrated ecosystem were developed entirely in-house without foreign ownership entanglements that trigger national security reviews, at least in the U.S.
Of course, it did face a similar threat in China a few years back:
Elon Musk responds to reports of Tesla ban among China’s military over security concerns
The Connected Vehicle Rule, first advanced under the prior administration and upheld under the current one, is part of a broader U.S. effort to protect the domestic auto industry and critical technology from Chinese influence. High tariffs on Chinese-made EVs and related restrictions have already reshaped the market. Tesla benefits directly: it avoids these barriers while continuing to lead in U.S. EV sales volume, Supercharger network expansion, and energy storage integration.
By clearing Polestar from the new-vehicle playing field, the policy reduces competitive pressure in the premium and performance EV segments where Tesla has invested billions. American consumers seeking cutting-edge electric vehicles now have one fewer option tied to foreign adversaries — and one clearer path to the market leader that has driven the EV transition from the start.
For Tesla, this is more than regulatory relief. It is a strategic tailwind that reinforces its position as America’s premier EV innovator at a time when domestic manufacturing and technological independence matter most.
Tesla Cybercab stands to gain from new rules that the Trump Administration is aiming to enforce on autonomous vehicles. On Thursday, NHTSA, under the Trump Administration’s U.S. Department of Transportation, commenced rulemaking on the Federal Motor Vehicle Safety Standards (FMVSS).
This effort aims to eliminate the mandate for manual brake pedals in vehicles that are designed to be driven exclusively by automated driving systems. This would impact the Tesla Cybercab, which the company has stated would operate without a steering wheel or pedals.
Tesla Cybercab launch is imminent after latest sighting at Giga Texas
The Trump Administration is looking to revise FMVSS No. 135, which requires standard braking systems on light-duty vehicles.
Currently, the regulation requires light-duty cars to use traditional manual braking systems that allow operators to slow the vehicle. With the advent of self-driving in the U.S., these regulations need updating, and these are the changes that could come to FMVSS No. 135:
- Removes requirements for hand- or foot-operated brake controls for vehicles designed never to be operated by a human. Existing rules still apply to AVs that retain manual controls.
- All subject vehicles must still meet the same stopping distance performance criteria via alternative testing procedures.
- While this update ensures AVs can physically stop when commanded, NHTSA is separately developing safety performance requirements for AVs in real-world driving scenarios.
- NHTSA will continue to use its broad defect enforcement authority to investigate unsafe ADS behavior and oversee recalls.
As autonomy becomes a greater part of passenger travel, these types of rule adjustments will be more than reasonable. It will give manufacturers the ability to self-certify their vehicles and avoid any red tape that could ultimately delay the deployment of these vehicles.
Administrators are also incredibly excited about the opportunity to play a role in the advancement of self-driving vehicles.
“We are at the cusp of the greatest technological revolution in vehicle technology since the innovation of the Model T,” NHTSA Administrator Jonathan Morrison said. “If we want America to lead the way, we have to reimagine our regulatory framework. That’s why under Secretary Sean Duffy’s AV Framework, NHTSA is tearing down pointless barriers to innovative designs while strengthening the fundamental safety requirements that matter and holding AV developers accountable for safe performance.”
The Cybercab entered mass production at Gigafactory Texas in April. Tesla ultimately plans to push the vehicle into its Robotaxi fleet, potentially when frameworks like these are established.
Tesla plans to boost production at its Gigafactory Berlin plant in Germany following a sharp rebound in sales and demand in Europe after a softer 2025.
The plans put Tesla in a better position to compete with strengthening companies in Europe and potentially other markets; demand indicators show Tesla is much better off than in 2025.
Last year was a tough year for Tesla in terms of overall demand in Europe. The company produced over 200,000 vehicles at the German plant last year, a soft figure compared to the 375,000 vehicles Tesla lists as its current capacity at the factory.
🚨 Tesla said this morning it will ramp up production at Gigafactory Berlin to a volume of 7,500 vehicles per week.
This is a 20 percent boost in production. Tesla will hire 1,000 new employees to help with the increase.$TSLA pic.twitter.com/kravKfRO5n
— TESLARATI (@Teslarati) June 25, 2026
Tesla’s overall European sales dropped significantly last year due to a variety of factors. However, sales are rebounding, and demand is strong once again, and only getting stronger. Tesla is now planning to bump production of Model Y vehicles at Giga Berlin upward by about 20 percent. It will also bring 1,000 new jobs to the plant.
Tesla confirmed the details of its planned production expansion in Germany this morning. It is a strategy to keep up with strengthening demand.
In Q1, Tesla saw a record 61,000 vehicles produced at Giga Berlin. European registrations rebounded sharply, with Model Y seeing 117 percent increases in March 2026 compared to last year. Germany alone saw stark increases, with a quadrupling in registrations to 9,252 units.
This trend continued in other key European markets, including France, Denmark and Sweden. Tesla registrations were up over 46 percent in some of these markets, and Model Y continued its trend as a top BEV in the market.
Demand has been recovering strongly in 2026, giving Tesla a reason to expand production efforts at the factory. These increases signal management’s confidence in sustained or growing European pull for Berlin-built vehicles.
One of Tesla’s biggest threats just got banned in the U.S.
Tesla Cybercab stands to gain from new Trump autonomy rules
