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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.
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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Elon Musk teases expectations for Tesla’s AI6 self-driving chip
This optimistic timeline for tape-out—the stage where chip design is finalized before manufacturing—signals Tesla’s push to rapidly advance its silicon capabilities.
Tesla CEO Elon Musk is outlining expectations for the AI6 self-driving chip, which is still two generations away. Despite this, it is already in the plans of the company and its serial entrepreneur CEO, who has high expectations for it.
Musk provided fresh details on the company’s aggressive AI hardware roadmap, spotlighting the upcoming AI6 chip designed to supercharge Tesla’s self-driving tech, humanoid robots, and data center operations.
In a post on X dated March 19, Musk stated, “With some luck and acceleration using AI, we might be able to tape out AI6 in December.”
With some luck and acceleration using AI, we might be able to tape out AI6 in December
— Elon Musk (@elonmusk) March 19, 2026
This optimistic timeline for tape-out—the stage where chip design is finalized before manufacturing—signals Tesla’s push to rapidly advance its silicon capabilities.
The announcement builds on progress with the predecessor AI5. Earlier in January, Musk announced that the AI5 design was “in good shape” and “almost done,” describing it as an “existential” project for the company that demanded his personal attention on weekends.
He characterized AI5 as roughly equivalent to Nvidia’s Hopper class performance in a single system-on-chip (SoC) and Blackwell-level as a dual configuration, but at significantly lower cost and power usage.
Elon Musk is setting high expectations for Tesla AI5 and AI6 chips
Musk highlighted that AI5 “will punch far above its weight” thanks to Tesla’s co-designed AI software and hardware stack, making maximal use of every circuit. While capable of data center training tasks, it is primarily optimized for edge computing in Optimus robots and Robotaxi vehicles.
For AI6, Musk envisions substantial gains. “In the same half reticle and same process node, we think a single AI6 chip has the potential to match a dual SoC AI5,” he explained.
The company is targeting ambitious nine-month development cycles for future chips, allowing rapid iteration to AI7, AI8, and beyond. AI5/AI6 engineering remains Musk’s top time allocation at Tesla, with the CEO calling AI5 “good” and AI6 “great.”
Samsung is expected to manufacture the AI6 chips, following deals worth billions, while AI5 will leverage TSMC and Samsung production. These chips will form the backbone of Tesla’s Full Self-Driving system, enabling safer and more capable autonomy, alongside powering dexterous movements in Optimus bots and efficient inference in expanding data centers.
Tesla to discuss expansion of Samsung AI6 production plans: report
Musk has also restarted work on the Dojo 3 supercomputer project now that AI5 is progressing. Long-term plans include in-house manufacturing via the Terafab facility.
By accelerating chip development with AI tools, Tesla aims to reduce dependence on third-party GPUs and deliver high-performance, energy-efficient solutions tailored to its ecosystem. Success with AI6 could mark a major milestone in Tesla’s journey toward full autonomy and robotics leadership, though timelines remain subject to manufacturing realities.
Elon Musk
SpaceX is quietly becoming the U.S. Military’s only reliable rocket
Space Force drops ULA for SpaceX on GPS launch after Vulcan rocket anomaly investigation halts flights.
The U.S. Space Force announced today it is switching an upcoming GPS III satellite launch from United Launch Alliance’s Vulcan rocket to a SpaceX Falcon 9, a move that is as much a reflection of Vulcan’s mounting problems as it is a validation of SpaceX’s growing dominance in national security space launch. The GPS III Space Vehicle 09, originally contracted to fly on Vulcan this month, will now target a late April liftoff on Falcon 9, marking the fourth consecutive GPS III satellite the Space Force has moved to SpaceX after contracts were originally awarded to ULA.
The immediate trigger is a solid rocket motor anomaly that occurred on February 12 during Vulcan’s USSF-87 mission. Although the payloads reached orbit and ULA declared the mission successful, the company characterized the malfunction as a “significant performance anomaly” and has since paused all military launches on Vulcan pending a root cause investigation.
“With this change, we are answering the call for rapid delivery of advanced GPS capability while the Vulcan anomaly investigation continues,” said Systems Delta 81 Commander Col. Ryan Hiserote. “We are once again demonstrating our team’s flexibility and are fully committed to leverage all options available for responsive and reliable launch for the Nation.”
The broader reality is that SpaceX’s reliability record and launch cadence have made it the path of least resistance for the Pentagon, and bodes well with Elon Musk’s plans to IPO SpaceX sometime this year. Its Falcon 9 is the most flight-proven rocket in history, and the Space Force’s Rapid Response Trailblazer program was specifically designed to enable exactly this kind of provider swap for GPS missions, and effectively building SpaceX’s flexibility into the national security launch architecture by design.
For ULA, the stakes are existential. The company entered 2026 with aspirations of finally turning a corner after years of Vulcan delays, with interim CEO John Elbon pointing to a backlog of over 80 missions as reason for optimism. Meanwhile, SpaceX’s contracts with the Space Force have given it a formal pathway to take on even more national security launches going forward.
The significance of today’s announcement extends beyond one satellite swap. It reinforces that America’s most critical space infrastructure, including GPS, missile warning, and beyond, is increasingly dependent on a single commercial provider.
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Tesla Full Self-Driving gets huge breakthrough on European expansion
All documentation for UN R-171 approval and Article 39 exemptions has been submitted, with RDW now conducting its internal review. Approval in the Netherlands is expected on April 10, shifted from the original March 20 target, following 18 months of rigorous collaboration.
Tesla Full Self-Driving has gotten a huge breakthrough as the company is still planning big things for its European expansion, hoping to bring the impressive platform into the continent after years of attempts.
Tesla Europe has announced a major breakthrough: the company has officially completed the final vehicle testing phase for Full Self-Driving (Supervised) in partnership with the Dutch vehicle authority RDW.
All documentation for UN R-171 approval and Article 39 exemptions has been submitted, with RDW now conducting its internal review. Approval in the Netherlands is expected on April 10, shifted from the original March 20 target, following 18 months of rigorous collaboration.
Together with RDW, we have officially completed the final vehicle testing phase for Full Self-Driving (Supervised) and have submitted all documentation required for the UN R-171 approval + Article 39 exemptions. The RDW team is now reviewing the documentation and test results…
— Tesla Europe, Middle East & Africa (@teslaeurope) March 20, 2026
The process has been exhaustive. Tesla said it has logged more than 1.6 million kilometers of FSD (Supervised) testing on European roads, conducted over 13,000 customer ride-alongs, executed 4,500+ track test scenarios, produced thousands of pages of documentation covering 400+ compliance requirements, and completed dozens of independent safety studies.
The company expressed pride in the partnership and anticipation of bringing the feature to “patient EU customers” soon after approval.
Europe’s regulatory landscape has presented steep challenges for Tesla’s advanced driver-assistance systems. The EU enforces some of the world’s strictest safety standards under the United Nations Economic Commission for Europe framework, particularly UN Regulation 171 on Driver Control Assistance Systems.
Unlike the more permissive U.S. environment, European rules historically limited system-initiated maneuvers, required constant driver supervision, and demanded country-by-country or bloc-wide exemptions. Tesla faced repeated delays, with initial February 2026 targets pushed back amid RDW’s insistence that safety, not public or corporate pressure, would govern timelines.
Tesla Europe builds momentum with expanding FSD demos and regional launches
A former Tesla executive warned in 2024 that certain regulatory elements could slip to 2028, highlighting bureaucratic hurdles, extensive audits, and the need for harmonized data privacy and liability frameworks across fragmented member states.
Yet progress is accelerating. Amendments to UN R-171 adopted in 2025 now permit hands-free highway lane changes and other automated features, clearing technical barriers. Once the Netherlands grants national approval, mutual recognition allows other EU countries to adopt it immediately, potentially leading to an EU-wide rollout by summer 2026.
This European breakthrough is part of Tesla’s broader push into foreign markets. Full Self-Driving (Supervised) is already live in the United States and expanding rapidly.
In China, where partial approvals exist, CEO Elon Musk has targeted full rollout around the same February–March 2026 window, despite lingering data-security reviews.
Additional markets, including the UAE, are slated for early 2026 launches. These expansions are critical as Tesla seeks to monetize software amid softening EV demand globally.
For European Tesla owners, the wait appears nearly over. Approval would unlock advanced autonomy features that have long been available elsewhere, marking a pivotal step in Tesla’s global autonomy ambitions and reinforcing its commitment to navigating complex international regulations.
Elon Musk teases expectations for Tesla’s AI6 self-driving chip
SpaceX is quietly becoming the U.S. Military’s only reliable rocket
