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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.
Elon Musk
SpaceX just got pulled into the biggest Weapons Program in U.S. history
SpaceX joins the Golden Dome software group, deepening its role in America’s most expensive defense program.
SpaceX has joined a nine-company group developing the core operating software for the Golden Dome, America’s next-generation missile defense system. According to a Bloomberg report, SpaceX is focused on integrating satellite communications for military operations and is working alongside eight other defense and artificial intelligence companies, including Anduril Industries, Palantir Technologies, and Aalyria Technologies, to build software connecting missile defense capabilities.
The Golden Dome concept dates back to President Trump’s 2024 campaign, and on January 27, 2025, he signed an executive order directing the U.S. Armed Forces to construct the system before the end of his term. The system is planned to employ a constellation of thousands of satellites equipped with interceptors, with data centers in space providing automated control through an AI network.
FCC accepts SpaceX filing for 1 million orbital data center plan
Space Force Gen. Michael Guetlein, director of the Golden Dome initiative, has described the software layer as a “glue layer” that would enable officers to manage and control radars, sensors, and missile batteries across services. The consortium is aiming to test the platform this summer.
Trump selected a design in May 2025 with a $175 billion price tag, expected to be operational by the end of his term in 2029, though the Congressional Budget Office projected the cost could reach $831 billion over two decades.
The Golden Dome role is only the latest in a string of military wins for SpaceX. As Teslarati reported, the U.S. Space Force awarded SpaceX a $178.5 million task order on April 1, 2026 to launch missile tracking satellites for the Space Development Agency, covering two Falcon 9 launches beginning in Q3 2027. That came on top of more than $22 billion in government contracts held by SpaceX as of 2024, per CEO Gwynne Shotwell, spanning NASA resupply missions, classified intelligence satellites through its Starshield program, and military broadband.
The accumulation of defense contracts, now including a seat at the table on the most expensive weapons program in U.S. history, positions SpaceX as the dominant infrastructure provider for American national security in space. With a SpaceX IPO still on the horizon, each new contract adds weight to what is already one of the most consequential companies in aerospace history, raising real questions about how much of America’s defense architecture will depend on a single private operator before it ever trades publicly.
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Tesla pulls back the curtain on Cybercab mass production
Tesla’s Cybercab drives itself off the Gigafactory Texas line in a striking new production video.
Tesla has provided a first look from inside a production Cybercab as it drove itself off the assembly line at Gigafactory Texas. The video footage, posted on X, opens on the factory floor with robotic arms and assembly equipment visible through the Cybercab windshield, and follows the car through a branded tunnel marked “Cybercab”, before autonomously navigating itself to a holding lot.
The first Cybercab rolled off the Giga Texas production line on February 17, 2026, with Musk writing on X, “Congratulations to the Tesla team on making the first production Cybercab.” April marked the official shift to volume production. The Giga Texas line is being prepared to produce hundreds of units per week, with 60 units already spotted on the Gigafactory campus earlier this month.
Purpose-built for autonomy
Cybercab in production now at Giga Texas pic.twitter.com/Y9qG3KyWBa
— Tesla (@Tesla) April 23, 2026
The Cybercab was first revealed publicly at Tesla’s “We, Robot” event in October 2024 at Warner Bros. Studios in Burbank, California, where 20 pre-production units gave attendees rides around the studio lot. Musk said he believed the average operating cost would be around $0.20 per mile, and that buyers would be able to purchase one for under $30,000. The two-seat design is deliberate. Musk noted that 90 percent of miles driven involve one or two people, making a compact two-passenger vehicle the most efficient configuration for a fleet-scale robotaxi. Eliminating rear seats also removes complexity and cost, supporting that sub-$30,000 target.
Tesla’s annual production goal is 2 million Cybercabs per year once several factories reach full design capacity. The Cybercab has no steering wheel, no pedals, and relies entirely on Tesla’s vision-based FSD system. What the video shows is the first evidence of that system working not as a demo, but as a production reality, driving itself off the line and into the world.
🚗 Our first ride in Tesla Cybercab last October: pic.twitter.com/kGqIqgJPRn https://t.co/BITCXFhbVd
— TESLARATI (@Teslarati) April 22, 2025
Elon Musk
Elon Musk talks Tesla Roadster’s future
Elon Musk confirmed the Roadster as Tesla’s last manually driven car, with a debut coming soon.
During Tesla’s Q1 2026 earnings call on April 22, Elon Musk made a brief but notable comment about the long-awaited next generation Roadster while describing Tesla’s future vehicle lineup. “Long term, the only manually driven car will be the new Tesla Roadster,” he said. “Speaking of which, we may be able to debut that in a month or so. It requires a lot of testing and validation before we can actually have a demo and not have something go wrong with the demo.”
That single statement is the entire Roadster update from yesterday’s call, and while it represents another timeline shift, it comes as no surprise with Tesla heads-down-at-work on the mass rollout of its Robotaxi service across US cities, and the industrial scale production of the humanoid Optimus.
The fact that Musk specifically framed the Roadster as the last manually driven Tesla is significant on its own. As the rest of the lineup moves toward full autonomy, the Roadster becomes something rare in the Tesla-sphere by keeping the driver in control. Driving enthusiasts who buy a $200,000 supercar are not doing so to be passengers. They want the physical connection to the road, the feel of acceleration under their own input, and the experience of controlling something with that level of performance. FSD, however capable it becomes, removes that entirely. The Roadster signals that Tesla understands this distinction and is building a car specifically for the people who consider driving itself the point.
Tesla isn’t joking about building Optimus at an industrial scale: Here we go
The specs for the Roadster Musk has teased over the years are genuinely unlike anything in production. The base model targets 0 to 60 mph in 1.9 seconds, a top speed above 250 mph, and up to 620 miles of range from a 200 kWh battery. The optional SpaceX package takes it further, rumored to add roughly ten cold gas thrusters operating at 10,000 psi, borrowed directly from Falcon 9 rocket technology. With thrusters, Musk has claimed 0 to 60 mph in as little as 1.1 seconds. In a 2021 Joe Rogan interview he went further, stating “I want it to hover. We got to figure out how to make it hover without killing people.” Tesla filed a patent for ground effect technology in August 2025, suggesting the hover concept has not been abandoned. The starting price remains $200,000, with the Founders Series requiring a $250,000 full deposit. Some reservation holders placed those deposits in 2017 and are approaching a full decade of waiting.
With production now targeted for 2027 or 2028 at the earliest, the Roadster remains Tesla’s most audacious promise and its longest-running delay. But if what Musk is testing lives up to even half of what he has described, the demo alone should be worth waiting for.
Elon Musk says the Tesla Roadster unveiling could be done “maybe in a month or so.”
He said it should be an extraordinary unveiling event. pic.twitter.com/6V9P7zmvEm
— TESLARATI (@Teslarati) April 22, 2026
SpaceX just got pulled into the biggest Weapons Program in U.S. history
Tesla pulls back the curtain on Cybercab mass production
