News
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 to become America’s Military data backbone for missiles, drones, and warfighters
The Space Force just handed SpaceX $2.29 billion to build the military’s space internet backbone.
The U.S. Space Force awarded SpaceX a $2.29 billion contract on May 26, 2026 to build the backbone of its Space Data Network, a satellite-based communications system designed to keep American military forces connected anywhere on Earth in real time. The contract is firm-fixed-price and requires SpaceX to deliver a fully operational prototype by the end of 2027.
In plain terms, the SDN Backbone is the plumbing behind the military’s space-based internet. It functions as a low Earth orbit satellite constellation providing robust, high-capacity, and low-latency data transport for the Joint Force, connecting sensors and weapons systems continuously, globally, and securely. Think of it as a private, hardened version of Starlink built specifically for battlefield communications, one that soldiers, ships, and aircraft can rely on even in contested environments where ground-based networks have been disrupted.
SpaceX is quietly becoming the U.S. Military’s only reliable rocket
The Space Force was direct about why SpaceX was selected. “The SDN Backbone leverages the best of commercial innovation and delivers a strong foundation for the SDN mission set — a huge benefit and enabler for our warfighters,” said USSF Col. Ryan Frazier.
“We aren’t trading speed for scale; we are demanding both. By using rapid prototyping and Other Transaction Authorities, we are ensuring our advanced solutions are integrated and delivered to the warfighter as fast as possible,” added USSF Lt. Col. Fry, SDN Backbone system program manager.
The SDN Backbone will work alongside the Space Development Agency’s Transport Layer, with the two systems forming a unified open architecture to provide critical data transport for current and future Department of War missions.
As Teslarati has reported, this is not SpaceX’s first Space Force contract of 2026. In April, the Space Force awarded SpaceX $178.5 million to launch missile tracking satellites, and SpaceX is already embedded in the Golden Dome missile defense software group. The $2.29 billion SDN Backbone award puts SpaceX at the center of how the American military communicates in space, a position with direct implications for its reported $1.75 trillion IPO valuation as the company heads toward a public offering as early as June 2026.
Tesla’s dedicated factory for building up to ten million Optimus units is officially under construction at Gigafactory Texas.
Drone footage released on May 27 by Giga Texas observer Joe Tegtmeyer captures the significant milestone of the first steel structure officially standing at Tesla’s new Optimus factory on the North Campus of the facility.
Phase two of land reclamation is advancing steadily, and the progress will let the new building extend nearly the full length of the main Giga Texas factory, potentially exceeding 4,000 feet, while measuring somewhere between 50 and 70 meters narrower. Extensive foundation work is proceeding as well.
Big news at the new Optimus 10m/y factory construction site today! The 1st steel structure has been erected & as expected the second phase of land reclamation is underway.
This will allow this new factory to grow to nearly the same length as the main Giga Texas factory,… pic.twitter.com/FidRLV6XpU
— Joe Tegtmeyer 🚀 🤠🛸😎 (@JoeTegtmeyer) May 27, 2026
This facility forms a central element of Tesla’s broader North Campus expansion at Giga Texas. The project will add more than 5.2 million square feet of new industrial space. It sits alongside other advanced developments, including a Terafab for next-gen AI chips. The scale reflects Tesla’s commitment to transforming humanoid robotics into a core pillar of the company’s future.
Musk has said that Optimus will be the biggest product in the world on several occasions. He believes it will be Tesla’s biggest valuation contributor.
Tesla prepares to expand Giga Texas with new Optimus production plant
Tesla plans to build about 10 million robots at the site annually once it is completed, which would be about 27,000 units each day.
The Optimus plant at Giga Texas is part of Tesla’s phased strategy for Optimus manufacturing. In an effort to start production of the robot well before the Giga Texas plant is complete, Tesla ended production of the Model S and Model X vehicles, which were built in Fremont, California, to make way for initial Optimus manufacturing efforts.
Production there will start in either July or August of this year, and early units will support internal factory tasks while the team gathers real-world data to refine processes. The Gigafactory Texas facility will house a second-gen production line. It targets high-volume output starting in Summer 2027.
Musk has repeatedly described Optimus as potentially more valuable than Tesla’s entire vehicle business. Current versions are already completing minor tasks around various facilities, while Tesla continues to refine its abilities and add new features.
Tesla’s total investment could reach several billion dollars. Significant challenges lie ahead, including the creation of an entirely new manufacturing ecosystem, the refinement of AI systems for dependable autonomy, and the development of reliable supply chains for actuators, sensors, and other components.
Nevertheless, the visible progress at Giga Texas highlights Tesla’s capacity to translate ambitious concepts into physical reality.
Tesla’s Optimus factory stands as much more than a simple expansion project, as it is quite literally the second phase of what could potentially be the biggest product ever. With construction beginning, 2027 is poised to become a transformative year for Tesla, as it evolves even further from an electric vehicle leader into a pioneer of intelligent, general-purpose machines.
Tesla Vice President of Vehicle Engineering, Lars Moravy, recently revealed the company has thought about introducing a Plaid powertrain on the Model 3, but there could be some challenges involved.
On the Ride the Lightning podcast, Moravy revealed that he thinks about a Plaid Model 3 “all the time,” and it certainly has a place in Tesla’s potential lineup of future vehicles.
Now that the Plaid powertrain is technically defunct due to the newfound absence of the Model S and Model X, Tesla could find a way to reintroduce the lightning-quick trim level to its mass-market vehicles.
But there are going to be some challenges with it. Moravy said that the Model 3 Plaid would likely adopt the carbon-sleeved motors that the Model S Plaid had. However, packaging would be a major challenge, as Moravy said on the podcast, it would be a “tight engineering squeeze.”
It’s important to note that there are no active production plans for the Model 3 Plaid at this point, but it’s also worth noting that with the Model S and Model X Plaid no longer available, Tesla would likely be willing to introduce something that is even more white-knuckle than the Model 3 Performance, which already boasts a 2.9-second 0-60 MPH acceleration rate and a top speed of 163 MPH.
Of course, there is the Roadster, but we don’t know when that will exactly make it to market, and we know that, for sure, it will not be accessible to many.
Tesla unveils juicy new detail on the Roadster and hints at new unveil timeline
Tesla has prided itself in building some of the best cars out there, but they’re also interested in building cars that are simply fun to be in.
A Plaid Model 3 could truly push the limits and could end up being one of the best cars Tesla will ever build, especially if it can shave off at least half of a second from its 0-60 MPH time and increase its top speed slightly.
More than anything, the real changes will be in the ride and aerodynamics. Tesla improving things like the suspension, handling, and downforce will be the true trademarks of its Plaid powertrain; putting it in the Model 3 could be a great move for the company and for customers interested in high-end performance.
SpaceX to become America’s Military data backbone for missiles, drones, and warfighters
Tesla’s dedicated Optimus factory construction officially underway at Giga Texas
