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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.
News
Ford is charging for a basic EV feature on the Mustang Mach-E
When ordering a new Ford Mustang Mach-E, you’ll now be hit with an additional fee for one basic EV feature: the frunk.
Ford is charging an additional fee for a basic EV feature on its Mustang Mach-E, its most popular electric vehicle offering.
Ford has shuttered its initial Model e program, but is venturing into a more controlled and refined effort, and it is abandoning the F-150 Lightning in favor of a new pickup that is currently under design, but appears to have some favorable features.
However, ordering a new Mustang Mach-E now comes with an additional fee for one basic EV feature: the frunk.
The frunk is the front trunk, and due to the lack of a large engine in the front of an electric vehicle, OEMs are able to offer additional storage space under the hood. There’s one problem, though, and that is that companies appear to be recognizing that they can remove it for free while offering the function for a fee.
Ford is now charging $495 on the Mustang Mach-E frunk (front trunk). What are your thoughts on that? pic.twitter.com/EOzZe3z9ZQ
— Alan of TesCalendar 📆⚡️ (@TesCalendar1) February 24, 2026
Ford is charging $495 for the frunk.
Interestingly, the frunk size varies by vehicle, but the Mustang Mach-E features a 4.7 to 4.8 cubic-foot-sized frunk, which measures approximately 9 inches deep, 26 inches wide, and 14 inches high.
When the vehicle was first released, Ford marketed the frunk as the ultimate tailgating feature, showing it off as a perfect place to store and serve cold shrimp cocktail.
Ford Mach-E frunk is perfect for chowders and chicken wings, and we’re not even joking
It appears the decision to charge for what is a simple advantage of an EV is not going over well, as even Ford loyal customers say the frunk is a “basic expectation” of an EV. Without it, it seems as if fans feel the company is nickel-and-diming its customers.
It will be pretty interesting to see the Mach-E without a frunk, and while it should not be enough to turn people away from potentially buying the vehicle, it seems the decision to add an additional charge to include one will definitely annoy some customers.
News
Tesla to improve one of its best features, coding shows
According to the update, Tesla will work on improving the headlights when coming into contact with highly reflective objects, including road signs, traffic signs, and street lights. Additionally, pixel-level dimming will happen in two stages, whereas it currently performs with just one, meaning on or off.
Tesla is looking to upgrade its Matrix Headlights, a unique and high-tech feature that is available on several of its vehicles. The headlights aim to maximize visibility for Tesla drivers while being considerate of oncoming traffic.
The Matrix Headlights Tesla offers utilize dimming of individual light pixels to ensure that visibility stays high for those behind the wheel, while also being considerate of other cars by decreasing the brightness in areas where other cars are traveling.
Here’s what they look like in action:
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- Credit: u/ObjectiveScratch | Reddit
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- Credit: u/ObjectiveScratch | Reddit
As you can see, the Matrix headlight system intentionally dims the area where oncoming cars would be impacted by high beams. This keeps visibility at a maximum for everyone on the road, including those who could be hit with bright lights in their eyes.
There are still a handful of complaints from owners, however, but Tesla appears to be looking to resolve these with the coming updates in a Software Version that is currently labeled 2026.2.xxx. The coding was spotted by X user BERKANT:
🚨 Tesla is quietly upgrading Matrix headlights.
Software https://t.co/pXEklQiXSq reveals a hidden feature:
matrix_two_stage_reflection_dip
This is a major step beyond current adaptive high beams.
What it means:
• The car detects highly reflective objects
Road signs,… pic.twitter.com/m5UpQJFA2n— BERKANT (@Tesla_NL_TR) February 24, 2026
According to the update, Tesla will work on improving the headlights when coming into contact with highly reflective objects, including road signs, traffic signs, and street lights. Additionally, pixel-level dimming will happen in two stages, whereas it currently performs with just one, meaning on or off.
Finally, the new system will prevent the high beams from glaring back at the driver. The system is made to dim when it recognizes oncoming cars, but not necessarily objects that could produce glaring issues back at the driver.
Tesla’s revolutionary Matrix headlights are coming to the U.S.
This upgrade is software-focused, so there will not need to be any physical changes or upgrades made to Tesla vehicles that utilize the Matrix headlights currently.
Elon Musk
xAI’s Grok approved for Pentagon classified systems: report
Under the agreement, Grok can be deployed in systems handling classified intelligence analysis, weapons development, and battlefield operations.
Elon Musk’s xAI has signed an agreement with the United States Department of Defense (DoD) to allow Grok to be used in classified military systems.
Previously, Anthropic’s Claude had been the only AI system approved for the most sensitive military work, but a dispute over usage safeguards has reportedly prompted the Pentagon to broaden its options, as noted in a report from Axios.
Under the agreement, Grok can be deployed in systems handling classified intelligence analysis, weapons development, and battlefield operations.
The publication reported that xAI agreed to the Pentagon’s requirement that its technology be usable for “all lawful purposes,” a standard Anthropic has reportedly resisted due to alleged ethical restrictions tied to mass surveillance and autonomous weapons use.
Defense Secretary Pete Hegseth is scheduled to meet with Anthropic CEO Dario Amodei in what sources expect to be a tense meeting, with the publication hinting that the Pentagon could designate Anthropic a “supply chain risk” if the company does not lift its safeguards.
Axios stated that replacing Claude fully might be technically challenging even if xAI or other alternative AI systems take its place. That being said, other AI systems are already in use by the DoD.
Grok already operates in the Pentagon’s unclassified systems alongside Google’s Gemini and OpenAI’s ChatGPT. Google is reportedly close to an agreement that will result in Gemini being used for classified use, while OpenAI’s progress toward classified deployment is described as slower but still feasible.
The publication noted that the Pentagon continues talks with several AI companies as it prepares for potential changes in classified AI sourcing.
Ford is charging for a basic EV feature on the Mustang Mach-E
Tesla to improve one of its best features, coding shows
