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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.
Tesla has finished construction at its biggest Supercharger ever in Lost Hills, California, and all 168 stalls are officially open as of today.
After several years of development, the company has officially announced that the Lost Hills Supercharger, known as Project Oasis, is officially open with 168 stalls active and available to drivers.
Tesla announced the completion of the Lost Hills Supercharger on Tuesday, showing off the site, which is powered by 10 Megapack batteries for storage and is completely independent of the grid, as it has 11 MW of solar panels bringing energy to the massive Battery Energy Storage System (BESS).
All 168 Stalls at the Tesla Supercharger in Lost Hills, California are officially open! pic.twitter.com/eo9xmZyUNB
— TESLARATI (@Teslarati) November 25, 2025
This is the largest Supercharger in the world and opens just in time for the Thanksgiving holiday, which is the most-traveled weekend of the year in the United States.
Spanning across 30 acres, it was partially opened back in July 2025 as Tesla opened just 84 of the 168 stalls at the site. However, Tesla finished certifying the site recently, which enabled the Supercharger to open up completely.
The site generates roughly 20 GWh of energy annually, which is enough to power roughly 1,700 homes. The launch of this site specifically is massive for the company as it plans to launch more Superchargers in more rural areas, making charging more available for cross-country rides that require stops in more remote regions of the United States.
This is perhaps the only weak point of Tesla’s massive charging infrastructure.
It has some features that are also extremely welcome for some owners, including things like pull-through stalls for those who tow, an idea that was extremely popular following the launch of the Cybertruck.
Tesla has over 70,000 active Superchargers across the world. The company has also made efforts to create unique experiences at some of the stops, most notably with its Tesla Diner, located on Santa Monica Boulevard in Los Angeles.
That Supercharger has two massive drive-in movie theaters and will soon transition to a full-service restaurant following the departure of its executive chef, Eric Greenspan.
Elon Musk
Elon Musk proposes Grok 5 vs world’s best League of Legends team match
Musk’s proposal has received positive reception from professional players and Riot Games alike.
Elon Musk has proposed a high-profile gaming challenge for xAI’s upcoming Grok 5. As per Musk, it would be interesting to see if the large language model could beat the world’ best human League of Legends team with specific constraints.
Musk’s proposal has received positive reception from professional players and Riot Games alike, suggesting that the exciting exhibition match might indeed happen.
Musk outlines restrictions for Grok
In his post on X, Musk detailed constraints to keep the match competitive, including limiting Grok to human-level reaction times, human-speed clicking, and viewing the game only through a camera feed with standard 20/20 vision. The idea quickly circulated across the esports community, drawing commentary from former pros and AI researchers, as noted in a Dexerto report.
Former League pro Eugene “Pobelter” Park expressed enthusiasm, offering to help Musk’s team and noting the unique comparison to past AI-versus-human breakthroughs, such as OpenAI’s Dota 2 bots. AI researcher Oriol Vinyals, who previously reached Grandmaster rank in StarCraft, suggested testing Grok in RTS gameplay as well.
Musk welcomed the idea, even responding positively to Vinyals’ comment that it would be nice to see Optimus operate the mouse and keyboard.
Pros debate Grok’s chances, T1 and Riot show interest
Reactions weren’t universally optimistic. Former professional mid-laner Joedat “Voyboy” Esfahani argued that even with Grok’s rapid learning capabilities, League of Legends requires deep synergy, game-state interpretation, and team coordination that may be difficult for AI to master at top competitive levels. Yiliang “Doublelift” Peng was similarly skeptical, publicly stating he doubted Grok could beat T1, or even himself, and jokingly promised to shave his head if Grok managed to win.
T1, however, embraced the proposal, responding with a GIF of Faker and the message “We are ready,” signaling their willingness to participate. Riot Games itself also reacted, with co-founder Marc Merrill replying to Musk with “let’s discuss.” Needless to say, it appears that Riot Games in onboard with the idea.
Though no match has been confirmed, interest from players, teams, and Riot suggests the concept could materialize into a landmark AI-versus-human matchup, potentially becoming one of the most viewed League of Legends events in history. The fact that Grok 5 will be constrained to human limits would definitely add an interesting dimension to the matchup, as it could truly demonstrate how human-like the large language model could be like in real-time scenarios.
Tesla has passed a key milestone, and it was one that CEO Elon Musk initially mentioned more than nine years ago when he published Master Plan, Part Deux.
As per Tesla China in a post on its official Weibo account, the company’s Autopilot system has accumulated over 10 billion kilometers of real-world driving experience.
Tesla China’s subtle, but huge announcement
In its Weibo post, Tesla China announced that the company’s Autopilot system has accumulated 10 billion kilometers of driving experience. “In this respect, Tesla vehicles equipped with Autopilot technology can be considered to have the world’s most experienced and seasoned driver.”
Tesla AI’s handle on Weibo also highlighted a key advantage of the company’s self-driving system. “It will never drive under the influence of alcohol, be distracted, or be fatigued,” the team wrote. “We believe that advancements in Autopilot technology will save more lives.”
Tesla China did not clarify exactly what it meant by “Autopilot” in its Weibo post, though the company’s intense focus on FSD over the past years suggests that the term includes miles that were driven by FSD (Beta) and Full Self-Driving (Supervised). Either way, 10 billion cumulative miles of real-world data is something that few, if any, competitors could compete with.
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Elon Musk’s 10-billion-km estimate, way back in 2016
When Elon Musk published Master Plan Part Deux, he outlined his vision for the company’s autonomous driving system. At the time, Autopilot was still very new, though Musk was already envisioning how the system could get regulatory approval worldwide. He estimated that worldwide regulatory approval will probably require around 10 billion miles of real-world driving data, which was an impossible-sounding amount at the time.
“Even once the software is highly refined and far better than the average human driver, there will still be a significant time gap, varying widely by jurisdiction, before true self-driving is approved by regulators. We expect that worldwide regulatory approval will require something on the order of 6 billion miles (10 billion km). Current fleet learning is happening at just over 3 million miles (5 million km) per day,” Musk wrote.
It’s quite interesting but Tesla is indeed getting regulatory approval for FSD (Supervised) at a steady pace today, at a time when 10 billion miles of data has been achieved. The system has been active in the United States and has since been rolled out to other countries such as Australia, New Zealand, China, and, more recently, South Korea. Expectations are high that Tesla could secure FSD approval in Europe sometime next year as well.
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Elon Musk’s Boring Company reveals Prufrock TBM’s most disruptive feature
As it turns out, the tunneling startup, similar to other Elon Musk-backed ventures, is also dead serious about pursuing reusability.
The Boring Company has quietly revealed one of its tunnel boring machines’ (TBMs) most underrated feature. As it turns out, the tunneling startup, similar to other Elon Musk-backed ventures, is also dead serious about pursuing reusability.
Prufrock 5 leaves the factory
The Boring Company is arguably the quietest venture currently backed by Elon Musk, inspiring far fewer headlines than his other, more high-profile companies such as Tesla, SpaceX, and xAI. Still, the Boring Company’s mission is ambitious, as it is a company designed to solve the problem of congestion in cities.
To accomplish this, the Boring Company would need to develop tunnel boring machines that could dig incredibly quickly. To this end, the startup has designed Prufrock, an all-electric TBM that’s designed to eventually be fast enough as an everyday garden snail. Among TBMs, such a speed would be revolutionary.
The startup has taken a step towards this recently, when The Boring Company posted a photo of Prufrock-5 coming out of its Bastrop, Texas facility. “On a rainy day in Bastrop, Prufrock-5 has left the factory. Will begin tunneling by December 1. Hoping for a step function increase in speed,” the Boring Company wrote.
Prufrock’s quiet disruption
Interestingly enough, the Boring Company also mentioned a key feature of its Prufrock machines that makes them significantly more sustainable and reusable than conventional TBMs. As per a user on X, standard tunnel boring machines are often left underground at the conclusion of a project because retrieving them is usually more expensive and impractical than abandoning them in the location.
As per the Boring Company, however, this is not the case for its Prufrock machines, as they are retrieved, upgraded, and deployed again with improvements. “All Prufrocks are reused, usually with upgrades between launches. Prufrock-1 has now dug six tunnels,” the Boring Company wrote in its reply on X.
The Boring Company’s reply is quite exciting as it suggests that the TBMs from the tunneling startup could eventually be as reusable as SpaceX’s boosters. This is on brand for an Elon Musk-backed venture, of course, though the Boring Company’s disruption is a bit more underground.
Tesla finishes its biggest Supercharger ever with 168 stalls
Elon Musk proposes Grok 5 vs world’s best League of Legends team match
