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.
News
Tesla FSD (Supervised) fleet passes 8.4 billion cumulative miles
The figure appears on Tesla’s official safety page, which tracks performance data for FSD (Supervised) and other safety technologies.
Tesla’s Full Self-Driving (Supervised) system has now surpassed 8.4 billion cumulative miles.
The figure appears on Tesla’s official safety page, which tracks performance data for FSD (Supervised) and other safety technologies.
Tesla has long emphasized that large-scale real-world data is central to improving its neural network-based approach to autonomy. Each mile driven with FSD (Supervised) engaged contributes additional edge cases and scenario training for the system.
The milestone also brings Tesla closer to a benchmark previously outlined by CEO Elon Musk. Musk has stated that roughly 10 billion miles of training data may be needed to achieve safe unsupervised self-driving at scale, citing the “long tail” of rare but complex driving situations that must be learned through experience.
The growth curve of FSD Supervised’s cumulative miles over the past five years has been notable.
As noted in data shared by Tesla watcher Sawyer Merritt, annual FSD (Supervised) miles have increased from roughly 6 million in 2021 to 80 million in 2022, 670 million in 2023, 2.25 billion in 2024, and 4.25 billion in 2025. In just the first 50 days of 2026, Tesla owners logged another 1 billion miles.
At the current pace, the fleet is trending towards hitting about 10 billion FSD Supervised miles this year. The increase has been driven by Tesla’s growing vehicle fleet, periodic free trials, and expanding Robotaxi operations, among others.
With the fleet now past 8.4 billion cumulative miles, Tesla’s supervised system is approaching that threshold, even as regulatory approval for fully unsupervised deployment remains subject to further validation and oversight.
Elon Musk
Elon Musk fires back after Wikipedia co-founder claims neutrality and dubs Grokipedia “ridiculous”
Musk’s response to Wales’ comments, which were posted on social media platform X, was short and direct: “Famous last words.”
Elon Musk fired back at Wikipedia co-founder Jimmy Wales after the longtime online encyclopedia leader dismissed xAI’s new AI-powered alternative, Grokipedia, as a “ridiculous” idea that is bound to fail.
Musk’s response to Wales’ comments, which were posted on social media platform X, was short and direct: “Famous last words.”
Wales made the comments while answering questions about Wikipedia’s neutrality. According to Wales, Wikipedia prides itself on neutrality.
“One of our core values at Wikipedia is neutrality. A neutral point of view is non-negotiable. It’s in the community, unquestioned… The idea that we’ve become somehow ‘Wokepidea’ is just not true,” Wales said.
When asked about potential competition from Grokipedia, Wales downplayed the situation. “There is no competition. I don’t know if anyone uses Grokipedia. I think it is a ridiculous idea that will never work,” Wales wrote.
After Grokipedia went live, Larry Sanger, also a co-founder of Wikipedia, wrote on X that his initial impression of the AI-powered Wikipedia alternative was “very OK.”
“My initial impression, looking at my own article and poking around here and there, is that Grokipedia is very OK. The jury’s still out as to whether it’s actually better than Wikipedia. But at this point I would have to say ‘maybe!’” Sanger stated.
Musk responded to Sanger’s assessment by saying it was “accurate.” In a separate post, he added that even in its V0.1 form, Grokipedia was already better than Wikipedia.
During a past appearance on the Tucker Carlson Show, Sanger argued that Wikipedia has drifted from its original vision, citing concerns about how its “Reliable sources/Perennial sources” framework categorizes publications by perceived credibility. As per Sanger, Wikipedia’s “Reliable sources/Perennial sources” list leans heavily left, with conservative publications getting effectively blacklisted in favor of their more liberal counterparts.
As of writing, Grokipedia has reportedly surpassed 80% of English Wikipedia’s article count.
News
Tesla Sweden appeals after grid company refuses to restore existing Supercharger due to union strike
The charging site was previously functioning before it was temporarily disconnected in April last year for electrical safety reasons.
Tesla Sweden is seeking regulatory intervention after a Swedish power grid company refused to reconnect an already operational Supercharger station in Åre due to ongoing union sympathy actions.
The charging site was previously functioning before it was temporarily disconnected in April last year for electrical safety reasons. A temporary construction power cabinet supplying the station had fallen over, described by Tesla as occurring “under unclear circumstances.” The power was then cut at the request of Tesla’s installation contractor to allow safe repair work.
While the safety issue was resolved, the station has not been brought back online. Stefan Sedin, CEO of Jämtkraft elnät, told Dagens Arbete (DA) that power will not be restored to the existing Supercharger station as long as the electric vehicle maker’s union issues are ongoing.
“One of our installers noticed that the construction power had been backed up and was on the ground. We asked Tesla to fix the system, and their installation company in turn asked us to cut the power so that they could do the work safely.
“When everything was restored, the question arose: ‘Wait a minute, can we reconnect the station to the electricity grid? Or what does the notice actually say?’ We consulted with our employer organization, who were clear that as long as sympathy measures are in place, we cannot reconnect this facility,” Sedin said.
The union’s sympathy actions, which began in March 2024, apply to work involving “planning, preparation, new connections, grid expansion, service, maintenance and repairs” of Tesla’s charging infrastructure in Sweden.
Tesla Sweden has argued that reconnecting an existing facility is not equivalent to establishing a new grid connection. In a filing to the Swedish Energy Market Inspectorate, the company stated that reconnecting the installation “is therefore not covered by the sympathy measures and cannot therefore constitute a reason for not reconnecting the facility to the electricity grid.”
Sedin, for his part, noted that Tesla’s issue with the Supercharger is quite unique. And while Jämtkraft elnät itself has no issue with Tesla, its actions are based on the unions’ sympathy measures against the electric vehicle maker.
“This is absolutely the first time that I have been involved in matters relating to union conflicts or sympathy measures. That is why we have relied entirely on the assessment of our employer organization. This is not something that we have made any decisions about ourselves at all.
“It is not that Jämtkraft elnät has a conflict with Tesla, but our actions are based on these sympathy measures. Should it turn out that we have made an incorrect assessment, we will correct ourselves. It is no more difficult than that for us,” the executive said.
Tesla FSD (Supervised) fleet passes 8.4 billion cumulative miles
Elon Musk fires back after Wikipedia co-founder claims neutrality and dubs Grokipedia “ridiculous”
