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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.
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Tesla developing small, affordable SUV, report claims
This latest rumor deserves heavy scrutiny. Tesla has already walked away from a mass-market $25,000 EV once before.
Tesla is developing a small, affordable SUV, a new report claims, speculating that the automaker is planning to add yet another vehicle to its lineup at a price point similar to the Model 3 and Model Y, but smaller and more compact.
But it does not make a whole lot of sense, especially considering a handful of things CEO Elon Musk said and the overall plan for Tesla’s future.
Reuters reported that Tesla is in the early stages of developing an all-new, smaller, cheaper electric SUV. Citing four sources familiar with the matter, the story claims the vehicle would be shorter than the Model Y, built in China, and represent a fresh platform rather than a variant of the Model 3 or Y.
Suppliers have reportedly been contacted to discuss details, though Tesla has not commented. The move appears aimed at broadening affordability amid slowing EV demand and intensifying competition, particularly from Chinese rivals.
This latest rumor deserves heavy scrutiny. Tesla has already walked away from a mass-market $25,000 EV once before.
In 2024, the company scrapped its long-teased “Redwood” project for a budget-friendly car. Elon Musk explained the decision bluntly during an earnings call: a conventional low-cost model would be “pointless” and “completely at odds with what we believe.”
It’s sort of hard to believe this report: 3/Y are already relatively affordable, Elon said a $25k wouldn’t make sense, consumers want something larger than the Y with X going away, and Musk said what’s coming is “cooler than a minivan.”
Have to think the car is at least an SUV. https://t.co/4CQUV9ZNA5
— TESLARATI (@Teslarati) April 9, 2026
In other words, chasing a bare-bones cheap EV runs counter to Tesla’s core mission of accelerating sustainable energy through cutting-edge technology and autonomy rather than volume-driven price wars.
Musk’s own recent statements reinforce skepticism about a compact SUV pivot. Just two weeks ago, on March 25, he responded to fan requests for a minivan by posting on X: “Something way cooler than a minivan is coming.”
Elon Musk says Tesla is developing a new vehicle: ‘Way cooler than a minivan’
The remark came in the context of family-hauling needs, with Musk highlighting the Cybertruck’s ability to seat multiple child seats. It signals Tesla’s focus is shifting toward more spacious, innovative people-movers—not shrinking its lineup.
U.S. demand data echoes this logic.
The long-wheelbase Model Y L—a six-seat, stretched variant offering extra room for families—has generated massive interest wherever offered. Fans in the U.S. have basically begged for the Model Y L to make its way to the States, or for the company to develop a full-size SUV.
The Model Y L is selling well in China, where it is manufactured.
Delivery wait times for the Model Y L stretched into February 2026 as orders poured in. Tesla recently expanded the trim to eight new Asian markets, yet it remains unavailable in the United States, where consumer appetite for a larger, more practical SUV is reportedly strong.
American buyers have consistently favored bigger vehicles; the Model Y already outsells most competitors precisely because it delivers crossover utility without compromise. A compact model shorter than today’s bestseller would likely miss this mark entirely.
Tesla’s product strategy has long emphasized differentiation through autonomy, range, and desirability rather than racing to the bottom on price. Stripped-down variants of the Model 3 and Y have already struggled to ignite broad demand.
A new compact SUV built in China might sound logical on paper for cost-sensitive buyers, but it risks repeating past missteps—diluting brand cachet while ignoring clear signals from Musk and the market.
History suggests Tesla talks about affordable cars more often than it delivers them. Whether this Reuters scoop evolves into metal or joins the $25k project on the scrap heap remains to be seen.
For now, the smart money is on Tesla doubling down on “way cooler” vehicles that actually fit American families—and Tesla’s ambitious vision—rather than a smaller SUV that feels like yesterday’s news.
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Tesla CEO Elon Musk says next FSD release is the one we’ve been waiting for
On Thursday, Musk teased the capabilities and next steps for Tesla’s Full Self-Driving software, focusing squarely on the incremental improvements of the current v14.3 suite, as well as the looming arrival of v15.
Tesla CEO Elon Musk teased the capabilities of a future Full Self-Driving release, but it seems like we are getting what Yogi Berra once called “Déjà vu all over again.”
On Thursday, Musk teased the capabilities and next steps for Tesla’s Full Self-Driving software, focusing squarely on the incremental improvements of the current v14.3 suite, as well as the looming arrival of v15.
He confirmed that upcoming point releases of v14.3 will deliver additional polish to the current build, smoothing out remaining edges in an already capable system. These iterative updates, Musk noted, are designed to refine performance without requiring a full version overhaul.
Yet the real headline was Musk’s forecast for v15.
“V15 will far exceed human levels of safety, even in completely unsupervised and complex situations,” he wrote.
Tesla V14.3 self-driving review. The point releases will bring polish.
V15 will far exceed human levels of safety, even in completely unsupervised and complex situations. https://t.co/s4UK9RWw9f
— Elon Musk (@elonmusk) April 9, 2026
He clarified that v15 will be powered by Tesla’s long-awaited large model, an AI architecture with roughly 10x the parameters of the smaller model currently in widespread use. The leap, Musk explained, stems from the unusually rapid progress of the compact model, which has advanced so quickly that the larger counterpart has yet to catch up in real-world deployment.
However, it is becoming a pattern that is, by now, familiar to anyone following Tesla’s autonomous driving roadmap.
There’s no debating you on that 🤷
— TESLARATI (@Teslarati) April 9, 2026
Musk has consistently and repeatedly framed each successive major release as the one poised to deliver game-changing autonomy. Earlier versions were similarly positioned as a movement toward the final piece of the puzzle, only for attention to pivot to the next milestone once they arrived.
The refrain has become a recurring feature of FSD communication: current software is impressive, the point releases will sharpen it further, but the true breakthrough lies one major iteration ahead.
Musk’s latest comments fit squarely into that cadence. While v14.3 point releases are expected to tighten supervised driving behaviors in the coming weeks, v15 is cast as the version that finally crosses the threshold into unsupervised operation at human-or-better safety levels across demanding scenarios.
Our rate of advancement with the small model has been so fast that the large model has not yet caught up.
V15 will be the large model.
— Elon Musk (@elonmusk) April 9, 2026
The 10x parameter scale of the underlying large model is presented as the key technical enabler, promising richer reasoning and more robust decision-making than anything deployed to date.
Whether v15 ultimately fulfills that promise remains to be seen. Tesla’s history shows that each new target generates fresh excitement—and occasional skepticism—about timelines.
Fans realize Musk’s timelines for FSD are exciting, but rarely met:
You can see a rift happening in the Tesla bull community between a large group of reasonable people who aren’t afraid to acknowledge the elephants in the room, and those who are essentially bull bots whose entire identities are destroyed if they have to acknowledge any bump in…
— Mike P (@mikepat711) April 9, 2026
For now, Musk’s message is familiar: the immediate focus is polishing v14.3 through targeted point releases, while the 10x-parameter large model in v15 represents the next decisive step toward fully unsupervised, superhuman safety.
Hopefully, Tesla can come through, but we can only believe that once v15 gets here, v16 will be the next big step toward autonomy.
Drivers can expect continued refinement in the short term and a significantly more ambitious leap once the large model is ready. The cycle continues, but the stakes, Musk insists, keep rising.
Elon Musk
Tesla Supercharger for Business exposes jaw-dropping ROI gap between best and worst locations
Tesla’s new Supercharger for Business calculator reveals an eye-opening all-in cost and location-based ROI projections.
Tesla has launched an online calculator for its Supercharger for Business program, giving property owners their first transparent look at what it really costs to install Superchargers on site and what kind of return they can expect.
The program itself launched in September 2025, allowing businesses to purchase and operate Supercharger hardware on their own property while Tesla handles installation, maintenance, software, and 24/7 driver support. As Teslarati reported at launch, hosts also get their logo placed on the chargers and their location integrated into Tesla’s in-car navigation, meaning drivers are actively routed there. The stalls are open to all EVs, not just Teslas.
We launched Supercharger for Business in 2025 to help companies get charging right. We found simplicity and transparency to be a problem in this industry.
We’re now sharing pricing and a financial calculator to help make informed decisions. The goal is to accelerate investments,…
— Tesla Charging (@TeslaCharging) April 8, 2026
The new online calculator, announced by Tesla on Wednesday with the note that “simplicity and transparency” have been a problem in the industry, lets any business enter a U.S. address and get a real cost and revenue model. A standard 8-stall V4 Supercharger site runs approximately $500,000 in hardware and $55,000 per post for installation, bringing an all-in price just shy of $1 million. Tesla charges a flat $0.10 per kWh fee to cover software, billing, and network operations. Businesses set their own retail price and keep the margin above that fee.
Taking a look at Tesla’s Supercharger for Business online calculator, we can see that ROI is not uniform, and the gap between a strong location and a poor one can stretch the breakeven point by several years.
The biggest driver is foot traffic and how long people stay. A busy rest station, hotel, or outlet mall brings in repeat visitors who need to charge while they’re already stopped, pushing utilization numbers higher and shortening payback time.
Local electricity rates matter just as much on the cost side. Markets like California carry some of the highest commercial electricity rates in the country, which eats into the margin between what a host pays per kWh and what they charge drivers. At the same time, dense urban areas with high EV adoption tend to support higher retail charging prices, which can offset that cost if demand is strong enough. Weather also plays a role. Cold climates reduce battery efficiency and increase charging frequency, but they can also suppress utilization in winter months if drivers avoid stopping in exposed outdoor locations. Suburban and rural sites face a different problem: lower baseline EV traffic, which means a site with cheaper power and lower operating costs can still take longer to pay back simply because the stalls sit idle more often. Tesla’s calculator uses real fleet data to pre-fill utilization estimates by ZIP code, so businesses can run their specific address against these variables rather than relying on averages.
The program has seen real adoption. Wawa, already the largest host of Tesla Superchargers with over 2,100 stalls across 223 locations, opened its first fully owned and branded site in Alachua, Florida earlier this year. Francis Energy of Oklahoma and the city of Alpharetta, Georgia have also deployed branded stations through the program, as Teslarati covered in January.
Tesla now exceeds 80,000 Supercharger stalls worldwide, and the calculator makes the economic case for accelerating that number through private investment rather than company-owned sites alone.
