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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 recently received its largest order for the all-electric Semi from Einride, a Swedish transport service, for 500 units, a groundbreaking invoice to receive before the first deliveries begin.
Even more remarkable, Einride CEO Roozbeh Charli said in a recent interview that he expects his company to take delivery of all 500 — the entire order — before the end of 2027. He even expects to have 75 Tesla Semi units in the Einride fleet before the end of this year.
🚨 Einride CEO Roozbeh Charli on the Tesla Semi partnership:
“If we start with the Amazon announcement that we did earlier this year, that was on the back of having gone through a proving period together with them and proving out our technology. Then we took that next step in… pic.twitter.com/oazkXjwoig
— TESLARATI (@Teslarati) August 28, 2026
Charli said the Tesla partnership was part of a broader push, along with its earlier partnership with Amazon. Einride is assisting Amazon with the use of its Saga AI platform, which helps eliminate questions about budgeting and forecasting for logistics companies.
The Semi, as well as Tesla’s production and subsequent delivery of the units to Einride, will help the company “to have a good supply of vehicles that we can deploy on the [Saga AI] platform,” Charli said. “Tesla is also a relationship we’ve had for a while, and as the Tesla Semi deliveries are firming up, we decided to do a larger commitment to that and deploy that on our platform.”
In its initial announcement, Einride said it anticipated taking delivery of the trucks over the next two years, but now it appears the company is expecting all 500 units within the next 16 months.
Built at a dedicated factory in Sparks, Nevada, the Tesla Semi has been perhaps the biggest and most intensive testing process the company has ever had for a single vehicle model. For the past several years, Tesla has been working with many companies, most notably Frito-Lay and PepsiCo, to gain knowledge on the performance on regional routes.
Tesla plans to launch the Semi officially on September 24, five months after production started ramping.
Additionally, drivers have said they are happy about the Semi’s performance and that its numerous safety and productivity features have made their jobs and routes much easier.
Tesla Cybercab is using a unique strategy for picking up the correct rider, which is a crucial part of ride-hailing to ensure people end up in the right place and are charged the correct price.
Cybercab will utilize an RGB strip in its front light bar that will illuminate in a variety of different colors to mark itself.
This identifying mark will also appear in the Robotaxi app, giving riders in the same location a notable distinction in an effort to avoid any confusion regarding who should get in each vehicle.
🚨 Tesla is using different light bar colors to help riders understand which vehicle is theirs
Pretty cool strategy pic.twitter.com/eGMpEMeRpc
— TESLARATI (@Teslarati) August 27, 2026
Other ride-hailing services use similar strategies: Lyft and Uber rides are recognizable through driver identity, vehicle type and color, as well as license plate. Waymo will display the rider’s initials on top of the vehicle, letting them know that the specific vehicle for them has arrived.
Tesla’s strategy is unique and interesting, but there are some flaws. Cybercab’s main purpose is aimed toward being an autonomous ride for all, including those who have disabilities like being blind or even color blind.
Tesla will likely have something in the pipeline for those who cannot see colors or have limited vision. There will definitely be multiple ways to identify which vehicle is the one that “you” specifically ordered.
Cybercab is set to start giving public rides next Thursday, September 3, in Austin, as it announced a dedicated event last week and invited many members of the Tesla community.
Additionally, members of the public will be invited as well. Tesla has been offering employee rides in Cybercab for nearly two months.
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Tesla has said goodbye to one customization option for its vehicles: the wrap service it launched several years ago.
After launching an in-house wrap service in August 2020 for the first time in China. In the U.S., it launched in October 2023. Tesla continued to expand the program and adjust it with better pricing and fewer options for the Cybertruck.
By December 2023, it was giving owners of the Model 3, Model Y, and the Cybertruck the opportunity to give their vehicle a fresh look with a vinyl wrap.
Tesla revamps in-house vinyl wrap service with better pricing
It was only available in five locations: Costa Mesa, Oceanside, Santa Clara, West Covina, all in California, and Seattle, Washington.
However, Tesla made some big adjustments to its shop, and the wrap service is officially gone:
Tesla has made a LOT of changes to its online shop recently — price increases, price cuts, new options, and several products being removed entirely.
Some of the biggest increases are wheel covers. 👀
📈 PRICE INCREASES
• 2017-2023 | Model 3 Aero Wheel Cover — Style: Refresh…— Phoenix Self-Driving 🐦🔥 (@PhoenixFSD) August 25, 2026
Wraps are very popular across the Tesla lineup, especially since the company offers relatively few colors. Many choose to wrap their Teslas with interesting colors, patterns, or even finishes, turning their cars from glossy to satin or matte.
However, Tesla’s wrap service was so limited geographically that it never really had a chance to get off the ground or compete with local shops. Every area in the United States is now overflowing with detailing shops, mobile detailers, and other automotive specialists, many of whom perform wrap services.
Tesla’s service was confined to the Pacific time zone and only spanned across two states. It was never going to be something Tesla was a major competitor in, nor was it going to disrupt the wrapping industry. Now that the program has ended, it seems pretty ideal to believe it was always going to be a short-term thing.
Along with the wrap service, Tesla removed several other products, but nothing too crazy. The Model 3 Door Pocket and Cupholder Liners, the Model S 19″ Magnetite Wheel and Winter Tire Package, Model X/Y Ski/Snowboard Carrier for Hitch Rack, Tesla’s Electric Summer Party Tee, and the Electric Summer Tee were the other items the company totally eliminated from its online shop.
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