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Google’s DeepMind unit develops AI that predicts 3D layouts from partial images

[Credit: Google DeepMind]

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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.

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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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Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Tesla influencers argue company’s polarizing Full Self-Driving transfer decision

Tesla maintains it will honor transfers for orders with initial delivery windows before the deadline and offers full deposit refunds otherwise, citing longstanding fine print that the program is “subject to change at any time.”

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Tesla’s decision to tighten its Full Self-Driving (FSD) transfer promotion has ignited fierce debate among owners and enthusiasts.

The company quietly updated its terms in late February 2026, changing the eligibility from “order by March 31, 2026” to “take delivery by March 31, 2026.”

What began as a flexible incentive to boost sales, allowing buyers to transfer their paid FSD (Supervised) to a new vehicle, now excludes many, particularly Cybertruck owners facing delivery delays into summer or later.

Tesla maintains it will honor transfers for orders with initial delivery windows before the deadline and offers full deposit refunds otherwise, citing longstanding fine print that the program is “subject to change at any time.”

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The reversal has polarized the Tesla community, with accusations of a “bait-and-switch” clashing against defenses of corporate pragmatism. Many owners who placed orders under the original wording feel betrayed, especially as production backlogs and new unsupervised FSD rollout complicate timelines.

However, Tesla has allowed them to cancel their orders and receive a refund.

Critics of the decision argue that the change disadvantages loyal customers who helped fund FSD development, calling it poor communication and a revenue grab as Tesla pivots toward subscriptions.

Popular influencers have amplified the divide. Whole Mars Catalog struck a measured but firm tone, acknowledging the original “order by” language but emphasizing Tesla’s right to adjust terms. He has continued to defend Tesla in this particular issue:

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He criticized extreme backlash as “dramatization” and “spoiled kids,” noting the unsupervised FSD era and broader sales challenges make blanket transfers financially risky. Whole Mars advocated for polite outreach to CEO Elon Musk over the issue.

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In a contrasting perspective, Dirty TesLA voiced sharper frustration, posting that blocking transfers feels “crazy” and distancing himself from “people that want to worship a corporation and say they can do no wrong.” His stance resonated with owners who view the policy flip as disrespectful to early adopters.

Popular Tesla influencer Sawyer Merritt captured the frustration felt by thousands. In a widely shared thread viewed over 700,000 times, Merritt detailed how pre-change Cybertruck orders now risk losing FSD eligibility unless their initial delivery window falls before March 31.

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The controversy underscores deeper tensions—between Tesla’s need for revenue discipline and owners’ expectations of goodwill. As FSD evolves toward unsupervised capability, the community remains split: some see the change as necessary business, others as a broken promise. Whether Tesla reconsiders under pressure or holds firm remains to be seen, but it does not appear they are planning to budge.

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Tesla Semi’s latest adoptee will likely encourage more of the same

Public visibility matters. When shoppers see a trusted name like Ralph’s running clean, high-tech trucks on public roads, skepticism fades. Competitors such as Albertsons, which pre-ordered Semis years ago, and other chains chasing ESG targets now have proof that electric autonomy works in real-world grocery fleets.

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Credit: X | ChargePozitive

The latest adoptee of the Tesla Semi will likely encourage more businesses in the same realm to adopt the all-electric Class 8 truck, as a new company utilizing the Semi has been spotted in Southern California.

A sleek, futuristic Tesla Semi truck branded for Ralph’s Supermarkets was spotted cruising a Los Angeles highway in a viral 13-second dashcam video posted March 2, by X user ChargePozitive.

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This sighting confirms Kroger’s March 2025 partnership with Tesla to deploy up to 500 autonomous electric Semis.

While the initial announcement targeted Midwest supply chains, the California appearance under the Ralph’s banner shows the program expanding to Kroger’s West Coast operations. Ralph’s, a staple for millions of Southern California shoppers, is now hauling groceries with the Semi, which has zero tailpipe emissions and claims up to 500 miles of range per charge.

Tesla Semi pricing revealed after company uncovers trim levels

The timing could not be better for sustainable logistics. Traditional trucking accounts for a massive share of retail emissions, but Tesla’s Semi slashes fuel and maintenance costs while leveraging full autonomy to ease driver shortages and improve safety.

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Tesla’s expanding Megacharger network, including new sites along major freight corridors and partnerships like the recently-announced one with Pilot Travel Centers, is removing range anxiety and making nationwide scaling realistic. There’s still a long way to go, but things are moving in the right direction.

Public visibility matters. When shoppers see a trusted name like Ralph’s running clean, high-tech trucks on public roads, skepticism fades. Competitors such as Albertsons, which pre-ordered Semis years ago, and other chains chasing ESG targets now have proof that electric autonomy works in real-world grocery fleets.

PepsiCo’s successful pilots already demonstrated viability, and Ralph’s sighting adds retail credibility.

As Tesla ramps high-volume Semi production through 2026, this isn’t an isolated curiosity. Instead, it’s a catalyst. More grocers adopting the platform will accelerate industry-wide decarbonization, cut operating expenses, and deliver tangible environmental wins.

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The future of sustainable supply chains is already on the highway, and Ralph’s just made it impossible to ignore.

Moving forward, Tesla hopes to expand the Semi program into other regions, including Europe, which CEO Elon Musk recently said is a total possibility next year.

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Tesla ramps Cybercab test manufacturing ahead of mass production

Tesla still has plans for volume production, which remains between four and eight weeks away, aligning with Musk’s statements that early ramps would be deliberately measured given the Cybercab’s novel architecture and full reliance on Tesla’s vision-based Full Self-Driving technology.

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Credit: Joe Tegtmeyer | X

Tesla is seemingly ramping Cybercab test manufacturing ahead of mass production, which is scheduled to begin next month, the company said.

At Tesla’s Gigafactory Texas, production of the Cybercab, the company’s groundbreaking purpose-built Robotaxi vehicle, is accelerating markedly. Drone footage from Joe Tegtmeyer captured striking aerial footage today, revealing what appears to be the largest public sighting of Cyebrcabs to date.

A total of 25 units were observed by Tegtmeyer across the Gigafactory Texas property, marking a clear step-up in testing and validation activities as Tesla prepares for a broader output.

Tesla Cybercab production begins: The end of car ownership as we know it?

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In the footage, 14 metallic gold Cybercabs were parked in a tight formation outside the factory exit, showcasing their sleek, autonomous-only design with no steering wheels, pedals, or traditional controls. Another 9 units sat at the crash testing facility, likely undergoing structural and safety validations, while two more appeared at the west end-of-line area for final checks.

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Tegtmeyer noted additional Cybercabs driving around the complex, hinting at active movement and real-world testing beyond static parking.

This surge follows the first production Cybercab rolling off the line in mid-February 2026, several weeks ahead of the originally anticipated April start.

That milestone, celebrated by Tesla employees and confirmed by CEO Elon Musk, kicked off low-volume builds on the dedicated “unboxed” manufacturing line, a modular process designed to slash costs, reduce factory footprint, and enable faster assembly compared to conventional methods.

Industry observers interpret the jump to dozens of visible units in early March as evidence that Tesla has transitioned into higher-volume test manufacturing.

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Tesla still has plans for volume production, which remains between four and eight weeks away, aligning with Musk’s statements that early ramps would be deliberately measured given the Cybercab’s novel architecture and full reliance on Tesla’s vision-based Full Self-Driving technology.

The Cybercab, envisioned as a sub-$30,000 autonomous two-seater for robotaxi fleets, represents Tesla’s bold pivot toward scalable autonomy and robotics.

Tesla fans and enthusiasts on X praised the imagery, with many expressing excitement over the visible progress toward deployment. While challenges remain, including software maturity, regulatory hurdles, and supply chain scaling, the increased factory activity underscores Tesla’s momentum in turning the Cybercab vision into reality.

As Giga Texas continues expanding and refining the manufacturing process of the Cybercab, the coming months will prove to be a pivotal time in determining how quickly this revolutionary vehicle reaches roads in the U.S. and internationally.

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