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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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SpaceX’s Starship V3 is almost ready and it will change space travel forever

SpaceX is targeting April for the debut test launch of Starship V3 “Version 3”

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SpaceX is closing in on one of the most anticipated rocket launches in history, as the company readies for a planned April test launch and debut of its next-gen Starship V3 “Version 3”.

The latest iteration of Starship V3 has a slightly taller Super Heavy booster and Starship upper stage than their predecessors, and produce stronger, more efficient thrust using SpaceX’s upgraded Raptor 3 engines. V3 also features increased propellant capacity, targeting a total payload capacity of over 100 tons to low Earth orbit, compared to around 35 tons for its predecessor. With Musk’s lifelong aspiration to colonize Mars one day, the increased payload capacity matters enormously, because Mars missions require moving massive amounts of cargo, fuel, and eventually, people. But the most critical upgrade may be orbital refueling. SpaceX’s entire deep space architecture depends on moving large amounts of propellant in space, and having orbital refueling capabilities turn Starship from just a rocket into a true transport system. Without it, neither the Moon nor Mars is reachable at scale.

A fully reusable Starship and Super Heavy, SpaceX aims to drive marginal launch costs down and at a tenfold reduction compared to current market leaders. To put that in perspective, getting a kilogram of cargo to orbit today costs thousands of dollars. Bring that number down far enough and space stops being an exclusive domain. That price point unlocks mass deployment of satellite constellations, large-scale science payloads, and affordable human transport beyond Earth orbit. It also means the Moon stops being a destination we visit and starts being one we inhabit.

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Elon Musk pivots SpaceX plans to Moon base before Mars

NASA expects Starship to take off for the Moon’s South Pole in 2028, with the ultimate goal of establishing a permanently crewed science station there. A successful V3 flight this spring keeps that timeline alive.  As for Mars, Musk has shifted focus toward building a self-sustaining city on the Moon first, arguing that the Moon can be reached every 10 days versus Mars’s 26-month alignment window. Mars remains the horizon, but the Moon is the proving ground.

Elon Musk hasn’t been shy with hyping the upcoming Starship V3 launch. In a social media post on Wednesday, he confirmed the first V3 flight is getting closer to launch. SpaceX also announced its initial activation campaign for V3 and Starbase Pad 2 was complete, wrapping up several days of cryogenic fuel testing on a V3 vehicle for the first time. The countdown is on. April can’t come soon enough.

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Tesla Cybertruck gets long-awaited safety feature

Tesla has announced the rollout of its innovative anti-dooring protection feature to the Cybertruck via the 2026.8 software update.

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Credit: Tesla Asia | X

Tesla is rolling out a new and long-awaited feature to the Cybertruck all-electric pickup, and it is a safety addition geared toward pedestrian and cyclist safety, as well as accidents with other vehicles.

Tesla has announced the rollout of its innovative anti-dooring protection feature to the Cybertruck via the 2026.8 software update.

This safety enhancement uses the vehicle’s existing cameras to detect approaching cyclists, pedestrians, or vehicles in the blind spot while parked. Upon attempting to open a door, if a hazard is detected, the system activates: the blind spot indicator light flashes, an audible chime sounds, and the door will not open on the initial button press.

Drivers must wait briefly and press the button again to override, providing crucial seconds to avoid an accident.

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The feature, also known as Blind Spot Warning While Parked, comes standard on every new Model 3 and Model Y, and is now extending to the Cybertruck. Leveraging Tesla’s vision-based system without requiring new hardware, it represents a cost-effective software solution that builds on community suggestions dating back to 2018.

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This technology addresses the persistent danger of “dooring,” where a driver opens a car door into the path of a passing cyclist or pedestrian.

Tesla implemented this little-known feature to make its cars even safer

Dooring incidents are alarmingly common in urban environments.

According to Chicago data, in 2011 alone, there were 344 reported dooring crashes, accounting for approximately 20 percent of all bicycle crashes in the city, nearly one incident per day.

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While numbers have fluctuated (dropping to 11 percent in 2014 before rising again), dooring consistently represents 10-20 percent of bike-related crashes in major cities.

A national analysis of emergency department data estimates over 17,000 dooring-related injuries treated in the U.S. over a decade, with many involving fractures, contusions, and head trauma, particularly affecting upper extremities.

By automatically intervening, Tesla’s system not only protects vulnerable road users but also safeguards its owners from potential liability and enhances overall road safety.

As cities promote cycling for sustainable transport, features like this demonstrate how advanced driver assistance and camera systems can evolve beyond highway driving to everyday urban scenarios.

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Enthusiastic responses on social media highlight appreciation for the proactive safety measure, with some calling for broader rollout to older models where hardware permits. Tesla continues to push the boundaries of vehicle safety through over-the-air updates, making its fleet smarter and safer over time.

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Tesla Roadster is ‘sorcery and magic’ and might be worth the wait, Uber founder says

Perhaps the wait will be worth it, especially according to Uber founder Travis Kalanick, who recently teased the Roadster’s potential capabilities based on what he has heard from internal Tesla sources.

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tesla roadster
Credit: Praveen Joseph/Twitter

Tesla is planning to unveil the Roadster in late April after years of waiting. But the wait might be worth it, according to Travis Kalanick, the founder of Uber, who recently shed some light on his expectations for the all-electric supercar.

We all know the Roadster is supposed to have some serious capability. CEO Elon Musk has said on numerous occasions that the Roadster will be unlike anything else ever produced. It might go from 0-60 MPH in about a second, it might hover, it might have SpaceX cold gas thrusters.

However, the constant delays in the Roadster program and its unveiling event continue to send Tesla fans into confusion because they’re just not sure when, or if, they’ll ever see the finished product.

Perhaps the wait will be worth it, especially according to Uber founder Travis Kalanick, who recently teased the Roadster’s potential capabilities based on what he has heard from internal Tesla sources.

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Kalanick said on X:

Musk has said this vehicle is not going to be geared for safety, and that, “If safety is your number one goal, do not buy the Roadster.”

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There has been so much hype regarding the Roadster that it is hard to believe the company could not come through on some kind of crazy features for the vehicle.

Elon Musk just dropped a huge detail on the Tesla Roadster

However, the latest delay that Tesla put on the unveiling event is definitely eye-opening, especially considering it is the latest in a series of pushbacks the company has put on the vehicle for the past several years.

Tesla has made several jumps in the Roadster project over the past few months, as it has ramped up hiring for the vehicle and also applied for a patent for a new seat design.

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The car has been a back-burner project for Tesla, as it has been focusing primarily on autonomy and the rollout of Robotaxi and Cybercab. Additionally, its other vehicle projects, like the Model 3 and Model Y refreshes, took precedence.

Tesla still plans to unveil the Roadster next month, so we can hope the company can stick to this timeframe.

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