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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.

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.

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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.

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 successfully launches 100th Starlink mission of 2025

With 100 Starlink missions completed for 2025, space enthusiasts have noted that SpaceX has successfully launched 2,554 Starlink satellites so far this year.

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(Credit: Starlink)

SpaceX achieved its 100th Starlink mission of the year on Friday, October 31, marking another milestone for 2025. 

A Falcon 9 rocket carrying 28 Starlink broadband satellites successfully lifted off from Vandenberg Space Force Base in California at 4:41 p.m. ET, carrying another 28 Starlink satellites to Low Earth Orbit (LEO).

Falcon 9 booster’s 29th flight

Roughly 8.5 minutes after liftoff, the Falcon 9’s first stage touched down on the drone ship Of Course I Still Love You in the Pacific Ocean. This marked the booster’s 29th flight, which is approaching SpaceX’s reuse record of 31 missions.

This latest mission adds to SpaceX’s impressive 138 Falcon 9 launches in 2025, 99 of which were dedicated to Starlink, according to Space.com. The company’s focus on reusing boosters has enabled this breakneck pace, with multiple launches each week supporting both Starlink’s expansion and external customers.

Starlink’s network continues massive global expansion

Starlink remains the largest active satellite constellation in history, with more than 10,000 satellites launched, nearly 8,800 of which are currently active. SpaceX recently achieved Starlink’s 10,000-satellite milestone. With 100 Starlink missions completed for 2025, space enthusiasts have noted that SpaceX has successfully launched 2,554 Starlink satellites so far this year.

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Starlink, which provides high-speed, low-latency internet connectivity even to the world’s most remote areas, has been proven to be life-changing technology for people across the globe. The service is currently operational in about 150 countries, and it currently has over 5 million subscribers worldwide. From this number, 2.7 million joined over the past year.

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Tesla shares updated timeframe for Cybertruck FSD V14 release

The Cybertruck was expected to receive FSD V14 before the end of the month, but Tesla was not able to meet the target.

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Credit: Tesla

Tesla’s Full Self-Driving (FSD) V14 update for the Cybertruck could arrive this weekend, as per recent comments from Director of Autopilot Software and VP of AI Ashok Elluswamy. 

The Cybertruck was expected to receive FSD V14 before the end of the month, but Tesla was not able to meet the target.

Cybertruck FSD V14

Considering the extended wait for FSD V14, it was no surprise that several Cybertruck owners were asking for updates about the system’s rollout to the all-electric pickup truck on Friday. These included the official Cybertruck X account, which responded to Elluswamy’s end of month estimate with “I only see trick. Where is my treat.” 

This prompted a response from the AI executive, who replied with, “Sorry, pushing for early access Cyber release over the weekend.” This means that if all goes well, Cybertruck owners would be able to experience FSD V14 very soon. Some, however, are wondering if Tesla would go straight to V14.2 for the Cybertruck’s FSD V14 update, or if the vehicle will receive V14.1 first. 

Tesla pushes to unify FSD experience across its lineup

The upcoming Cybertruck rollout represents the next step in Tesla’s efforts to roll out FSD capabilities across all of its vehicles. FSD V14 is a notable step forward for the company’s AI-driven self driving system, with features like Mad Max mode getting positive reviews from longtime Full Self Driving testers.

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For the Cybertruck, the FSD V14 update would mark one of its first major over-the-air upgrades for the vehicle. Likely due to its size, the Cybertruck tends to receive FSD updates later than the S3XY lineup, which is quite surprising considering that the all-electric pickup truck is a premium-priced vehicle that is home to some of Tesla’s most advanced technologies.

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“Tesla Ride” program lets riders experience FSD and Grok AI in real-world demos

The initiative aims to bring supervised Full Self-Driving demos and Grok AI-guided experiences to consumers in real world trips.

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Credit: Tesla AI/X

Tesla has launched a new service designed to make its Full Self-Driving (FSD) technology familiar to all commuters. 

Dubbed the “Tesla Ride” program, the initiative aims to bring supervised Full Self-Driving demos and Grok AI-guided experiences to consumers in real world trips. 

How Tesla Ride Works

As per the official Tesla Ride website, the session will allow participants to sit in the driver’s seat while a Tesla Advisor rides shotgun as co-pilot. The Tesla Advisor then guides riders through the company’s latest supervised FSD features, comfort settings, and in-car entertainment. Participants would also be able to interact with Grok AI in the vehicles. Grok will be capable of answering questions during the ride, and it will even tell stories along the way.

Tesla noted, however, that Tesla Ride sessions are capped at 45 minutes each, and it requires participants to have a valid driver’s license and insurance. Interested participants are also advised to call beforehand so they can schedule their Tesla Rides.

Marketing push and reach

The Tesla Ride program runs across several markets from October into November, and in some locations into the end of December 2025. Participating states are numerous, from Michigan to Virginia to Illiois, Nevada, and California, among others. A look at the official webpage for Tesla Ride shows that the company is still taking a very cautious approach with the program, with disclaimers clearly stating that FSD Supervised does not make Teslas autonomous just yet.

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Tesla’s focus on safety with FSD was highlighted recently by Senior Vice President for Automotive Tom Zhu. “Elon said it in 2021: “For self-driving, even if the road is painted completely wrong and a UFO lands in the middle of the road, the car still cannot crash and still needs to do the right thing. 

“The prime directive for the autopilot system is: Don’t crash. That really overrides everything. No matter what the lines say or how the road is done, the thing that needs to happen is minimizing the probability of impact while getting you to your destination conveniently and comfortably,” the executive stated.

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