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

[Credit: Google DeepMind]

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8 years ago

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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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Investor's Corner

Lucid denies rumors of bankruptcy after over 40% stock drop

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4 hours ago

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July 14, 2026

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Credit: Lucid

Electric vehicle maker Lucid Group has denied rumors of an imminent bankruptcy after a report from this morning sent the stock on a dramatic drop on Wall Street, seeing losses of more than 40 percent during trading hours.

Lucid’s Director of Communications, Nick Twork, responded to the report from Eletric-Vehicles.com, which stated the company’s restructuring advisor, AlixPartners, was asked to review two decisions: taking Lucid shares private or filing for Chapter 11 bankruptcy protection.

The report also claims AlixPartners told the Lucid board to “concentrate on Gravity production while improving its quality, and to temporarily hold back the Lucid Air, the sedan that has defined the company since its launch.”

Twork said:

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Shares rebounded after the response to the report, halving its losses as the trading day neared 3 p.m. Eastern.

Lucid has struggled to get its sales off the ground and into more respectable numbers, but the company is in its early years, when things are hard to begin with. It is also backed by several notable investors, including the Saudi Public Investment Fund (PIF), which has nearly limitless money and likely would not ditch an investment of this size so soon.

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Lucid shares were down just 14 percent at the time of publication, a far cry from the 55 percent its losses topped out at during the day.

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Tesla owner attempts resale of Model S Signature Edition for over $260k

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8 hours ago

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July 14, 2026

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Credit: Tesla

A Tesla owner who purchased a Model S Signature Edition, one of the final 250 units of the all-electric flagship vehicle that the company discontinued earlier this year, is attempting to sell the car despite a no-resale clause that prohibits reselling for the first year.

The car is being sold by J&S Autohaus in Ewing, New Jersey, and is priced at $260,490, well above the $159,420 that Tesla sold it for earlier this year.

To those who do not know, the Model S Signature was a highly exclusive, limited-run farewell variant of the Model S Plaid that was produced this year to mark the end of production of both the Model S and Model X, Tesla’s two flagship vehicles.

Limited to just 250 units with invite-only sales, it serves as a collector’s item celebrating the legacy of the Model S, which helped pioneer Tesla’s electric vehicle success since its 2012 launch.

It bundles top-tier performance with bespoke cosmetic and luxury upgrades, plus Tesla’s Luxe Package. Here’s what the Model S Signature has over the typical Model S Plaid:

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  • Exclusive Exterior – Unique Garnet Red Paint, matching door handles, gold Tesla “T” badges upfront, gold Plaid and Signature badging at the rear.
  • Premium Interior – White Alcantara upholstery with gold piping/accents, gold Plaid seat badges, Signature-marked door sills, individually numbered dashboard plaque, gold puddle lights, special interior lighting sequence, and a custom Signature key fob.
  • Performance Upgrades – Carbon-ceramic brakes with gold calipers
  • Bundled Luxe Package – Full Self-Driving (Supervised), four years of Premium Connectivity, free lifetime Supercharging
  • Performance Metrics – ~1,020 horsepower, sub-2-second 0-60 MPH, ~390-mile range

Tesla quickly introduced a No Resale Agreement for the Signature Editions of the Model S and Model X, which would penalize the seller for “the amount of $50,000 or the value received as consideration for the sale or transfer, whichever is greater.”

The company continues:

“If you sell or otherwise transfer the ownership of your Model S or Model X, the remainder of the Recommended Maintenance, Wheel and Tire Protection Plan, and Windshield Protection Plan will transfer automatically to the buyer. The Full Self-Driving (Supervised), Free Supercharging and Premium Connectivity will not transfer with the vehicle and will terminate once the ownership of the Model S or Model X is transferred.”

Tesla will likely come after the seller, especially as it has been about two months since Tesla launched deliveries.

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Tesla Full Self-Driving v14.3.5 Early Impressions: new features and early performance

Published

11 hours ago

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July 14, 2026

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Credit: TESLARATI

Tesla rolled out Full Self-Driving (Supervised) v14.3.5 yesterday, and about fifty miles of driving on the new version has given me enough time to highlight what seems to be strong about the release and what is not.

Additionally, Tesla has added a few new features with this specific update, which we’ll highlight as well.

Tesla Full Self-Driving v14.3.5 Performance

The new update is business as usual. Things seem to be running completely normal and necessary, but there are a few things that we’ve seemed to pick up on based on our own experience with v14.3.5, as well as what other users are seeing.

Initially, it seems to be more aware of its surroundings, making moves that are incredibly courteous to other drives and operating just a tad more reserved than what the suite might have done previously.

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We had two instances where it showed this, the first being FSD needing to pass a Flagger Force vehicle that was placing down signage for the day. Their work truck was right at the front corner of a right-hand turn; typically where most cars travel when they take that turn.

FSD v14.3.5 recognized this, slowed down, and took the turn wide with no issues:

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Additionally, v14.3.5 backed up for a semi truck that was making a wide turn onto a road my car was on. This is not new, but it seemed to be backing up for courtesy; it didn’t seem completely necessary, but it might have put some peace of mind in the truck driver’s head:

X user Mike P, also a Pennsylvania native like myself, shared three clips of his Tesla running v14.3.5 performing similar maneuvers. He said:

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“FSD turns right into a small alley that only fits one car at a time, sees oncoming car, reverses out of alley to make space, realizes oncoming car is actually parking, re-enters alley.”

Check it out here:

It seems like Speed Profiles are still in need of some tweaking; I am adjusting what Speed Profile I’m in frequently, constantly changing it to get it to travel at the correct speed. This was an issue for me on v14.3.4. It seems like they’re just a little inconsistent.

Terrible Parking

Parking attempts on v14.3.5 were not good. There are quite a few people who have said this:

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David Moss, the Tesla owner who has taken multiple coast-to-coast drives without any interventions, also has had some issues with parking early on with v14.3.5:

New Features

Tesla has added the ability to open Camera Preview at any time. Previously, it was only available in Park. Here’s what that feature looks like in action:

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Check back later this week for a longer review of what we’ve noticed on Full Self-Driving v14.3.5.

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