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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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Elon Musk reveals when SpaceX will perform first-ever Starship catch

“Starship catch is probably flight 13 to 15, depending on how well V3 flights go,” Musk said.

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Credit: SpaceX

Elon Musk revealed when SpaceX would perform the first-ever catch attempt of Starship, its massive rocket that will one day take life to other planets.

On Tuesday, Starship aced its tenth test flight as SpaceX was able to complete each of its mission objectives, including a splashdown of the Super Heavy Booster in the Gulf, the deployment of eight Starlink simulators, and another splashdown of the ship in the Indian Ocean.

It was the first launch that featured a payload deployment:

SpaceX Starship Flight 10 was so successful, it’s breaking the anti-Musk narrative

SpaceX was transparent that it would not attempt to catch the Super Heavy Booster, something it has done on three previous occasions: Flight 5 on October 13, 2024, Flight 7 on January 16, and Flight 8 on March 6.

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This time, it was not attempting to do so. However, there are bigger plans for the future, and Musk detailed them in a recent post on X, where he discussed SpaceX’s plans to catch Starship, which would be a monumental accomplishment.

Musk said the most likely opportunities for SpaceX to catch Starship itself would be Flight 13, Flight 14, and Flight 15, but it depends on “how well the V3 flights go.”

The Starship launched with Flight 10 was a V2, which is the same size as the subsequent V3 rocket but has a smaller payload-to-orbit rating and is less powerful in terms of initial thrust and booster thrust. Musk said there is only one more V2 rocket left to launch.

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V3 will be the version flown through 2026, as V4, which will be the most capable Starship build SpaceX manufactures, is likely to be the first company ship to carry humans to space.

Musk said that SpaceX planned to “hopefully” attempt a catch of Starship in 2025. However, it appears that this will likely be pushed back to 2026 due to timing.

SpaceX will take Starship catch one step further very soon, Elon Musk confirms

SpaceX would need to launch the 11th and 12th test flights by the end of the year in order to get to Musk’s expected first catch attempt of Flight 13. It’s not unheard of, but the company will need to accelerate its launch rate as it has only had three test flights this year.

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Tesla Robotaxi rival Waymo confirms massive fleet expansion in Bay Area

New data from the California Public Utilities Commission (CPUC) said Waymo had 1,429 vehicles operating in California, and 875 of them were “associated with a terminal in San Francisco,” according to The SF Examiner.

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Credit: Uber

Tesla Robotaxi rival Waymo has confirmed that it has expanded its fleet of driverless ride-sharing vehicles in the Bay Area of California massively since its last public disclosure.

It is perhaps one of the most important metrics in the race for autonomous supremacy, along with overall service area. Tesla has seemed to focus on the latter, while expanding its fleet slowly to maintain safety.

Waymo, on the other hand, is bringing its fleet size across the country to significant levels. In March, it told The SF Examiner that there were over 300 Waymos in service in the San Francisco area, which was not a significant increase from the 250 vehicles on the road it reported in August 2023.

In May, the company said in a press release that it had more than 1,500 self-driving Waymos operating nationwide. More than 600 were in the San Francisco area.

Tesla analyst compares Robotaxi to Waymo: ‘The contrast was clear’

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However, new data from the California Public Utilities Commission (CPUC) said Waymo had 1,429 vehicles operating in California, and 875 of them were “associated with a terminal in San Francisco,” according to The SF Examiner.

CPUC data from March 2025 indicated that there were a total of 1,087 Waymo vehicles in California, with 762 located in San Francisco. Some were test vehicles, others were deployed to operate as ride-sharing vehicles.

The company’s August update also said that it deploys more than 2,000 commercial vehicles in the United States. That number was 1,500 in May. There are also roughly 400 in Phoenix and 500 in Los Angeles.

While Waymo has done a good job of expanding its fleet, it has also been able to expand its footprint in the various cities it is operating in.

Most recently, it grew its geofence in Austin, Texas, to 90 square miles. This outpaced Tesla for a short period before the company expanded its Robotaxi service area earlier this week to roughly 170 square miles.

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Tesla one-ups Waymo once again with latest Robotaxi expansion in Austin

The two companies have drastically different approaches to self-driving, as Waymo utilizes LiDAR, while Tesla relies solely on cameras for its suite. Tesla CEO Elon Musk has made no mistake about which he believes to be the superior solution to autonomy.

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Tesla launches Full Self-Driving in a new region

Today, Tesla launched Full Self-Driving in Australia for purchase by car buyers for $10,100, according to Aussie automotive blog Man of Many, which tried out the suite earlier this week.

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Credit: Tesla

Tesla has launched its Full Self-Driving suite in a new region, marking a significant step in the company’s progress to expand its driver assistance suite on a global scale.

It is also the first time Tesla has launched FSD in a right-hand-drive market.

Today, Tesla launched Full Self-Driving in Australia for purchase by car buyers for $10,100, according to Aussie automotive blog Man of Many, which tried out the suite earlier this week.

Previously, Basic and Enhanced Autopilot suites were available, but the FSD capability now adds Traffic Light and Stop Sign Control, along with all the features of the previous two Autopilot suites.

It is the first time Tesla has launched the suite by name in a region outside of North America. In China, Tesla has “City Autopilot,” as it was not permitted to use the Full Self-Driving label for regulatory reasons.

However, Tesla still lists Full Self-Driving (Supervised) as available in the U.S., Canada, China, Mexico, and Puerto Rico.

The company teased the launch of the suite in Australia earlier this week, and it appeared to have been released to select media members in the region earlier this week:

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Tesla FSD upcoming Australia release seemingly teased bv media

The rollout of Full Self-Driving in the Australian market will occur in stages, as Model 3 and Model Y vehicles with Hardware 4 will receive the first batch of FSD rollouts in the region.

TechAU also reported that “the initial deployment of FSDs in Australia will roll out to a select number of people outside the company, these people are being invited into Tesla’s Early Access Program.”

Additionally, the company reportedly said it is “very close” to unlocking FSD in customer cars:

Each new Tesla sold will also come with a 30-day free trial of the suite.

Australia is the sixth country to officially have Full Self-Driving available to them, following the United States, Canada, China, Mexico, and Puerto Rico.

Here’s the first look at the suite operating in Australia:

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