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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 issues statement on Starship V3 Booster 18 anomaly

The incident unfolded during gas-system pressure testing at the company’s Massey facility in Starbase, Texas. 

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Credit: SpaceX/X

SpaceX has issued an initial statement about Starship Booster 18’s anomaly early Friday. The incident unfolded during gas-system pressure testing at the company’s Massey facility in Starbase, Texas. 

SpaceX’s initial comment

As per SpaceX in a post on its official account on social media platform X, Booster 18 was undergoing gas system pressure tests when the anomaly happened. Despite the nature of the incident, the company emphasized that no propellant was loaded, no engines were installed, and personnel were kept at a safe distance from the booster, resulting in zero injuries.

“Booster 18 suffered an anomaly during gas system pressure testing that we were conducting in advance of structural proof testing. No propellant was on the vehicle, and engines were not yet installed. The teams need time to investigate before we are confident of the cause. No one was injured as we maintain a safe distance for personnel during this type of testing. The site remains clear and we are working plans to safely reenter the site,” SpaceX wrote in its post on X. 

Incident and aftermath

Livestream footage from LabPadre showed Booster 18’s lower half crumpling around the liquid oxygen tank area at approximately 4:04 a.m. CT. Subsequent images posted by on-site observers revealed extensive deformation across the booster’s lower structure. Needless to say, spaceflight observers have noted that Booster 18 would likely be a complete loss due to its anomaly.

Booster 18 had rolled out only a day earlier and was one of the first vehicles in the Starship V3 program. The V3 series incorporates structural reinforcements and reliability upgrades intended to prepare Starship for rapid-reuse testing and eventual tower-catch operations. Elon Musk has been optimistic about Starship V3, previously noting on X that the spacecraft might be able to complete initial missions to Mars.

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Investor's Corner

Tesla analyst maintains $500 PT, says FSD drives better than humans now

The team also met with Tesla leaders for more than an hour to discuss autonomy, chip development, and upcoming deployment plans.

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Credit: Tesla

Tesla (NASDAQ:TSLA) received fresh support from Piper Sandler this week after analysts toured the Fremont Factory and tested the company’s latest Full Self-Driving software. The firm reaffirmed its $500 price target, stating that FSD V14 delivered a notably smooth robotaxi demonstration and may already perform at levels comparable to, if not better than, average human drivers. 

The team also met with Tesla leaders for more than an hour to discuss autonomy, chip development, and upcoming deployment plans.

Analysts highlight autonomy progress

During more than 75 minutes of focused discussions, analysts reportedly focused on FSD v14’s updates. Piper Sandler’s team pointed to meaningful strides in perception, object handling, and overall ride smoothness during the robotaxi demo.

The visit also included discussions on updates to Tesla’s in-house chip initiatives, its Optimus program, and the growth of the company’s battery storage business. Analysts noted that Tesla continues refining cost structures and capital expenditure expectations, which are key elements in future margin recovery, as noted in a Yahoo Finance report. 

Analyst Alexander Potter noted that “we think FSD is a truly impressive product that is (probably) already better at driving than the average American.” This conclusion was strengthened by what he described as a “flawless robotaxi ride to the hotel.”

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Street targets diverge on TSLA

While Piper Sandler stands by its $500 target, it is not the highest estimate on the Street. Wedbush, for one, has a $600 per share price target for TSLA stock.

Other institutions have also weighed in on TSLA stock as of late. HSBC reiterated a Reduce rating with a $131 target, citing a gap between earnings fundamentals and the company’s market value. By contrast, TD Cowen maintained a Buy rating and a $509 target, pointing to strong autonomous driving demonstrations in Austin and the pace of software-driven improvements. 

Stifel analysts also lifted their price target for Tesla to $508 per share over the company’s ongoing robotaxi and FSD programs. 

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SpaceX Starship Version 3 booster crumples in early testing

Photos of the incident’s aftermath suggest that Booster 18 will likely be retired.

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Credit: SpaceX/X

SpaceX’s new Starship first-stage booster, Booster 18, suffered major damage early Friday during its first round of testing in Starbase, Texas, just one day after rolling out of the factory. 

Based on videos of the incident, the lower section of the rocket booster appeared to crumple during a pressurization test. Photos of the incident’s aftermath suggest that Booster 18 will likely be retired. 

Booster test failure

SpaceX began structural and propellant-system verification tests on Booster 18 Thursday night at the Massey’s Test Site, only a few miles from Starbase’s production facilities, as noted in an Ars Technica report. At 4:04 a.m. CT on Friday, a livestream from LabPadre Space captured the booster’s lower half experiencing a sudden destructive event around its liquid oxygen tank section. Post-incident images, shared on X by @StarshipGazer, showed notable deformation in the booster’s lower structure.

Neither SpaceX nor Elon Musk had commented as of Friday morning, but the vehicle’s condition suggests it is likely a complete loss. This is quite unfortunate, as Booster 18 is already part of the Starship V3 program, which includes design fixes and upgrades intended to improve reliability. While SpaceX maintains a rather rapid Starship production line in Starbase, Booster 18 was generally expected to validate the improvements implemented in the V3 program.

Tight deadlines

SpaceX needs Starship boosters and upper stages to begin demonstrating rapid reuse, tower catches, and early operational Starlink missions over the next two years. More critically, NASA’s Artemis program depends on an on-orbit refueling test in the second half of 2026, a requirement for the vehicle’s expected crewed lunar landing around 2028.

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While SpaceX is known for diagnosing failures quickly and returning to testing at unmatched speed, losing the newest-generation booster at the very start of its campaign highlights the immense challenge involved in scaling Starship into a reliable, high-cadence launch system. SpaceX, however, is known for getting things done quickly, so it would not be a surprise if the company manages to figure out what happened to Booster 18 in the near future.

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