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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.

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. 

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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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NASA taps SpaceX for more astronaut missions as Boeing Starliner remains grounded

NASA just gave SpaceX a $946 million contract for three more astronaut missions through 2030.

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NASA has awarded SpaceX a $946 million contract modification covering three more astronaut missions to the International Space Station, according to an announcement the agency published Friday. The award adds Crew-15, Crew-16, and Crew-17 to SpaceX’s existing Commercial Crew Transportation Capability contract, bringing the agreement’s total value to $5.92 billion across 17 flights.

SpaceX confirmed the award on X, writing that it was excited for Falcon 9 and Dragon to launch NASA’s Crew-15, 16, and 17 missions to the Space Station from Florida. The new missions cover ground, launch, in orbit, and return operations, along with cargo transport and a lifeboat capability while docked at the station, and the period of performance runs through 2030.

The award follows a notice of intent NASA issued in May, when the agency first signaled it would purchase up to six additional post certification missions from SpaceX. Teslarati covered that filing at the time, noting NASA cited technical issues and schedule delays encountered by Boeing as a driving factor. Friday’s contract modification locks in three of those six missions, with the remaining three left open for NASA to award later, potentially to Boeing if Starliner clears certification.

Boeing’s CST-100 Starliner has still not flown an operational crew rotation mission for NASA. The spacecraft’s most recent crewed test flight in 2024 ended without the astronauts returning aboard Starliner, and the company has spent the time since working through thruster problems. SpaceX President Gwynne Shotwell said this week that SpaceX is not retiring Crew Dragon today, for sure, while stopping short of committing to fly it past 2030.

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Crew-12 is currently docked at the space station, and NASA has said Crew-13 is targeting a launch in the coming weeks. The newly awarded Crew-15 through Crew-17 missions extend SpaceX’s role as NASA’s primary way of getting astronauts to and from orbit well into the back half of the decade, regardless of what happens with Starliner or Starship in the meantime.

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New drone video shows Tesla’s Optimus Factory reaching a turning point

New drone footage shows Tesla’s dedicated Optimus factory steel frame nearing completion at Giga Texas.

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Tesla’s dedicated Optimus factory at Gigafactory Texas is closing in on a finished steel frame, according to drone footage posted Thursday afternoon by longtime site observer Joe Tegtmeyer. In the video, Tegtmeyer said structural steel assembly is now about five column grids away from reaching the building’s north perimeter beam, putting the primary skeleton in its final stretch roughly six months after Tesla broke ground on the North Campus site in late March.

Tegtmeyer’s footage shows concrete already going in on three upper floors while crews continue laying rebar and pouring grade beam footings at ground level. That kind of parallel work, steel rising at one end of the site while concrete sets at the other, is a scheduling approach Tesla used at the original Giga Texas building and appears to be repeating here to save time before the plant’s targeted 2027 production start.

Teslarati has tracked the building’s progress since Tesla confirmed construction was officially underway in May, when the first steel structure went up on what was then bare, reclaimed land. The facility is part of a more than 5.2 million square foot expansion of Giga Texas’s North Campus that Tesla has said will eventually run nearly the length of the existing vehicle factory, over 4,000 feet, while sitting somewhat narrower. Musk has pegged the long term output target at 10 million Optimus units a year once the line is running at full capacity, a volume that would dwarf the one million unit pilot line Tesla is standing up separately at its Fremont, California factory.

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Tesla Giga Texas to feature massive Optimus V4 production line

The Texas facility sits alongside another major buildout on the same campus. Terafab, the joint Tesla and SpaceX chip fabrication plant that will eventually supply the silicon running Optimus units in the field. Housing robot assembly and chip production on the same grounds is a deliberate supply chain decision, cutting down on the shipping and lead time that would otherwise sit between the two.

Tesla has not given an updated timeline beyond its previously stated goal of bringing high volume Optimus production online at the site in the summer of 2027. Fremont’s smaller pilot line began mass producing the current Gen 3 robot in January, with that plant expected to build tens of thousands of units this year primarily to generate the real world data Tesla needs to refine the robot’s software before Giga Texas ramps up. Six months of visible construction progress, tracked almost entirely through Tegtmeyer’s recurring drone flights, gives the clearest outside look yet at how seriously Tesla is treating that 2027 deadline.

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Tesla and SpaceX take “Terafab” Trademark fight to Federal Court

Tesla and SpaceX sue a small Illinois firm after cease and desist letters over Terafab.

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SpaceX Terafab rendering

Tesla and SpaceX are asking a federal judge to rule that their planned Terafab chip factory does not infringe a small Illinois company’s trademark, a request that arrives only after months of quiet negotiation broke down this summer.

The dispute traces to May 18, when Tesla filed three U.S. trademark applications for “Terafab” and “Tesla Terafab,” covering semiconductor chips and related chip making services. TERA-print LLC, a nanotechnology company that has held a federal trademark for “Tera-Fab” since 2021, responded five days later with a cease and desist letter. According to the lawsuit, first reported by Reuters, TERA-print argued that Tesla and SpaceX’s use of “Terafab” would confuse consumers familiar with its own trademark, which covers a desktop photolithography printer sold to researchers for sensor and bioengineering work.

What stands out in the filing is the timing of TERA-print’s own paperwork. One day before sending that cease and desist letter, on May 22, TERA-print applied to expand its existing registration to cover semiconductor materials, silicon chips, nanoelectronic devices and AI design services, categories it had not previously claimed. Tesla and SpaceX call that filing opportunistic in their complaint, noting it arrived two months after Tesla’s public Terafab announcement and just days after Tesla’s own trademark applications went in.

Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry

By June 10, TERA-print was threatening to sue for federal trademark infringement, false designation of origin and unfair competition, the complaint states. Rather than wait to be sued, Tesla, SpaceX and SpaceXAI met with TERA-print six separate times between June and August trying to resolve the dispute directly. Those talks collapsed, and the companies filed for declaratory judgment this week in the U.S. District Court for the Western District of Texas, asking a judge to find that “Terafab” does not infringe TERA-print’s mark before TERA-print can file a claim of its own.

TERA-print isn’t backing down. The company told PCMag it discussed a settlement with Tesla as recently as September 2 and feels misled by what it called Tesla’s professed interest in settling. Its CTO, Andrey Ivankin, said TERA-print holds a Defense Department contract to fabricate semiconductors and partially owns Mattiq Inc., an AI company built on TERA-print’s products, and that the company will vigorously defend its rights.

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Tesla and SpaceX argue the overlap is superficial. Terafab is planned as a $16.8 billion complex spanning roughly 100 million square feet at the Grimes County site SpaceX confirmed last month, built to produce chips for Optimus robots, Tesla’s AI computing needs and SpaceX’s orbital data center ambitions, a scale and purpose the companies say no reasonable consumer would confuse with a tabletop lab printer. TERA-print’s product line has stayed focused on lithography tools for biological and sensor research since it registered its mark in 2021.

The trademark fight is the second legal dispute tied to the Terafab project in the past week, following a separate SpaceX suit aimed at keeping company records about the facility out of public view, as KBTX reported. Whether construction proceeds under the Terafab name now depends on a federal judge in Austin.

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