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Google’s DeepMind unit develops AI that predicts 3D layouts from partial images
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.
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.
Elon Musk
Tesla gives the Roadster an official “Go for launch” demonstration date
Tesla teased an October 1 Roadster reveal, reviving years of delayed SpaceX thruster hover promises.
Tesla teased an October 1 event date for its next generation Roadster, posting an image on X Saturday that shows the car lit up like it is sitting on a launch pad, with the date “10.01” stamped across the bottom and the caption “Go for launch.” A countdown clock on Tesla’s Roadster order page now points to the same date, which falls on a Thursday. The company has not said where the event will happen or whether it will be streamed at the moment. Stay with us @Teslarati for live updates.
Go for launch pic.twitter.com/Khu03eiZ04
— Tesla (@Tesla) September 12, 2026
Tesla has since sent formal invitations to reservation holders confirming the event will take place in Waco, Texas, about 90 minutes north of its Austin headquarters, based on a digital ticket shared on X by Sawyer Merritt. Tesla did not name the exact venue, though Waco sits close to SpaceX’s McGregor, Texas, rocket test site, previously reported as the planned location for a Roadster thruster demonstration. The invite sets the reveal for 8:30 p.m. Eastern on October 1, requires RSVPs by midnight on September 16, and limits entry to guests 21 and older. Invitations are non-transferable.
The tease follows nine years of a project defined by unimaginable specs along with slipped dates. Musk first showed the second generation Roadster in November 2017 as a surprise reveal at the end of the Tesla Semi event, promising a 0 to 60 mph time under two seconds, a top speed above 250 mph, 620 miles of range from a 200 kWh battery, and production starting in 2020. At last November’s shareholder meeting, Musk set an April 1 demo date and joked the choice gave him “deniability” if it slipped again, which it did, moving first to late April, then to “a month or so,” then to August.
Tesla Roadster SpaceX Package’s 1.1-second 0-60 mph launch visualized in concept video
Whatever Tesla shows on October 1 is expected to center on the SpaceX developed thruster package Musk has described since 2018. Internally code named A71, a nod to the Lockheed SR-71 Blackbird, the system reportedly uses cold gas thrusters fed by a composite overwrapped pressure vessel, the same tank design SpaceX uses on Falcon 9. Musk has said a thruster equipped Roadster could hit 60 mph in about 1.1 seconds under roughly 2.75 g of launch force, well past the 1.9 second figure quoted for the standard car. That version reportedly will not be street legal and has reportedly been discussed as a limited run sold through a track only program.
The standard Roadster is still expected to carry the original $200,000 base price and $250,000 Founders Series tier, both set when Tesla opened $50,000 and $250,000 reservations in 2017. Tesla VP of Vehicle Engineering Lars Moravy has confirmed production will happen at Gigafactory Texas, with Musk targeting 2027 or 2028, 12 to 18 months after whatever the company demonstrates next month.
Tesla is planning to roll out some pretty significant safety and accident avoidance features with Full Self-Driving version 15, which will be the next major FSD deployment from the company.
Tesla AI lead Ashok Elluswamy used a near-miss this week to preview what the company says is the next leap in Full Self-Driving.
In response to a driver whose car had swerved away from another vehicle pulling out of a parking lot, Elluswamy wrote that he was glad the owner was safe and that “even earlier prediction of hazards, even faster reaction time and overall significantly better safety and collision avoidance” would arrive with FSD v15.
Glad you are safe. Even earlier prediction of hazards, even faster reaction time and overall significantly better safety and collision avoidance coming as part of the next big upgrade (v15).
— Ashok Elluswamy (@aelluswamy) September 11, 2026
The comment landed as Tesla continues to treat software as the primary safety upgrade path. v15 is described internally as a larger architectural step, with a much bigger neural network and tighter coupling between prediction and control.
The company has already begun using early v15 software in some robotaxi operations while rolling out safety features such as Automatic Collision Evasion into current customer cars, allowing the driving stack to intervene even when the driver is in manual control.
Tesla is rolling out a new FSD version with a massive safety addition
Tesla’s published telemetry is the backbone of its safety argument. In recent North American Vehicle Safety Report data, vehicles with FSD (Supervised) engaged traveled roughly 5.1 million to 5.7 million miles between major collisions, defined as airbag-deployment events.
Tesla’s estimate of the U.S. average over the same period is about 699,000 miles per comparable crash. That is the comparison Tesla often frames as roughly seven times fewer major collisions.
A tighter comparison uses the same Tesla fleet. Cars driven manually with active safety features such as automatic emergency braking still recorded a major collision about every 2.1 million miles. Against that baseline, FSD’s advantage shrinks to roughly 2.4 to 2.7 times fewer severe crashes, which independent researchers argue is the more apples-to-apples figure.
European data released in 2026 pointed in the same direction: Tesla reported FSD as 3.5 times safer than manual driving in the Netherlands and 4.1 times fewer collisions than manually driven Teslas with active safety across more than 100 million kilometers in five approved countries.
Those numbers do not settle every debate. NHTSA’s Standing General Order still shows Tesla accounting for the large majority of U.S. Level 2 driver-assist crash reports, in part because the fleet logs far more assisted miles than rivals. Critics also note that Tesla’s “U.S. average” mixes crash definitions and driving mix.
Even so, Tesla’s own same-car comparisons, plus lower rates of automatic emergency braking and harsh maneuvers when FSD is engaged, are the evidence Elluswamy is pointing to when he says v15 will push prediction and collision avoidance further. The claim is not that software already eliminates risk. It is that each major version is meant to widen the gap between the system and an unaided human driver.
Cybertruck
Tesla’s most delayed Cybertruck feature is finally here
Tesla finally links Cybertruck Powershare with Powerwall 3 for extended home backup after years overdue.
Tesla’s Cybertruck can now pair with a Powerwall 3 to keep a house running longer during an outage, a feature the company first promised when the truck launched in November 2023.
The official Cybertruck account posted the update on X Thursday: “Powerwall 3 & I can now power your house together. This extends your home backup by over 3 days, equivalent to 9 additional Powerwalls,” Cybertruck lead engineer Wes Morrill confirmed the rollout separately, calling it the first time a vehicle and a home battery have worked together this way. Powerwall 2 and Powerwall+ compatibility is still coming later this year, per both the Cybertruck account and Morrill.
Powerwall 3 & I can now power your house together⁰ ⁰This extends your home backup by over 3 days, equivalent to 9 additional Powerwalls pic.twitter.com/8G2twIm6AN
— Cybertruck (@cybertruck) September 10, 2026
Powershare itself is not new. Tesla enabled the version that lets Cybertruck power tools, appliances or another EV through its bed outlets when the truck launched in 2023. Home backup through a Powershare Gateway and Universal Wall Connector arrived in 2024, and Tesla extended that support to homes with solar the following year. What has been missing until now is Powershare working alongside an existing Powerwall, instead of functioning as a separate backup source competing for the same job.
The pairing matters because a single Powerwall home battery typically covers a home for about a day, less if usage is heavy or the outage stretches into a heat wave or freeze. A second Powerwall for more backup storage costs several thousand dollars installed. A Cybertruck instead uses a battery the owner already has, one large enough here to add roughly three more days of backup without mounting another unit or booking an installer visit. For households in wildfire, hurricane or winter storm regions where outages run past a day, that keeps the refrigerator and medical equipment running instead of shutting down.
The company told owners in October 2024 that Powerwall integration was coming sometime in 2025. That date passed, and in December 2025 Tesla pushed the target to mid-2026, with Morrill explaining at the time that two grid-forming devices need to negotiate which one manages a home during an outage, and that certifying the process across multiple generations of Powerwall took longer than expected.
For owners who bought Powershare hardware expecting it to work with whatever battery setup they already had, Thursday’s update closes a gap that has shown up repeatedly in owner complaints since Cybertruck deliveries began. Tesla has also rolled out a separate Powershare grid support program in Texas, letting Cybertrucks send power back to the grid during high demand events, so the truck’s role in a home’s energy setup keeps expanding even as individual pieces of it arrive later than promised.
Tesla gives the Roadster an official “Go for launch” demonstration date
Tesla plans big safety improvements for Full Self-Driving v15
