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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.
Tesla has revealed plans through permit submissions for a massive Robotaxi charging hub in Austin, Texas.
Tesla plans to build the Supercharger hub in multiple phases, with the second phase potentially introducing wireless induction charging, something the company has been developing for the Robotaxi fleet.
Initially, 48 Tesla Robotaxi-geared Superchargers will be built on a lot just across from the St. Elmo, Texas, Service Center. There are about 80 additional spots that will not be impacted by phase 1 of the construction process.
Filings show that the second phase of the project will turn those 80 additional spots into wireless charging for Robotaxi, but it might be an error. The Key Notes state that item 3 is listed as “V4 Charging Cabinet to Support 80 Wireless Chargers in Phase 2. However, the drawings point to V3 Cabinets that are already tied to Superchargers:
There are roughly 128 total spots in the lot, but it is unclear if they will all be used for charging based on what appears to be some sort of typo in the blueprint.
A new Robotaxi fleet charging hub is coming soon to Austin, Texas!!
Permits have been filed for the installation of 48 (V3) stalls in a vehicle storage lot across the road from Tesla’s St Elmo service center. pic.twitter.com/xwRgSWDqht
— MarcoRP (@MarcoRPi1) August 18, 2026
This is among the first Robotaxi charging hubs Tesla has started to develop, as it currently has four others planned throughout various areas: one in Phoenix, one in San Antonio, another in Irving, which will serve the Dallas-Fort Worth area, and another in Las Vegas.
These projects are necessary as Tesla expands its Robotaxi program. Now that preparations have started for the public launch of Cybercab, Robotaxi will likely be expanding aggressively, especially over the next two to three years.
Last night, The Information reported that Tesla was planning to launch Cybercab as soon as the end of August. Hours later, Tesla then announced it was launching a competition for fans to potentially ride in Cybercab during its first public rides.
Tesla’s plan to expand its charging infrastructure in the regions where Robotaxi will initially operate is great preparation for the expanding service. There is still a lot to do, including launching the Cybercab on time.
Tesla got its largest order for the all-electric Class 8 Semi yet, a 500-unit order from Einride AB, a Swedish trucking company.
Einride made the announcement this morning following its second-quarter earnings call. The company said it plans to use 500 Tesla Semi units on its fleet intelligence platform, called Saga AI. The deployments will serve large companies like Amazon and will extend Einride’s electric freight network across logistics routes in California, New Jersey, Texas, Illinois, and Georgia.
🚨 Tesla has received a MASSIVE order from Swedish freight company Einride AB, which placed an order for 500 Tesla Semi trucks
Tesla’s biggest order for the Semi yet! pic.twitter.com/PrtLp5yzvh
— TESLARATI (@Teslarati) August 18, 2026
The deployment is being carried out in several phases over the next two years as Tesla ramps production of the Semi at its dedicated production facility in Sparks, Nevada. Einride will receive its first Semi units in September.
Saga AI
Saga AI is Einride’s dedicated fleet intelligence platform. It enables scaled adoption of electric trucks for freight use and allows shippers to integrate electric capacity without the operational burden or capital risks of managing a fleet. This helps integrate cost-efficient logistics and makes budgeting and forecasting much more accurate.
Tesla Semi’s Adoption
The Tesla Semi is now gathering large-scale clients past those who have helped the company operate a Pilot Program to gain initial information and feedback from real-world drivers.
Perhaps the biggest and most notable is that of Frito-Lay and PepsiCo., who have worked with Tesla for the past several years to dial in the finer details of the truck, including its efficiency and operation-related components.
Tesla Semi gets strange-but-understandable comparison from Jay Leno
There has been tremendous progress in that time, and it even catalyzed Tesla to make some design changes, which were unveiled earlier this year.
But Einride CEO Roozbeh Charli says his company’s partnership with Tesla will continue to push those things forward:
“This deployment is yet another proof point that we can execute at the scale our customers demand. Working closely with Tesla to bring next-generation Semis into active operations quickly and at scale is a testament to the strength of that partnership, and how quickly this technology is maturing from promise to daily operations.”
Additionally, Dan Priestley, the Director of the Semi Program at Tesla, said the partnership is ideal due to Einride’s focus on sustainable transport:
“Einride is at the forefront of sustainable freight, and we are thrilled to deepen our relationship with them through this order of 500 Semis. EV heavy trucks provide lower costs per mile from fuel savings, reduced maintenance, and better uptime over diesel trucks. These savings increase further through operational efficiency when deploying EV trucks at scale, and we are excited that Einride recognizes this and look forward to supporting their deployments.”
Elon Musk
India tells Elon Musk’s X to “Follow the Law” in latest censorship update
Elon Musk says X now exposes government censorship, but India’s secrecy laws complicate that promise.
Elon Musk’s promise to make government censorship requests on X “clearly visible” is running into a wall in India, where the law forbids the very disclosure Musk is promising.
On August 15, Musk responded to an update from X’s open-source algorithm team by writing “Any censorship required by governments is now clearly visible.” The claim referred to a change X pushed two days earlier to its public xai-org/x-algorithm repository, which now includes a controversial filter written directly into the code. The filter suppresses posts from 665 accounts flagged by Brazil’s Superior Electoral Court from appearing in the For You feed of any viewer located in Brazil, unless the viewer already follows the account. The election tied to the filter is scheduled for October 4.
India’s government wasn’t as impressed, and responded on Monday that “X will have to follow the law of the land,” in response to Musk’s transparency push covered by the Times of India. The problem is structural rather than political. India issues content blocking orders under Section 69A of its IT Act, and Rule 16 of the accompanying 2009 Blocking Rules requires those orders to stay confidential. Publishing an India equivalent of the Brazil filter, naming specific accounts and citing specific government orders, would itself violate Indian law. Government use of Section 69A has grown from roughly 6,000 orders a year between 2018 and 2023 to about 24,300 in 2025, according to a Tech Times report.
The contrast puts Musk’s transparency pledge in an odd spot. It works largely as advertised in Brazil, where electoral law requires disclosure and X can point to specific account IDs and a specific court order in public code. It cannot work the same way in India, where the law requires the opposite. X users in India will keep seeing content disappear from search and their feeds without any public accounting of why, even as X tells the rest of the world that its censorship compliance is now inspectable.
This isn’t the first time X’s fights with a national government have shaped how the platform operates. Brazil’s Supreme Court ordered X to suspend the accounts of sitting lawmakers and journalists in 2024, a standoff that cost X its Brazilian revenue for months and froze Starlink’s local accounts before the investigation into Musk and X was closed in March with no evidence of wrongdoing found. X also sued California over a state law requiring moderation disclosures, arguing the mandate itself violated the First Amendment.
Whether India’s government pursues anything beyond a public statement remains to be seen. For now, the mismatch between what X can legally publish and what different governments legally allow it to publish is the real story behind Musk’s seven word claim.
Tesla reveals plans for Robotaxi charging hub in Austin
Tesla Semi gets its largest order yet
