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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.
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Tesla ships out update that brings massive change to two big features
“This change only updates the name of certain features and text in your vehicle,” the company wrote in Release Notes for the update, “and does not change the way your features behave.”
Tesla has shipped out an update for its vehicles that was caused specifically by a California lawsuit that threatened the company’s ability to sell cars because of how it named its driver assistance suite.
Tesla shipped out Software Update 2026.2.9 starting last week; we received it already, and it only brings a few minor changes, mostly related to how things are referenced.
“This change only updates the name of certain features and text in your vehicle,” the company wrote in Release Notes for the update, “and does not change the way your features behave.”
The following changes came to Tesla vehicles in the update:
- Navigate on Autopilot has now been renamed to Navigate on Autosteer
- FSD Computer has been renamed to AI Computer
Tesla faced a 30-day sales suspension in California after the state’s Department of Motor Vehicles stated the company had to come into compliance regarding the marketing of its automated driving features.
The agency confirmed on February 18 that it had taken a “corrective action” to resolve the issue. That corrective action was renaming certain parts of its ADAS.
Tesla discontinued its standalone Autopilot offering in January and ramped up the marketing of Full Self-Driving Supervised. Tesla had said on X that the issue with naming “was a ‘consumer protection’ order about the use of the term ‘Autopilot’ in a case where not one single customer came forward to say there’s a problem.”
This was a “consumer protection” order about the use of the term “Autopilot” in a case where not one single customer came forward to say there’s a problem.
Sales in California will continue uninterrupted.
— Tesla North America (@tesla_na) December 17, 2025
It is now compliant with the wishes of the California DMV, and we’re all dealing with it now.
This was the first primary dispute over the terminology of Full Self-Driving, but it has undergone some scrutiny at the federal level, as some government officials have claimed the suite has “deceptive” names. Previous Transportation Secretary Pete Buttigieg was one of those federal-level employees who had an issue with the names “Autopilot” and “Full Self-Driving.”
Tesla sued the California DMV over the ruling last week.
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Tesla workers push back against Giga Berlin unionization
“IG Metall did not succeed in Giga Berlin‘s works council election earlier today. The union share was reduced from nearly 40% in 2024 to 31% in 2026! This is a clear message by the Giga Berlin team towards an independent co-determination! The list called Giga United, led by the current chairwoman, Michaela Schmitz, received the most votes with more than 40%! Good news for Giga Berlin!”
Tesla workers pushed back against unionization efforts at Gigafactory Berlin, and over the past few years, there has been a dramatic decrease in interest to unionize at the German plant.
Gigafactory Berlin Plant Manager André Thierig announced on Wednesday that IG Metall, the European union group, saw its share reduce from 40 to 31 percent in 2026 as employees eligible to vote on the issue. Instead, the Giga Berlin team, known as Giga United, received the most votes with more than 40 percent.
BREAKING! 🚨
IG Metall did not succeed in Giga Berlin‘s works council election earlier today. The union share was reduced from nearly 40% in 2024 to 31% in 2026!
This is a clear message by theGiga Berlin team towards an independent co-determination!
The list called Giga…
— André Thierig (@AndrThie) March 4, 2026
Thierig gave specific details in a post on X:
“IG Metall did not succeed in Giga Berlin‘s works council election earlier today. The union share was reduced from nearly 40% in 2024 to 31% in 2026! This is a clear message by the Giga Berlin team towards an independent co-determination! The list called Giga United, led by the current chairwoman, Michaela Schmitz, received the most votes with more than 40%! Good news for Giga Berlin!”
There were over 10,700 total employees who were eligible to vote, with 87 percent of them turning out to cast what they wanted. There were three key outcomes: Giga United, IG Metall, and other notable groups, with the most popular being the Polish Initiative.
The 37-seat council remains dominated by non-unionized representatives, preserving Giga Berlin as Germany’s only major auto plant without a collective bargaining agreement.
Thierig and Tesla framed the outcome as employee support for an “independent, flexible, and unbureaucratic” future, enabling acceleration on projects like potential expansions or new models. IG Metall expressed disappointment, accusing management of intimidation tactics and an “unfair” campaign.
The first election of this nature happened back in 2022. In 2024, IG Metall emerged as the largest single faction with 39.4 percent, but non-union lists coalesced for a majority.
But this year was different. There was some extra tension at Giga Berlin this year, as just two weeks ago, an IG Metall rep was accused by Tesla of secretly recording a council meeting. The group countersued for defamation.
Tesla Giga Berlin plant manager faces defamation probe after IG Metall union complaint
This result from the 2026 vote reinforced Tesla’s model of direct employee-management alignment over traditional German union structures, amid ongoing debates about working conditions. IG Metall views it as a setback but continues advocacy. Tesla sees it as validation of its approach in a competitive EV market.
This outcome may influence future labor dynamics at Giga Berlin, including any revival of expansion plans or product lines, which Musk has talked about recently.
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SpaceX President Gwynne Shotwell details xAI power pledge at White House event
The commitment was announced during an event with United States President Donald Trump.
SpaceX President Gwynne Shotwell stated that xAI will develop 1.2 gigawatts of power at its Memphis-area AI supercomputer site as part of the White House’s new “Ratepayer Protection Pledge.”
The commitment was announced during an event with United States President Donald Trump.
During the White House event, Shotwell stated that xAI’s AI data center near Memphis would include a major energy installation designed to support the facility’s power needs.
“As you know, xAI builds huge supercomputers and data centers and we build them fast. Currently, we’re building one on the Tennessee-Mississippi state line. As part of today’s commitment, we will take extensive additional steps to continue to reduce the costs of electricity for our neighbors…
“xAI will therefore commit to develop 1.2 GW of power as our supercomputer’s primary power source. That will be for every additional data center as well. We will expand what is already the largest global Megapack power installation in the world,” Shotwell said.
She added that the system would provide significant backup power capacity.
“The installation will provide enough backup power to power the city of Memphis, and more than sufficient energy to power the town of Southaven, Mississippi where the data center resides. We will build new substations and invest in electrical infrastructure to provide stability to the area’s grid.”
Shotwell also noted that xAI will be supporting the area’s water supply as well.
“We haven’t talked about it yet, but this is actually quite important. We will build state-of-the-art water recycling plants that will protect approximately 4.7 billion gallons of water from the Memphis aquifer each year. And we will employ thousands of American workers from around the city of Memphis on both sides of the TN-MS border,” she noted.
The Ratepayer Protection Pledge was introduced as part of the federal government’s effort to address concerns about rising electricity costs tied to large AI data centers, as noted in an Insider report. Under the agreement, companies developing major AI infrastructure projects committed to covering their own power generation needs and avoiding additional costs for local ratepayers.
Tesla ships out update that brings massive change to two big features
Tesla workers push back against Giga Berlin unionization
