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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 Cybercab production begins: The end of car ownership as we know it?
While this could unlock unprecedented mobility abundance — cheaper rides, reduced congestion, freed-up urban space, and massive environmental gains — it risks massive job displacement in ride-hailing, taxi services, and related sectors, forcing society to confront whether the benefits of AI-driven autonomy will outweigh the human costs.
The first Tesla Cybercab rolled off of production lines at Gigafactory Texas yesterday, and it is more than just a simple manufacturing milestone for the company — it’s the opening salvo in a profound economic transformation.
Priced at under $30,000 with volume production slated for April, the steering-wheel-free, pedal-less Robotaxi-geared vehicle promises to make personal car ownership optional for many, slashing transportation costs to as little as $0.20 per mile through shared fleets and high utilization.
Credit: wudapig/Reddit< /a>
While this could unlock unprecedented mobility abundance — cheaper rides, reduced congestion, freed-up urban space, and massive environmental gains — it risks massive job displacement in ride-hailing, taxi services, and related sectors, forcing society to confront whether the benefits of AI-driven autonomy will outweigh the human costs.
Let’s examine the positives and negatives of what the Cybercab could mean for passenger transportation and vehicle ownership as we know it.
The Promise – A Radical Shift in Transportation Economics
Tesla has geared every portion of the Cybercab to be cheaper and more efficient. Even its design — a compact, two-seater, optimized for fleets and ride-sharing, the development of inductive charging, around 300 miles of range on a small battery, half the parts of the Model 3, and revolutionary “unboxed” manufacturing — is all geared toward rapid production.
Operating at a fraction of what today’s rideshare prices are, the Cybercab enables on-demand autonomy for a variety of people in a variety of situations.
Tesla ups Robotaxi fare price to another comical figure with service area expansion
It could also be the way people escape expensive and risky car ownership. Buying a vehicle requires expensive monthly commitments, including insurance and a payment if financed. It also immediately depreciates.
However, Cybercab could unlock potential profitability for owning a car by adding it to the Robotaxi network, enabling passive income. Cities could have parking lots repurposed into parks or housing, and emissions would drop as shared electric vehicles would outnumber gas cars (in time).
The first step of Tesla’s massive production efforts for the Cybercab could lead to millions of units annually, turning transportation into a utility like electricity — always available, cheap, and safe.
The Dark Side – Job Losses and Industry Upheaval
With Robotaxi and Cybercab, they present the same negatives as broadening AI — there’s a direct threat to the economy.
Uber, Lyft, and traditional taxis will rely on human drivers. Robotaxi will eliminate that labor cost, potentially displacing millions of jobs globally. In the U.S. alone, ride-hailing accounts for billions of miles of travel each year.
There are also potential ripple effects, as suppliers, mechanics, insurance adjusters, and even public transit could see reduced demand as shared autonomy grows. Past automation waves show job creation lags behind destruction, especially for lower-skilled workers.
Gig workers, like those who are seeking flexible income, face the brunt of this. Displaced drivers may struggle to retrain amid broader AI job shifts, as 2025 estimates bring between 50,000 and 300,000 layoffs tied to artificial intelligence.
It could also bring major changes to the overall competitive landscape. While Waymo and Uber have partnered, Tesla’s scale and lower costs could trigger a price war, squeezing incumbents and accelerating consolidation.
Balancing Act – Who Wins and Who Loses
There are two sides to this story, as there are with every other one.
The winners are consumers, Tesla investors, cities, and the environment. Consumers will see lower costs and safer mobility, while potentially alleviating themselves of awkward small talk in ride-sharing applications, a bigger complaint than one might think.
Elon Musk confirms Tesla Cybercab pricing and consumer release date
Tesla investors will be obvious winners, as the launch of self-driving rideshare programs on the company’s behalf will likely swell the company’s valuation and increase its share price.
Cities will have less traffic and parking needs, giving more room for housing or retail needs. Meanwhile, the environment will benefit from fewer tailpipes and more efficient fleets.
A Call for Thoughtful Transition
The Cybercab’s production debut forces us to weigh innovation against equity.
If Tesla delivers on its timeline and autonomy proves reliable, it could herald an era of abundant, affordable mobility that redefines urban life. But without proactive policies — retraining, safety nets, phased deployment — this revolution risks widening inequality and leaving millions behind.
Elon on the MKBHD bet, stating “Yes” to the question of whether Tesla would sell a Cybercab for $30k or less to a customer before 2027 https://t.co/sfTwSDXLUN
— TESLARATI (@Teslarati) February 17, 2026
The real question isn’t whether the Cybercab will disrupt — it’s already starting — it’s whether society is prepared for the economic earthquake it unleashes.
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Tesla Model 3 wins Edmunds’ Best EV of 2026 award
The publication rated the Model 3 at an 8.1 out of 10, and with its most recent upgrades and changes, Edmunds says, “This is the best Model 3 yet.”
The Tesla Model 3 has won Edmunds‘ Top Rated Electric Car of 2026 award, beating out several other highly-rated and exceptional EV offerings from various manufacturers.
This is the second consecutive year the Model 3 beat out other cars like the Model Y, Audi A6 Sportback E-tron, and the BMW i5.
The car, which is Tesla’s second-best-selling vehicle behind the popular Model Y crossover, has been in the company’s lineup for nearly a decade. It offers essentially everything consumers could want from an EV, including range, a quality interior, performance, and Tesla’s Full Self-Driving suite, which is one of the best in the world.
The Tesla Model 3 has won Edmunds Top EV of 2026:
“The Tesla Model 3 might be the best value electric car you can buy, combining an Edmunds Rating of 8.1 out of 10, a starting price of $43,880, and an Edmunds-tested range of 338 miles. This is the best Model 3 yet. It is… pic.twitter.com/ARFh24nnDX
— TESLARATI (@Teslarati) February 18, 2026
The publication rated the Model 3 at an 8.1 out of 10, and with its most recent upgrades and changes, Edmunds says, “This is the best Model 3 yet.”
In its Top Rated EVs piece on its website, it said about the Model 3:
“The Tesla Model 3 might be the best value electric car you can buy, combining an Edmunds Rating of 8.1 out of 10, a starting price of $43,880, and an Edmunds-tested range of 338 miles. This is the best Model 3 yet. It is impressively well-rounded thanks to improved build quality, ride comfort, and a compelling combination of efficiency, performance, and value.”
Additionally, Jonathan Elfalan, Edmunds’ Director of Vehicle Testing, said:
“The Model 3 offers just about the perfect combination of everything — speed, range, comfort, space, tech, accessibility, and convenience. It’s a no-brainer if you want a sensible EV.”
The Model 3 is the perfect balance of performance and practicality. With the numerous advantages that an EV offers, the Model 3 also comes in at an affordable $36,990 for its Rear-Wheel Drive trim level.
Elon Musk
Elon Musk’s xAI celebrates nearly 3,000 headcount at Memphis site
The update came in a post from the xAI Memphis account on social media platform X.
xAI has announced that it now employs nearly 3,000 people in Memphis, marking more than two years of local presence in the city amid the company’s supercomputing efforts.
The update came in a post from the xAI Memphis account on social media platform X.
In a post on X, xAI’s Memphis branch stated it has been part of the community for over two years and now employs “almost 3,000 locally to help power Grok.” The post was accompanied by a photo of the xAI Memphis team posing for a rather fun selfie.
“xAI is proud to be a member of the Memphis community for over two years. We now employ almost 3,000 locally to help power @Grok. From electricians to engineers, cooks to construction — we’re grateful for everyone on our team!” the xAI Memphis’ official X account wrote.
xAI’s Memphis facilities are home to Grok’s foundational supercomputing infrastructure, including Colossus, a large-scale AI training cluster designed to support the company’s advanced models. The site, located in South Memphis, was announced in 2024 as the home of one of the world’s largest AI compute facilities.
The first phase of Colossus was built out in record time, reaching its initial 100,000 GPU operational status in just 122 days. Industry experts such as Nvidia CEO Jensen Huang noted that this was significantly faster than the typical 2-to-4-year timeline for similar projects.
xAI chose Memphis for its supercomputing operations because of the city’s central location, skilled workforce, and existing industrial infrastructure, as per the company’s statements about its commitment to the region. The initiative aims to create hundreds of permanent jobs, partner with local businesses, and contribute to economic and educational efforts across the area.
Colossus is intended to support a full training pipeline for Grok and future models, with xAI planning to scale the site to millions of GPUs.
Tesla Cybercab production begins: The end of car ownership as we know it?
Tesla Model 3 wins Edmunds’ Best EV of 2026 award
