News
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 announced it has hit a major milestone with Full Self-Driving subscriptions, shortly after it said it would exclusively offer the suite without the option to purchase it outright.
Tesla announced on Wednesday during its Q4 Earnings Call for 2025 that it had officially eclipsed the one million subscription mark for its Full Self-Driving suite. This represented a 38 percent increase year-over-year.
This is up from the roughly 800,000 active subscriptions it reported last year. The company has seen significant increases in FSD adoption over the past few years, as in 2021, it reported just 400,000. In 2022, it was up to 500,000 and, one year later, it had eclipsed 600,000.
NEWS: For the first time, Tesla has revealed how many people are subscribed or have purchased FSD (Supervised).
Active FSD Subscriptions:
• 2025: 1.1 million
• 2024: 800K
• 2023: 600K
• 2022: 500K
• 2021: 400K pic.twitter.com/KVtnyANWcs— Sawyer Merritt (@SawyerMerritt) January 28, 2026
In mid-January, CEO Elon Musk announced that the company would transition away from giving the option to purchase the Full Self-Driving suite outright, opting for the subscription program exclusively.
Musk said on X:
“Tesla will stop selling FSD after Feb 14. FSD will only be available as a monthly subscription thereafter.”
The move intends to streamline the Full Self-Driving purchase option, and gives Tesla more control over its revenue, and closes off the ability to buy it outright for a bargain when Musk has said its value could be close to $100,000 when it reaches full autonomy.
It also caters to Musk’s newest compensation package. One tranche requires Tesla to achieve 10 million active FSD subscriptions, and now that it has reached one million, it is already seeing some growth.
The strategy that Tesla will use to achieve this lofty goal is still under wraps. The most ideal solution would be to offer a less expensive version of the suite, which is not likely considering the company is increasing its capabilities, and it is becoming more robust.
Tesla is shifting FSD to a subscription-only model, confirms Elon Musk
Currently, Tesla’s FSD subscription price is $99 per month, but Musk said this price will increase, which seems counterintuitive to its goal of increasing the take rate. With that being said, it will be interesting to see what Tesla does to navigate growth while offering a robust FSD suite.
News
Tesla confirms Robotaxi expansion plans with new cities and aggressive timeline
Tesla plans to launch in Dallas, Houston, Phoenix, Miami, Orlando, Tampa, and Las Vegas. It lists the Bay Area as “Safety Driver,” and Austin as “Ramping Unsupervised.”
Tesla confirmed its intentions to expand the Robotaxi program in the United States with an aggressive timeline that aims to send the ride-hailing service to several large cities very soon.
The Robotaxi program is currently active in Austin, Texas, and the California Bay Area, but Tesla has received some approvals for testing in other areas of the U.S., although it has not launched in those areas quite yet.
However, the time is coming.
During Tesla’s Q4 Earnings Call last night, the company confirmed that it plans to expand the Robotaxi program aggressively, hoping to launch in seven new cities in the first half of the year.
Tesla plans to launch in Dallas, Houston, Phoenix, Miami, Orlando, Tampa, and Las Vegas. It lists the Bay Area as “Safety Driver,” and Austin as “Ramping Unsupervised.”
These details were released in the Earnings Shareholder Deck, which is published shortly before the Earnings Call:
🚨 BREAKING: Tesla plans to launch its Robotaxi service in Dallas, Houston, Phoenix, Miami, Orlando, Tampa, and Las Vegas in the first half of this year pic.twitter.com/aTnruz818v
— TESLARATI (@Teslarati) January 28, 2026
Late last year, Tesla revealed it had planned to launch Robotaxi in Las Vegas, Phoenix, Dallas, and Houston, but Tampa and Orlando were just added to the plans, signaling an even more aggressive expansion than originally planned.
Tesla feels extremely confident in its Robotaxi program, and that has been reiterated many times.
Although skeptics still remain hesitant to believe the prowess Tesla has seemingly proven in its development of an autonomous driving suite, the company has been operating a successful program in Austin and the Bay Area for months.
In fact, it announced it achieved nearly 700,000 paid Robotaxi miles since launching Robotaxi last June.
🚨 Tesla has achieved nearly 700,000 paid Robotaxi miles since launching in June of last year pic.twitter.com/E8ldSW36La
— TESLARATI (@Teslarati) January 28, 2026
With the expansion, Tesla will be able to penetrate more of the ride-sharing market, disrupting the human-operated platforms like Uber and Lyft, which are usually more expensive and are dependent on availability.
Tesla launched driverless rides in Austin last week, but they’ve been few and far between, as the company is certainly easing into the program with a very cautiously optimistic attitude, aiming to prioritize safety.
Investor's Corner
Tesla (TSLA) Q4 and FY 2025 earnings call: The most important points
Executives, including CEO Elon Musk, discussed how the company is positioning itself for growth across vehicles, energy, AI, and robotics despite near-term pressures from tariffs, pricing, and macro conditions.
Tesla’s (NASDAQ:TSLA) Q4 and FY 2025 earnings call highlighted improving margins, record energy performance, expanding autonomy efforts, and a sharp acceleration in AI and robotics investments.
Executives, including CEO Elon Musk, discussed how the company is positioning itself for growth across vehicles, energy, AI, and robotics despite near-term pressures from tariffs, pricing, and macro conditions.
Key takeaways
Tesla reported sequential improvement in automotive gross margins excluding regulatory credits, rising from 15.4% to 17.9%, supported by favorable regional mix effects despite a 16% decline in deliveries. Total gross margin exceeded 20.1%, the highest level in more than two years, even with lower fixed-cost absorption and tariff impacts.
The energy business delivered standout results, with revenue reaching nearly $12.8 billion, up 26.6% year over year. Energy gross profit hit a new quarterly record, driven by strong global demand and high deployments of MegaPack and Powerwall across all regions, as noted in a report from The Motley Fool.
Tesla also stated that paid Full Self-Driving customers have climbed to nearly 1.1 million worldwide, with about 70% having purchased FSD outright. The company has now fully transitioned FSD to a subscription-based sales model, which should create a short-term margin headwind for automotive results.
Free cash flow totaled $1.4 billion for the quarter. Operating expenses rose by $500 million sequentially as well.
Production shifts, robotics, and AI investment
Musk further confirmed that Model S and Model X production is expected to wind down next quarter, and plans are underway to convert Fremont’s S/X line into an Optimus robot factory with a capacity of one million units.
Tesla’s Robotaxi fleet has surpassed 500 vehicles, operating across the Bay Area and Austin, with Musk noting a rapid monthly expansion pace. He also reiterated that CyberCab production is expected to begin in April, following a slow initial S-curve ramp before scaling beyond other vehicle programs.
Looking ahead, Tesla expects its capital expenditures to exceed $20 billion next year, thanks to the company’s operations across its six factories, the expansion of its fleet expansion, and the ramp of its AI compute. Additional investments in AI chips, compute infrastructure, and future in-house semiconductor manufacturing were discussed but are not included in the company’s current CapEx guidance.
More importantly, Tesla ended the year with a larger backlog than in recent years. This is supported by record deliveries in smaller international markets and stronger demand across APAC and EMEA. Energy backlog remains strong globally as well, though Tesla cautioned that margin pressure could emerge from competition, policy uncertainty, and tariffs.
Tesla hits major milestone with Full Self-Driving subscriptions
Tesla confirms Robotaxi expansion plans with new cities and aggressive timeline
