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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 scaled back driver monitoring to be less naggy with the latest version of the Full Self-Driving (Supervised) suite, which is version 14.3.3.
The latest version is already earning praise from owners, who are reporting that the suite is far less invasive when it comes to keeping drivers from taking their eyes off the road. The first to mention it was notable Tesla community member on X known as Zack, or BLKMDL3.
14.3.3 nags less too https://t.co/IuiWzuYO6O
— Elon Musk (@elonmusk) May 18, 2026
Musk confirmed that v14.3.3 was made to nag drivers significantly less, something that Tesla has worked toward in the past and has said with previous versions that it is less likely to push drivers to look ahead, at least after looking away for a few seconds.
This refinement aligns with Tesla’s ongoing push toward unsupervised FSD. The update also brings faster Actual Smart Summon (now up to 8 mph), reliable “Hey Grok” voice commands, richer visualizations, smoother Mad Max acceleration, and an intervention streak counter that rewards consistent use. Reviewers describe the drive as more human-like and confident, with fewer twitches or unnecessary maneuvers.
Musk has repeatedly signaled this direction. In late 2025, he stated that FSD would allow phone use “depending on context of surrounding traffic,” noting safety data would justify relaxing rules so drivers could text in low-risk scenarios like stop-and-go traffic.
We tested this, and even still, the cell phone monitoring really seems to be less active in terms of alerting drivers:
Tesla Full Self-Driving v14.2.1 texting and driving: we tested it
Earlier, ahead of v14, Musk promised the system would “nag the driver much less” once safety metrics improved.
In 2023, he confirmed the steering wheel torque nag would be “gradually reduced, proportionate to improved safety,” shifting reliance to the cabin camera. Subsequent updates like v13.2.9 and v12.4 further loosened monitoring, cracking down on workarounds while easing legitimate distractions.
These steps reflect Tesla’s data-driven approach: FSD’s safety record—reportedly averaging millions of miles per crash—now outpaces human drivers in many scenarios, giving the company confidence to dial back interventions. Reduced nags improve usability and trust, encouraging more drivers to rely on the system rather than disengaging out of frustration.
However, there are certainly still some concerns. In many states, it is illegal to handle a cell phone in any way, requiring the use of hands-free devices. In Pennsylvania, it is illegal to use your cell phone at stop lights, which is definitely a step further than using it while the car is actively in motion.
v14.3.3 represents tangible progress. Making FSD less adversarial and more seamless is definitely a step forward, but drivers need to be aware of the dangers of distracted driving. FSD is extremely capable, but it is in no way fully autonomous, nor does its performance warrant owners to take their attention off the road.
Tesla has officially expanded its Full Self-Driving (FSD) suite in Europe once again, as it will now be offered to customer vehicles in Lithuania, marking a significant milestone as the second European Union country to offer the system.
Tesla confirmed FSD’s rollout in Lithuania this morning:
FSD Supervised now rolling out to Teslas in Lithuania 🇱🇹!
Making European roads safer, one by one pic.twitter.com/Uuj0bNG7pP
— Tesla Europe, Middle East & Africa (@teslaeurope) May 20, 2026
Tesla showed several clips of Full Self-Driving navigation in Lithuania to mark the announcement, while Lithuanian Transport Minister Juras Taminskas highlighted the system’s potential to assist with lane-keeping, speed adjustment, and traffic tasks on longer drives, while emphasizing that drivers must stay alert and ready to intervene.
Just a few weeks ago, Tesla officially entered Europe with Full Self-Driving in the Netherlands. The expansion of FSD on the continent is now officially underway.
Full Self-Driving’s European Journey
Europe has long posed one of the toughest regulatory challenges for Tesla’s autonomy ambitions due to stringent safety standards under the United Nations Economic Commission for Europe (UNECE) framework, particularly UN Regulation 171 for Driver Control Assistance Systems.
The Netherlands’ RDW authority granted the pioneering approval after over 18 months of rigorous testing, including 1.6 million kilometers on European roads and extensive data submissions.
This approval enables mutual recognition across the EU, allowing other member states to adopt it nationally without full re-testing. Lithuania quickly leveraged this mechanism, becoming the second adopter. Tesla positions FSD Supervised as a tool to incrementally improve road safety, with the company claiming it reduces incidents when used properly.
Bottlenecks slowing broader European deployment include fragmented national regulations, varying levels of regulatory skepticism, and requirements for robust driver monitoring. Some EU officials have raised concerns about performance in adverse conditions like icy roads or speeding scenarios, alongside frustrations over Tesla’s public advocacy approach.
Additional hurdles involve data privacy, liability frameworks, and the need for EU-wide harmonization. While countries like Belgium appear to be fast-tracking adoption, larger markets such as Germany, France, and Italy are expected to follow in the coming months, with potential EU-wide progress targeted for later in 2026.
Tesla Full Self-Driving Across the World
As of May, Full Self-Driving (Supervised) is available in approximately ten countries.
In North America, it has been live for years in the United States, Canada, Mexico, and Puerto Rico. Asia-Pacific additions include Australia, New Zealand, and South Korea, while China utilizes what Tesla calls “City Autopilot.” In Europe, the Netherlands and now Lithuania join the list, with more countries mulling the possibility of also approving FSD.
Tesla offers FSD via monthly subscriptions (around €99 in Europe) or one-time purchases (with deadlines approaching in many markets), shifting toward recurring revenue models. Today is the final day Europeans will be able to purchase the suite outright.
This expansion underscores Tesla’s push for global autonomy, starting with supervised and building toward greater capabilities. With Lithuania now online, momentum is building across Europe, though regulatory caution will continue shaping the pace. Owners in approved regions report smoother highway and urban driving, but the system remains Level 2, which requires human oversight.
Elon Musk
Tesla ditches India after years of broken promises
Tesla has ditched its plans to build a factory in India after years of failed negotiations.
Tesla’s long-running effort to establish a manufacturing presence in India is officially over. India’s Minister of Heavy Industries H.D. Kumaraswamy confirmed on May 19, 2026 that Tesla has informed authorities it will not proceed with a manufacturing facility in the country.
Tesla first signaled serious interest in India around 2021, when it began hiring local staff and lobbying the Indian government for lower import tariffs. The ask was straightforward: reduce duties enough for Tesla to test the market with imported vehicles before committing capital to a local factory. India’s position was equally firm, with an ask of Tesla to commit to manufacturing first, then receive tariff relief. Neither side moved, and the talks quietly collapsed.
Tesla to open first India experience center in Mumbai on July 15
India had offered a policy that would reduce import duties from 110% down to 15% on EVs priced above $35,000, provided companies committed at least $500 million toward local manufacturing investment within three years. Tesla declined to participate. The tariff standoff was only part of the problem. Analysts pointed to significant gaps in India’s local supply chain, inadequate industrial infrastructure, and a mismatch between Tesla’s premium pricing and the purchasing power of India’s automotive market as additional factors that made the investment difficult to justify.
First signs of an unraveling relationship came in April 2024, when Musk abruptly cancelled a planned trip to India where he was set to meet Prime Minister Modi and announce Tesla’s market entry. By July 2024, Fortune reported that Tesla executives had stopped contacting Indian government officials entirely. The government at that point understood Tesla had capital constraints and no plans to invest.
The more fundamental issue is that Tesla’s existing factories are currently operating at approximately 60% capacity, making a commitment to building new manufacturing capacity in a new market difficult to defend to investors. Tesla will continue selling imported Model Y vehicles through its existing showrooms in Mumbai, Delhi, Gurugram, and Bengaluru, but local production is no longer part of the plan.
Tesla scales back driver monitoring with latest Full Self-Driving release
Tesla Full Self-Driving expands in Europe, entering its second country
