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Google’s DeepMind unit develops AI that predicts 3D layouts from partial images

[Credit: Google DeepMind]

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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.

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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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Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Tesla plans for largest Australian Supercharger yet

The company has a 20-stall site in the city of Goulburn in New South Wales, which is an ideal location for trips between Sydney and Canberra, two major cities.

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Credit: Tesla

Tesla is planning to build its largest Supercharger in Australia yet, expanding on the infrastructure the company has built for electric vehicles.

The company has a 20-stall site in the city of Goulburn in New South Wales, which is an ideal location for trips between Sydney and Canberra, two major cities.

However, according to The Driven, a new Australian Supercharger is on the way, and it is going to be the biggest in the country, accounting for more than 25 stalls total. They will likely be V4 Superchargers, Tesla’s fastest piles that enable some serious range for cars that will plug in.

Tesla is operating 148 active Supercharger sites in Australia, with 80 of those being available to non-Tesla EVs as a part of the company’s initiative to make things accessible for all electric vehicle owners.

The expansion of Tesla Superchargers is welcome for all EV owners, especially as there are so many automakers that have access to the network. It is widely reliable and extremely dependable; it is tough to find a Supercharger location that is completely out of service.

The opening of the stalls will be welcome for the Tesla owners of Australia, especially as the Model Y continues to be a major contributor to the company’s prowess in the market.

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Tesla’s sales performance in Australia showed a mixed but challenging picture in 2025, with the company delivering 28,856 new vehicles, marking a significant 24.8% decline from 38,347 units in 2024.

This represented the brand’s largest annual drop on record and the second consecutive year of decline, amid intensifying competition from Chinese EV makers like BYD and shifting buyer preferences toward SUVs. The Tesla Model Y remained a standout performer and Australia’s best-selling electric vehicle, with 22,239 deliveries, up 4.6percent year-over-year, accounting for about 77 percent of Tesla’s total sales.

The mid-year launch of the updated “Juniper” Model Y helped sustain momentum in the popular mid-size SUV segment.

In contrast, the Model 3 sedan struggled sharply, plummeting 61.3 percent to just 6,617 units, as consumers favored SUVs and faced growing options in the sedan category.

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Despite the overall dip, Tesla held onto leadership in the EV segment, capturing roughly 28 percent of the BEV market. Australia’s EV market grew robustly, surpassing 156,000 sales and reaching 13 percent market share, up 38.7 percent from 2024, highlighting strong broader adoption even as Tesla faced headwinds.

Early 2026 data suggests a rebound, with EV sales nearly doubling year-over-year in February and the Model Y showing strong gains, positioning Tesla for potential recovery amid ongoing competition.

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Tesla Model Y L gets new entertainment feature

Beyond audio quality, Immersive Sound X aligns with Tesla’s ecosystem of over-the-air updates, potentially allowing future refinements.

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Credit: Tesla China

Tesla is including a new entertainment feature in the Model Y L, improving the vehicle even further and making it what appears to be the best configuration of the all-electric crossover globally.

Unfortunately, we in the U.S. do not yet have access to the vehicle, and the plans for it to enter the market remain up in the air, as CEO Elon Musk has said it could appear late this year. However, there is nothing concrete at this time.

Tesla’s latest enhancement to the Model Y L is a new Immersive Sound X feature, exclusive to the Model Y L.

It aims to transform the in-car listening experience into something truly cinematic. First introduced by Tesla China in October 2025, this advanced audio mode is now rolling out to deliveries in Australia and New Zealand, highlighting Tesla’s approach to region-specific premium upgrades.

At its core, Immersive Sound X leverages real-time sound extraction technology to create a customizable 3D soundstage. Using advanced algorithms, it analyzes audio tracks to separate direct sounds, such as vocals or lead instruments, from ambient elements like echoes and reverb.

The system then positions direct sounds front and center while diffusing ambient sounds to the side and rear speakers, simulating an expansive virtual environment. This results in a heightened sense of depth and spatial awareness, making listeners feel as if they’re in a concert hall or studio.

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What sets Immersive Sound X apart from the standard Immersive Sound found in other Tesla models is its hardware dependency and enhanced processing. The Model Y L boasts an 18-speaker system with a subwoofer, compared to the 15-speaker setup, plus a subwoofer, in the Model Y Long Range’s previous premium audio configuration.

This upgrade provides more “kick” and precision, enabling finer control over the soundstage. Unlike traditional surround sound, which requires multi-channel mixes like Dolby Atmos, Immersive Sound X works with any stereo source from platforms like Spotify or Apple Music, so every owner will be able to use it.

Tesla Model Y lineup expansion signals an uncomfortable reality for consumers

You can fine-tune the experience via an adjustable immersion slider, scaling the “size” of the virtual space to personal preferences. This caters to a more custom sound.

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An Auto mode intelligently adapts based on media type, whether it’s music, podcasts, or videos, ensuring optimal immersion without manual tweaks. This feature is unavailable on standard Model Y variants (with 7 or 15 speakers) or Model 3 trims, underscoring Tesla’s strategy to differentiate higher trims through superior hardware and software integration.

Beyond audio quality, Immersive Sound X aligns with Tesla’s ecosystem of over-the-air updates, potentially allowing future refinements.

For audiophiles and casual listeners alike, it elevates mundane commutes into immersive journeys, proving Tesla’s commitment to blending cutting-edge tech with user-centric design.

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Elon Musk teases crazy outlook for xAI against its competitors

Musk’s response was vintage hyperbole, designed to rally supporters and dismiss doubters, something his responses on social media often do.

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Credit: NVIDIA

Elon Musk has never been one to shy away from crazy timelines, massive expectations, and outrageous outlooks. However, his recent plans for xAI and where he believes it will end up compared to its competitors are sure to stimulate conversation.

In a bold and characteristic response on X, Elon Musk fired back at a recent analysis that positioned his AI venture, xAI, as lagging behind industry frontrunners.

The post, from March 14, came as a direct reply to forecaster Peter Wildeford’s assessment, which drew from benchmarks and reporting to rank AI developers.

Wildeford placed Anthropic, Google, and OpenAI in a virtual tie at the top, with xAI and Meta trailing by about seven months. Chinese players like Moonshot, Deepseek, zAI, and Alibaba were estimated to be nine months behind, while France’s Mistral lagged by about a year and a half.

Musk’s response was vintage hyperbole, designed to rally supporters and dismiss doubters, something his responses on social media often do.

He claimed xAI would “catch up this year,” meaning by the end of 2026, erasing that seven-month deficit against the leaders. But he didn’t stop there.

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Musk escalated his vision to 2029, predicting xAI would “exceed them all by such a long distance” that observers would need the James Webb Space Telescope, NASA’s orbiting observatory stationed about 930,000 miles from Earth, to spot whoever lands in second place. This analogy underscores Musk’s confidence in xAI’s trajectory, implying an astronomical lead that could redefine the AI landscape.

Breaking down these claims reveals Musk’s strategic optimism. First, the short-term catch-up: xAI, launched in 2023, has already released models like Grok, but recent benchmarks, including those for Grok 4.2, have shown it falling short in capabilities compared to rivals.

Anthropic’s Claude series, Google’s Gemini, and OpenAI’s GPT models dominate in areas like reasoning, coding, and multimodal tasks. Musk’s assertion suggests aggressive scaling in compute, talent, or architecture, perhaps leveraging xAI’s ties to Tesla’s Dojo supercomputers or Musk’s vast resources, to close the gap swiftly.

The longer-term dominance by 2029 paints an even more audacious picture. Musk envisions xAI not just parity but supremacy, outpacing competitors in innovation speed and model sophistication.

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This could involve breakthroughs in energy-efficient training, real-world integration, like Tesla’s robotics, or ethical AI alignment, aligning with Musk’s stated goal of “understanding the universe.”

Critics, however, point to parallels with Tesla’s Full Self-Driving delays; one reply highlighted Musk’s 2023 promise of FSD readiness. Musk has made this promise for many years, and although the system has been strong and improving, it is still a ways off from the completely autonomous operation that was expected by now.

Tesla Full Self-Driving v14.2.2.5 might be the most confusing release ever

Musk’s comment highlights the intensifying U.S.-centric AI race, with xAI challenging the “three-way” dominance noted by Wharton professor Ethan Mollick, whom Wildeford quoted. As geopolitical tensions rise—evident in the Chinese firms’ lag—Musk’s tease could spur investment and talent wars.

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Yet, it also invites scrutiny: Will xAI deliver, or is this another telescope-needed mirage? In an industry where timelines slip but stakes soar, Musk’s words keep the spotlight on xAI’s ambitious path forward.

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