Connect with us

News

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

[Credit: Google DeepMind]

Published

on

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.

Advertisement

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.

Advertisement

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.

Advertisement
Comments

News

Tesla’s AI Chief just hinted at something big for FSD v14 lite owners

Tesla’s AI chief suggests the newest FSD v14 Lite build may finally go wide release.

Published

on

By

Tesla’s head of AI, Ashok Elluswamy, noted on Sunday that the newest FSD v14 Lite build rolling out to Hardware 3 cars is likely the version that goes to wide release, the strongest signal yet that Tesla is near to closing out an early access phase that Hardware 3 owners have waited more than a year for.

Elluswamy made the comment in response to an extensive review from Tesla owner Zack, known on X as @BLKMDL3, who tested software version 2026.20.6.10 and detailed the changes in a lengthy post. “FSD v14 Lite (for Tesla AI3 hardware vehicles) review.

The update restarts a rollout that had stalled after its initial release. Tesla began pushing FSD v14 Lite to Hardware 3 early access drivers on June 29, bringing driving behavior learned on the newer Hardware 4 computer down to the more limited chip that has powered Tesla vehicles built between 2019 and early 2023. That release, as we covered in detail, gave roughly 4 million HW3 vehicles their first meaningful update since being frozen on version 12.6 in early 2025.

Tesla Full Self-Driving v14 ‘Lite’ Release Notes: new capabilities and features

Advertisement

The latest build adds features that bring Hardware 3 closer in line with what Hardware 4 owners already have. FSD can now start directly from park without a brake pedal confirmation, a change Zack called a small but meaningful quality of life improvement. The interface also picks up the blue “P” park icon, approaching destination alerts, and a dedicated Self-Driving app with streak tracking, all details previously exclusive to the AI4 branch of v14, as outlined in Tesla’s original release notes.

The stakes around Hardware 3 go beyond software polish. Tesla sold the Full Self-Driving package for years on the promise that every vehicle equipped with it had the hardware needed to eventually drive itself without supervision. That promise broke down during Tesla’s Q1 2026 earnings call, when Musk acknowledged HW3 cars could not run unsupervised FSD, prompting Tesla to offer trade-in discounts and hardware retrofits alongside the Lite software track.

Tesla confirmed HW3 can’t do Unsupervised FSD but there’s more to the story

Tesla has continued to frame v14 Lite as the primary path forward for the HW3 fleet, telling owners in April that international markets would follow the U.S. rollout once regulatory approvals came through. For now, HW3 owners in the early access group are the only ones running the new build. A broader rollout would mark the second major software delivery to the legacy fleet since Tesla first released FSD v14 to Hardware 4 vehicles, and the first sign since June that the Lite program is still moving rather than stuck in early access limbo.

Advertisement
Continue Reading

Elon Musk

Elon Musk sends first warning to SpaceX short sellers

Published

on

Credit: Grok

In a pointed message on X, Elon Musk warned that firms maintaining significant short positions in SpaceX over time face “very low” survival probability.

The statement comes amid post-IPO volatility for the rocket company, now trading under the ticker $SPCX.

Advertisement

Five weeks after what was described as the largest IPO in history, the stock had fallen roughly 30% from its peak above $2.6 trillion, briefly surpassing Microsoft and Amazon in market value. Short sellers celebrated gains of about $8.7 billion, but Musk’s reply underscores his long-term conviction.

The warning directly echoes a detailed bullish analysis arguing that Starship’s cost reductions could unlock a multi-trillion-dollar space economy. Projects ranging from solar power beamed from orbit and asteroid mining to orbital data centers and Mars terraforming were projected to create over $100 trillion in new market capitalization.

In this vision, SpaceX acts as the essential infrastructure provider, akin to AWS for cloud computing, capturing monopoly-like revenues from launches, crew transport, and data traffic across a rapidly expanding frontier.

This is far from the first time Musk has targeted short sellers. With Tesla, he has repeatedly framed persistent bears as destined for major losses. In July 2024, Musk declared that once Tesla achieves full autonomy and volume production of Optimus robots, “anyone still holding a short position will be obliterated. Even Gates,” referencing Microsoft co-founder Bill Gates’ reported short bets.

Advertisement

Elon Musk reveals what Tesla stock surge could do to Bill Gates

Earlier, in 2018, he taunted shorts that they had “about three weeks before their short position explodes,” a remark followed by sharp stock gains. Musk has also called short selling “value destroying” and once suggested it “should be illegal,” viewing it as betting against innovation and progress.

Critics often dismiss Musk’s optimism as hype, especially when near-term metrics like quarterly deliveries or stock fluctuations disappoint.

Yet his pattern remains consistent: framing short positions against his companies as fundamentally misjudging exponential technological leaps. For SpaceX shorts, the message is clear: betting against multi-planetary ambitions and the infrastructure monopoly they enable carries existential risk for the firms involved.

Advertisement

As Musk and supporters see it, the space economy’s upside dwarfs Earth-bound valuation models, making today’s dips temporary in a decades-long ascent.

Continue Reading

News

Tesla reveals first vehicle model to receive Starlink integration

Published

on

Tesla has evidently revealed which of its vehicle models will be the first to receive Starlink integration: the Cybercab.

Tesla’s Santana Row showroom now has a full-fledged display of the Cybercab, with an extensive bit of information hung around an exhibit that seems to reveal the vehicle’s newest feature: an integrated Starlink antenna that will enable secure and reliable internet access during trips.

Credit: @Starscream_SJC | X

Cybercab is geared toward autonomous ride-hailing for one or two passengers. The production units rolling off the lines at Gigafactory Texas are built without steering wheels or pedals, meaning when public rides begin, passengers will not need to interact with a human being or control the vehicle in any way outside of what appears on the center screen for their entertainment during the ride.

Advertisement

Along the display, Tesla wrote this message about Cybercab:

“Cybercab is built for autonomy. It has no steering wheel, no side mirrors, and no pedals. It goes where you tell it to go and how you want it to, so you can relax along the way. It is hyper aware and responsive to your surroundings, monitoring other drivers, responding to emergency vehicles, utilizing its expertise in the rarest scenarios to help keep you safe.”

Tesla has been teasing a potential Starlink integration for quite some time now. In December, the company hinted at potential Starlink internet terminal integration within its vehicles in a patent that described a vehicle roof assembly with integrated radio frequency (RF) transparency.

Tesla hints at Starlink integration with recent patent

Advertisement

The company wrote in its patent application that a new roof design built with materials that differ from the standard metallic or glass elements used in today’s cars would allow it to integrate modern vehicular technologies, in particular, ones that require radio frequency transmission and reception.

Tesla suggested high-strength polymer blends, like Polycarbonate, Acrylonitrile Butadiene Styrene, or Acrylonitrile Styrene Acrylate.

This is the first time we’ve seen Tesla officially confirm the Starlink integration into the Cybercab. It’s not much of a surprise considering the company’s intention behind the Cybercab, which is to make travel autonomous.

Productivity will now be at a maximum during a work-related commute, while the center screen could be utilized for Netflix or potentially even live TV for those who are heading to dinner or to a fun activity.

Advertisement
Continue Reading