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.
Elon Musk
How to use Grok Bot to block spam calls and texts
Musk told users to ask Grok Bot to scrub their phone numbers from spam lists.
Elon Musk has a new use case for Grok Bot, and it is the spam call. On Thursday he replied to an X user named Arash with a short instruction: “Ask your @Grok @Bot to remove your phone number from spam call & text lists!” Arash had said he got tired of the calls, had an AI bot find his number on listing sites and file removal requests, and packaged the process as a free skill for others.
The skill is called Spam-Call Scrubber, which is described to find a phone number on people search sites and data brokers, submits the opt outs, completes the confirmation emails those sites send back, and rechecks on a schedule the user picks. Using it requires the Grok Bot app. The pitch is time saved, since most broker opt outs sit behind separate forms on separate sites.
Ask your @Grok @Bot to remove your phone number from spam call & text lists!
— Elon Musk (@elonmusk) October 15, 2026
Musk said Grok Bot now gives each bot its own email address, and that it can detect scam emails. On Thursday he also said SpaceX would make users whole if the bot botches a purchase or leaks a card, then told users to shop away from Amazon after the retailer blocked the agent, as Teslarati reported. The terms of service we reviewed at the time put responsibility for what an agent does on the user.
For Tesla owners, Grok Bot is not just a phone app. Tesla brought Grok Bot into its vehicles on September 22, and we argued earlier this week that the Cybercab’s real advantage may be the errands it runs during a ride. Every Cybercab and the rest of the Model Y Robotaxi fleet has it enabled. The more routine tasks like this one become, the more a rider has reason to hand over something personal in the back seat.
The new Spam-Call Scrubber skill can be downloaded for free and works on sites that honor removal requests, while noting that listings can reappear, and illegal robocallers do not check any registry. Whether Spam-Call Scrubber cuts anyone’s call volume is something the first wave of users will find out, and Musk’s endorsement guarantees that wave is coming.
Investor's Corner
Tesla’s flying Roadster just revealed something bigger than the car
Analysts say the Roadster demo puts a Tesla and SpaceX merger back on the table.
The Roadster unveiling near Waco ended Thursday night, and by Friday morning much of the investor reaction had less to do with the car than with who owns the rocket technology inside it.
Wedbush analyst Dan Ives said the event “puts the Tesla/SpaceX relationship on the table in a tangible way,” pointing to the propulsion, pressure vessel and control hardware sitting on a Tesla product. Gene Munster of Deepwater Asset Management called the demo “a ridiculous display of engineering” with “no commercial value” beyond embarrassing traditional automakers, though he said it showed Musk wants the two companies together.
The more specific forecast came a day earlier from Barclays. Analyst Dan Levy told clients a deal could be announced before Tesla’s annual meeting, which must happen by December 6, and that an announcement in late October or early November could make shareholder approval harder. Barclays expects SpaceX to be the buyer in an all stock deal, with Tesla holders receiving SpaceX shares at a premium, based on market values of roughly $2.1 trillion for SpaceX and $1.5 trillion for Tesla. If nothing lands around the meeting, the bank still sees an announcement within 6 to 12 months.
The Roadster demo just added more weight to merger speculations. Tesla’s demo used cold gas thrusters and pressure tanks of the kind SpaceX uses on Falcon 9, and Musk described the car as a collaboration between Tesla and SpaceX engineers, as we mentioned in our breakdown of the three Roadster configurations.
Musk has not publicly addressed a deal since the event, as far as we have seen. His most direct answer remains the one he gave at the All In Summit, when he said that with so much collaboration, “who can imagine what action one might take” without ruling anything out. Ives has held to a 2027 timeline since his March note, and Musk pushed back on the China piece of the speculation when ARK floated a year end announcement in August.
The next test is Tesla’s third quarter earnings call on October 21. However, we recall in July that Musk told analysts, “we can’t talk about combining companies and that kind of thing on an earnings call,” so a clear answer wouldn’t be expected.
News
How Tesla’s Roadster fan system and thrusters are built to dominate the corners
Tesla’s Roadster uses fans, active wings and cold gas thrusters to create grip at any speed.
Tesla’s new Roadster is best known for flipping through the air in Texas, but the technology that matters most for a race track is the stuff that keeps it on the ground. Tesla’s Roadster page describes a multi-mode fan and ground sealing system that acts as a downforce generator, pulling air out from beneath the car. Tesla says it provides enough suction to hold the vehicle upside down, even when stationary.
That is the key difference from the wings and diffusers on a normal supercar. Conventional aero only makes downforce when the car is moving, and it grows with speed, so a car has the least grip in the slow corners and under hard braking. A fan system makes downforce at any speed. Tesla’s patent, which we covered last year, describes fans and deployable skirts that create sealed or partially sealed regions under the car, with the fans extracting air to lower the pressure and increase grip and stability.
Still processing this … the most unreal thing I’ve seen. https://t.co/HtEuvnkZjY
— TESLARATI (@Teslarati) October 16, 2026
Tesla pairs that with active wings, a next generation steer by wire system and a Track Mode that lowers the car and changes the suspension, with high downforce and low drag settings for the circuit. To keep weight down, Tesla points to magnesium, titanium and carbon fiber, manual controls and a fixed seat position, which it says lets the car respond to driver inputs almost instantly.
Tesla Roadster: Three configs, one can fly, 0-60 in 0.8 seconds
The cold gas thrusters are the other half. On the Thrust version they sit at the rear and Tesla says they take the car from 0 to 60 mph in under 0.9 seconds, while the Rocket version adds perimeter thrusters for forward, upward and lateral rotational movement. Tesla says the all electric actuators make micro adjustments within a fraction of a second.
Roadster transforms in Track Mode
These aero features aren’t just for looks: they provide the best passive downforce package of any road car (approaching F1 levels!) with wing actuation driven by the @Tesla_Optimus actuator system https://t.co/AqrC4qUga9
— Tesla (@Tesla) October 16, 2026
Musk has been talking about records for years. In June 2019 he said, “We’re going to do things with the new Roadster that are kind of unfair to other cars.” That September, when a follower asked whether the Roadster would beat the Nürburgring production car record, he replied with one word, “Absolutely,” as we reported at the time. In February 2024 he said Tesla had “radically increased the design goals” for the car and that its sub one second 0 to 60 time would be “the least interesting part.”
There are caveats. Tesla has not published a lap time or a verified cornering figure, so the record talk is still a promise rather than a result. Tesla also says the car is not approved for public road use, and the thruster features are limited to the Rocket trim, which is invite only. Fan cars have also been banned or withdrawn before, and getting a sealed underbody to work on a rough public road is a harder problem than on a smooth track. The first real test will be an official lap at a circuit.
How to use Grok Bot to block spam calls and texts
Tesla’s flying Roadster just revealed something bigger than the car
How Tesla’s Roadster fan system and thrusters are built to dominate the corners
SpaceX reveals how its 1 Million AI satellite network will work and prevent space collisions
Elon Musk’s Boring Company lands a new Middle East deal, and Nashville is about to get faster
