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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.
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Tesla (TSLA) receives “Buy” rating and $551 PT from Canaccord Genuity
He also maintained a “Buy” rating for TSLA stock over the company’s improving long-term outlook, which is driven by autonomy and robotics.
Canaccord Genuity analyst George Gianarikas raised his Tesla (NASDAQ:TSLA) price target from $482 to $551. He also maintained a “Buy” rating for TSLA stock over the company’s improving long-term outlook, which is driven by autonomy and robotics.
The analyst’s updated note
Gianarikas lowered his 4Q25 delivery estimates but pointed to several positive factors in the Tesla story. He noted that EV adoption in emerging markets is gaining pace, and progress in FSD and the Robotaxi rollout in 2026 represent major upside drivers. Further progress in the Optimus program next year could also add more momentum for the electric vehicle maker.
“Overall, yes, 4Q25 delivery expectations are being revised lower. However, the reset in the US EV market is laying the groundwork for a more durable and attractive long-term demand environment.
“At the same time, EV penetration in emerging markets is accelerating, reinforcing Tesla’s potential multi‑year growth runway beyond the US. Global progress in FSD and the anticipated rollout of a larger robotaxi fleet in 2026 are increasingly important components of the Tesla equity story and could provide sentiment tailwinds,” the analyst wrote.
Tesla’s busy 2026
The upcoming year would be a busy one for Tesla, considering the company’s plans and targets. The autonomous two-seat Cybercab has been confirmed to start production sometime in Q2 2026, as per Elon Musk during the 2025 Annual Shareholder Meeting.
Apart from this, Tesla is also expected to unveil the next-generation Roadster on April 1, 2026. Tesla is also expected to start high-volume production of the Tesla Semi in Nevada next year.
Apart from vehicle launches, Tesla has expressed its intentions to significantly ramp the rollout of FSD to several regions worldwide, such as Europe. Plans are also underway to launch more Robotaxi networks in several more key areas across the United States.
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Waymo sues Santa Monica over order to halt overnight charging sessions
In its complaint, Waymo argued that its self-driving cars’ operations do not constitute a public nuisance, and compliance with the city’s order would cause the company irreparable harm.
Waymo has filed a lawsuit against the City of Santa Monica in Los Angeles County Superior Court, seeking to block an order that requires the company to cease overnight charging at two facilities.
In its complaint, Waymo argued that its self-driving cars’ operations do not constitute a public nuisance, and compliance with the city’s order would cause the company irreparable harm.
Nuisance claims
As noted in a report from the Los Angeles Times, Waymo’s two charging sites at Euclid Street and Broadway have operated for about a year, supporting the company’s growing fleet with round-the-clock activity. Unfortunately, this has also resulted in residents in the area reportedly being unable to sleep due to incessant beeping from self-driving taxis that are moving in and out of the charging stations around the clock.
Frustrated residents have protested against the Waymos by blocking the vehicles’ paths, placing cones, and “stacking” cars to create backups. This has also resulted in multiple calls to the police.
Last month, the city issued an order to Waymo and its charging partner, Voltera, to cease overnight operations at the charging locations, stating that the self-driving vehicles’ activities at night were a public nuisance. A December 15 meeting yielded no agreement on mitigations like software rerouting. Waymo proposed changes, but the city reportedly insisted that nothing would satisfy the irate residents.
“We are disappointed that the City has chosen an adversarial path over a collaborative one. The City’s position has been to insist that no actions taken or proposed by Waymo would satisfy the complaining neighbors and therefore must be deemed insufficient,” a Waymo spokesperson stated.
Waymo pushes back
In its legal complaint, Waymo stated that its “activities at the Broadway Facilities do not constitute a public nuisance.” The company also noted that it “faces imminent and irreparable harm to its operations, employees, and customers” from the city’s order. The suit also stated that the city was fully aware that the Voltera charging sites would be operating around the clock to support Waymo’s self-driving taxis.
The company highlighted over one million trips in Santa Monica since launch, with more than 50,000 rides starting or ending there in November alone. Waymo also criticized the city for adopting a contentious strategy against businesses.
“The City of Santa Monica’s recent actions are inconsistent with its stated goal of attracting investment. At a time when the City faces a serious fiscal crisis, officials are choosing to obstruct properly permitted investment rather than fostering a ‘ready for business’ environment,” Waymo stated.
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Tesla FSD v14.2.2 is getting rave reviews from drivers
So far, early testers have reported buttery-smooth drives with confident performance, even at night or on twisty roads.
Tesla Full Self-Driving (Supervised) v14.2.2 is receiving positive reviews from owners, with several drivers praising the build’s lack of hesitation during lane changes and its smoother decision-making, among others.
The update, which started rolling out on Monday, also adds features like dynamic arrival pin adjustment. So far, early testers have reported buttery-smooth drives with confident performance, even at night or on twisty roads.
Owners highlight major improvements
Longtime Tesla owner and FSD user @BLKMDL3 shared a detailed 10-hour impression of FSD v14.2.2, noting that the system exhibited “zero lane change hesitation” and “extremely refined” lane choices. He praised Mad Max mode’s performance, stellar parking in locations including ticket dispensers, and impressive canyon runs even in dark conditions.
Fellow FSD user Dan Burkland reported an hour of FSD v14.2.2’s nighttime driving with “zero hesitations” and “buttery smooth” confidence reminiscent of Robotaxi rides in areas such as Austin, Texas. Veteran FSD user Whole Mars Catalog also demonstrated voice navigation via Grok, while Tesla owner Devin Olsen completed a nearly two-hour drive with FSD v14.2.2 in heavy traffic and rain with strong performance.
Closer to unsupervised
FSD has been receiving rave reviews, even from Tesla’s competitors. Xpeng CEO He Xiaopeng, for one, offered fresh praise for FSD v14.2 after visiting Silicon Valley. Following extended test drives of Tesla vehicles running the latest FSD software, He stated that the system has made major strides, reinforcing his view that Tesla’s approach to autonomy is indeed the proper path towards autonomy.
According to He, Tesla’s FSD has evolved from a smooth Level 2 advanced driver assistance system into what he described as a “near-Level 4” experience in terms of capabilities. While acknowledging that areas of improvement are still present, the Xpeng CEO stated that FSD’s current iteration significantly surpasses last year’s capabilities. He also reiterated his belief that Tesla’s strategy of using the same autonomous software and hardware architecture across private vehicles and robotaxis is the right long-term approach, as it would allow users to bypass intermediate autonomy stages and move closer to Level 4 functionality.
Tesla (TSLA) receives “Buy” rating and $551 PT from Canaccord Genuity
Waymo sues Santa Monica over order to halt overnight charging sessions
