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Waymo launches its AI research model for self-driving operations

Credit: Waymo

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Waymo, the driverless ride-hailing arm of Google parent company Alphabet, has now launched a new AI research model for its self-driving operations.

In a pair of press releases on its approach to AI and its new end-to-end multimodal model for autonomous driving, dubbed EMMA, Waymo has shared details about its plans for the AI research model going forward. The company says it is still using the EMMA model in research stages, rather than in operational vehicles, and the approach comes as an alternative that looks a lot like Tesla’s Full Self-Driving (FSD) and other end-to-end model approaches.

“EMMA is research that demonstrates the power and relevance of multimodal models for autonomous driving,” said Drago Anguelov, VP and Head of Research at Waymo. “We are excited to continue exploring how multimodal methods and components can contribute towards building an even more generalizable and adaptable driving stack.”

Waymo says the EMMA model uses real-world knowledge based on its Gemini language model, while the end-to-end approach is expected to eventually let autonomous vehicles operate directly from sensor data and real-time driving scenarios. The company has also highlighted its use of Large Language Models (LLMs) and Vision-Language Models (VLMs), calling its architecture the Waymo Foundation Model.

Hear the company’s executive detail the Waymo research and AI program more below.

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EMMA research and criticisms

In the announcement press release about EMMA, Waymo lays out the following as key aspects of the research program:

  1. End-to-End Learning: EMMA processes raw camera inputs and textual data to generate various driving outputs including planner trajectories, perception objects, and road graph elements.
  2. Unified Language Space: EMMA maximizes Gemini’s world knowledge by representing non-sensor inputs and outputs as natural language text.
  3. Chain-of-Thought Reasoning: EMMA uses chain-of-thought reasoning to enhance its decision-making process, improving end-to-end planning performance by 6.7% and providing interpretable rationale for its driving decisions.

“The problem we’re trying to solve is how to build autonomous agents that navigate in the real world,” says Srikanth Thirumalai, Waymo VP of Engineering. “This goes far beyond what many AI companies out there are trying to do.”

Still, some have cast doubt on the large-scale end-to-end model, saying that it may be too risky to utilize generative AI models without including significant safeguards.

“It’s bandwagoning around something that sounds impressive but is not a solution,” said Sterling Anderson, Aurora Innovation’s Chief Product Officer, in a statement to Automotive News.

Mobileye CTO Shai Shalev-Shwartz called end-to-end approaches “a huge risk,” especially regarding the verification of decision-making process for vehicles operating on the model. It’s also worth noting that Waymo is currently only researching the approach, and it doesn’t currently have any plans to make it commercially available.

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The news comes after Waymo recently closed on a $5.6 billion funding round, effectively bringing the company’s valuation up past $45 billion. The company is also working on its next generation of self-driving vehicles based on the Hyundai Ioniq 5, built at a new factory in Georgia.

Waymo hires former Tesla Executive 

What are your thoughts? Let me know at zach@teslarati.com, find me on X at @zacharyvisconti, or send us tips at tips@teslarati.com.

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Zach is a renewable energy reporter who has been covering electric vehicles since 2020. He grew up in Fremont, California, and he currently lives in Colorado. His work has appeared in the Chicago Tribune, KRON4 San Francisco, FOX31 Denver, InsideEVs, CleanTechnica, and many other publications. When he isn't covering Tesla or other EV companies, you can find him writing and performing music, drinking a good cup of coffee, or hanging out with his cats, Banks and Freddie. Reach out at zach@teslarati.com, find him on X at @zacharyvisconti, or send us tips at tips@teslarati.com.

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Elon Musk

Elon Musk and Tesla AI Director share insights after empty driver seat Robotaxi rides

The executives’ unoccupied tests hint at the rapid progress of Tesla’s unsupervised Robotaxi efforts.

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Ashok Elluswamy

Tesla CEO Elon Musk and AI Director Ashok Elluswamy celebrated Christmas Eve by sharing personal experiences with Robotaxi vehicles that had no safety monitor or occupant in the driver’s seat. Musk described the system’s “perfect driving” around Austin, while Elluswamy posted video from the back seat, calling it “an amazing experience.”

The executives’ unoccupied tests hint at the rapid progress of Tesla’s unsupervised Robotaxi efforts.

Elon and Ashok’s firsthand Robotaxi insights

Prior to Musk and the Tesla AI Director’s posts, sightings of unmanned Teslas navigating public roads were widely shared on social media. One such vehicle was spotted in Austin, Texas, which Elon Musk acknowleged by stating that “Testing is underway with no occupants in the car.” 

Based on his Christmas Eve post, Musk seemed to have tested an unmanned Tesla himself. “A Tesla with no safety monitor in the car and me sitting in the passenger seat took me all around Austin on Sunday with perfect driving,” Musk wrote in his post.

Elluswamy responded with a 2-minute video showing himself in the rear of an unmanned Tesla. The video featured the vehicle’s empty front seats, as well as its smooth handling through real-world traffic. He captioned his video with the words, “It’s an amazing experience!”

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Towards Unsupervised operations

During an xAI Hackathon earlier this month, Elon Musk mentioned that Tesla owed be removing Safety Monitors from its Robotaxis in Austin in just three weeks. “Unsupervised is pretty much solved at this point. So there will be Tesla Robotaxis operating in Austin with no one in them. Not even anyone in the passenger seat in about three weeks,” he said. Musk echoed similar estimates at the 2025 Annual Shareholder Meeting and the Q3 2025 earnings call.

Considering the insights that were posted Musk and Elluswamy, it does appear that Tesla is working hard towards operating its Robotaxis with no safety monitors. This is quite impressive considering that the service was launched just earlier this year.

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Elon Musk

Starlink passes 9 million active customers just weeks after hitting 8 million

The milestone highlights the accelerating growth of Starlink, which has now been adding over 20,000 new users per day.

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Credit: Starlink/X

SpaceX’s Starlink satellite internet service has continued its rapid global expansion, surpassing 9 million active customers just weeks after crossing the 8 million mark. 

The milestone highlights the accelerating growth of Starlink, which has now been adding over 20,000 new users per day.

9 million customers

In a post on X, SpaceX stated that Starlink now serves over 9 million active users across 155 countries, territories, and markets. The company reached 8 million customers in early November, meaning it added roughly 1 million subscribers in under seven weeks, or about 21,275 new users on average per day. 

“Starlink is connecting more than 9M active customers with high-speed internet across 155 countries, territories, and many other markets,” Starlink wrote in a post on its official X account. SpaceX President Gwynne Shotwell also celebrated the milestone on X. “A huge thank you to all of our customers and congrats to the Starlink team for such an incredible product,” she wrote. 

That growth rate reflects both rising demand for broadband in underserved regions and Starlink’s expanding satellite constellation, which now includes more than 9,000 low-Earth-orbit satellites designed to deliver high-speed, low-latency internet worldwide.

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Starlink’s momentum

Starlink’s momentum has been building up. SpaceX reported 4.6 million Starlink customers in December 2024, followed by 7 million by August 2025, and 8 million customers in November. Independent data also suggests Starlink usage is rising sharply, with Cloudflare reporting that global web traffic from Starlink users more than doubled in 2025, as noted in an Insider report.

Starlink’s momentum is increasingly tied to SpaceX’s broader financial outlook. Elon Musk has said the satellite network is “by far” the company’s largest revenue driver, and reports suggest SpaceX may be positioning itself for an initial public offering as soon as next year, with valuations estimated as high as $1.5 trillion. Musk has also suggested in the past that Starlink could have its own IPO in the future. 

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NVIDIA Director of Robotics: Tesla FSD v14 is the first AI to pass the “Physical Turing Test”

After testing FSD v14, Fan stated that his experience with FSD felt magical at first, but it soon started to feel like a routine.

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Credit: Grok Imagine

NVIDIA Director of Robotics Jim Fan has praised Tesla’s Full Self-Driving (Supervised) v14 as the first AI to pass what he described as a “Physical Turing Test.”

After testing FSD v14, Fan stated that his experience with FSD felt magical at first, but it soon started to feel like a routine. And just like smartphones today, removing it now would “actively hurt.”

Jim Fan’s hands-on FSD v14 impressions

Fan, a leading researcher in embodied AI who is currently solving Physical AI at NVIDIA and spearheading the company’s Project GR00T initiative, noted that he actually was late to the Tesla game. He was, however, one of the first to try out FSD v14

“I was very late to own a Tesla but among the earliest to try out FSD v14. It’s perhaps the first time I experience an AI that passes the Physical Turing Test: after a long day at work, you press a button, lay back, and couldn’t tell if a neural net or a human drove you home,” Fan wrote in a post on X. 

Fan added: “Despite knowing exactly how robot learning works, I still find it magical watching the steering wheel turn by itself. First it feels surreal, next it becomes routine. Then, like the smartphone, taking it away actively hurts. This is how humanity gets rewired and glued to god-like technologies.”

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The Physical Turing Test

The original Turing Test was conceived by Alan Turing in 1950, and it was aimed at determining if a machine could exhibit behavior that is equivalent to or indistinguishable from a human. By focusing on text-based conversations, the original Turing Test set a high bar for natural language processing and machine learning. 

This test has been passed by today’s large language models. However, the capability to converse in a humanlike manner is a completely different challenge from performing real-world problem-solving or physical interactions. Thus, Fan introduced the Physical Turing Test, which challenges AI systems to demonstrate intelligence through physical actions.

Based on Fan’s comments, Tesla has demonstrated these intelligent physical actions with FSD v14. Elon Musk agreed with the NVIDIA executive, stating in a post on X that with FSD v14, “you can sense the sentience maturing.” Musk also praised Tesla AI, calling it the best “real-world AI” today.

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