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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.

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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Tesla Robotaxi gets a massive upgrade in Nevada

Nevada regulators just approved a massive expansion of Tesla’s robotaxi fleet across the entire county.

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Concept art of a Tesla Cybercab in Las Vegas Strip as rendered via Grok

Tesla’s robotaxi footprint in Nevada just grew by roughly 500 times in a single regulatory vote.

The Nevada Transportation Authority approved Tesla’s full Autonomous Vehicle Network Company permit on Thursday, clearing the way for the company to deploy up to 5,000 driverless vehicles across Clark County over the next 12 months. The decision came during a four hour general session meeting that Tesla investor Sawyer Merritt watched live and reported on X, noting the vote replaces the interim order that had limited Tesla to just 10 robotaxis on a narrow stretch of the Las Vegas Strip.

That earlier cap, covered here after it surfaced on August 13, came with restrictions that looked stricter than what Tesla runs in Austin: a 45 mph speed ceiling, no airport pickups, and a geofence confined to the Strip corridor. The new approval extends Tesla’s operating authority to all of Clark County, with room to request an even wider geofence across the state.

Tesla representatives at the meeting said they have no intention of putting 5,000 cars on the road right away. Commercial rides are expected to start within 30 days, pending vehicle inspections, insurance filings, and fare approval, the standard steps every robotaxi operator in Nevada has had to clear.

Tesla’s own Robotaxi account replied to the news with a short line, The golden future is upon us.

The timing lines up with Tesla’s broader robotaxi push this month. The company is preparing to open Cybercab rides to the public in Austin as soon as this month, and it opened a sweepstakes for riders to win a seat at the launch event. Tesla filed its original application for a 5,000 vehicle Nevada fleet back in June, a request regulators trimmed to 10 vehicles when they issued the interim order in July. Thursday’s vote effectively grants the number Tesla asked for from the start.

Zoox, the Amazon owned robotaxi operator, has run in Nevada since 2025 and was capped at 100 vehicles before Thursday’s decision. Tesla’s new ceiling puts it well ahead of that comparison on paper, though the company has said its actual fleet size will depend on how quickly FSD v15 rolls out, the software update executives have called the gateway to scaling unsupervised robotaxi operations nationwide.

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Tesla admits to slow Model Y Robotaxi integration, but for a good reason

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Credit: Tesla

Tesla welcomed JPMorgan analysts to one of its factories earlier this month, with the Wall Street firm highlighting its findings in a new note to investors. One of the more pertinent pieces of information is that Tesla admitted to slowly integrating Model Y vehicles into its Robotaxi fleet, but it has a good reason.

JPMorgan analysts recently toured Tesla’s Fremont Factory and met with the company’s investor relations team, emerging with a clearer picture of the automaker’s Robotaxi strategy. According to the bank’s note, Tesla is intentionally limiting the addition of Model Y vehicles to its existing Robotaxi fleet.

The firm’s analysts said:

“Tesla indicated it is intentionally holding back on adding Model Y units to the robotaxi fleet, expressing confidence in its ability to scale Cybercab in the near-term. On FSD V15, Tesla views this release as a step-change in performance, comparable to the leap from V13 to V14. The V15 upgrade encompasses seven core technologies, with ~40% of those currently being tested in the robotaxi fleet, where initial feedback has been encouraging.”

Far from signaling delays or doubts about autonomy, the move reflects strong management confidence in the near-term scalability of the purpose-built Cybercab.

Tesla has operated its Robotaxi service primarily with modified Model Ys since launching in Austin and expanding to other markets. Yet the company is now deliberately holding back further Model Y conversions. The rationale is straightforward: leadership believes the Cybercab, a two-seat, steering-wheel- and pedal-free vehicle optimized for high utilization, can ramp production and deployment more efficiently in the coming months.

This dedicated form factor promises better unit economics for the majority of rides, which typically involve one or two passengers, while freeing consumer Model Y inventory for retail sales.

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Supporting this pivot is Full Self-Driving (FSD) software version 15, which Tesla describes as a genuine step-change in performance, comparable to the leap from V13 to V14. The update incorporates seven core technologies; roughly 40 percent are already undergoing real-world testing in the current Robotaxi fleet, with early feedback described as encouraging.

Tesla is carefully managing software development to minimize regressions in core driving functions as new capabilities are added. Management positions V15 as the primary gateway to scaling unsupervised FSD. Importantly, the existing AI and Hardware 4 stack is already capable of running V15 and supporting unsupervised operation.

Cybercab itself is only the first vehicle on the platform. Tesla reiterated that additional form factors will follow, pointing to concepts such as the earlier “Robovan” demonstration as examples of how the architecture can evolve.

Tesla’s mysterious Robovan makes a sneak peek with Optimus in Terafab video

Parallel progress continues on the Optimus humanoid robot, which remains on track for start of production in the coming months, with commercial sales possible as early as the second half of 2027. Generation 3 details will be revealed closer to production to preserve competitive advantages, while Generation 4 scope will draw on real-world Gen 3 experience.

JPMorgan left the meeting with a deeper appreciation for Tesla’s manufacturing automation and maintained its $475 price target. The decision to slow Model Y Robotaxi integration is therefore not a setback but a calculated prioritization of a more efficient, purpose-built solution that management believes is ready to scale.

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Elon Musk gives a timeline for SpaceX’s first Starship catch attempt

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SpaceX Starship V3 from Starbase, Texas on April 14, 2026

SpaceX CEO Elon Musk announced today that the company will likely attempt to catch the Starship upper stage with its launch tower arms “in a few months.”

In a post on X, Musk wrote, “Looks like we will probably catch the ship with the tower in a few months. If there had been a tower out to sea where we practiced landing the ship, it would have been caught.” He added that the first reflight of a Starship vehicle is expected by the end of 2026 or early 2027, describing it as “a fork in the road of history for consciousness reaching the stars.”

Musk’s prediction comes amid ongoing progress toward full reusability of the Starship system, a two-stage rocket designed for rapid turnaround and dramatically lower launch costs. Catching the upper stage, known simply as “ship,” with the Mechazilla tower’s mechanical arms would mark a major milestone. It would allow both stages to return directly to the launch site for quick refurbishment and reuse, eliminating the need for ocean recovery.

Musk has previously signaled plans for a ship catch. In July, shortly after SpaceX’s wildly successful Starship 13 mission, he stated that the company would attempt to catch the ship with the tower on the next flight unless problems emerged in the mission data review. Earlier comments also outline conditions such as successful soft ocean landings before attempting a land recovery to minimize risk.

SpaceX has solved Starship’s biggest challenge, Elon Musk says

The latest update from Musk adjusts this timeline to a few months, reflecting the iterative nature of the test campaign.

SpaceX has already demonstrated the tower catch technique successfully with the Super Heavy booster on a couple of occasions. The first successful booster catch occurred during Flight 5 in October 2024, when the massive first stage returned to the Starbase pad in Texas and was plucked from the air by the tower arms.

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Additional catches followed on later flights, including Flight 7, proving the concept for the booster and building confidence in the system as a whole.

Achieving a similar catch for the upper stage would represent a significant step forward. The ship returns from much higher speeds and greater heat loads after orbital or near-orbital flight. Success would advance SpaceX’s goal of full and rapid reusability, potentially reducing the cost of access to orbit by a factor of 100 or more and supporting ambitions for frequent satellite deployments, lunar missions, and eventual Mars flights.

Musk has long emphasized that true reusability, refueling rather than discarding hardware, is essential for making humanity a multi-planetary species.

As SpaceX continues refining Starship through successive test flights, the coming months will test whether the ambitious catch timeline can be met. The combination of prior booster successes and improving ship landing precision suggests the company is steadily closing in on this historic capability.

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