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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.

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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.

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“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.

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 

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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 Model Y L gets biggest hint yet that it’s coming to the U.S.

Over the past week, a noticeable wave of American Tesla influencers descended on China and Australia, each posting in-depth YouTube reviews of the Model Y L within days of one another.

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Credit: Tesla China

The Tesla Model Y L is perhaps the most wanted vehicle in the company’s lineup in the United States, especially now that it is void of a true family vehicle with the removal of the Model X.

In China, Tesla currently offers a longer, more family-friendly version of the Model Y, known as the Model Y L, which is longer in terms of its wheelbase and larger in terms of interior space, making it the perfect option for those with a need for a tad more room than what the all-electric crossover offers in its Standard, Premium, and Performance trims.

However, there seems to be a hint that the Model Y L could be on its way to the United States. Over the past week, a noticeable wave of American Tesla influencers descended on China and Australia, each posting in-depth YouTube reviews of the Model Y L within days of one another:

The timing has sparked some intense speculation as to whether Tesla is quietly preparing to bring the long-wheelbase, three-row family SUV to North America after months of requests from fans.

The Model Y L stretches the wheelbase by about five inches compared to the standard Model Y.

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This delivers dramatically more rear legroom, optional captain’s chairs in the second row, and a true six- or seven-seat configuration ideal for growing families. Reviewers praise its refined ride, upgraded interior features like a rear touchscreen and premium audio, and competitive range—up to roughly 466 miles in some configurations.

Many observers see the coordinated influencer trip as more than a coincidence. Tesla China appears to have hosted the group, possibly tied to the Beijing Auto Show, giving U.S.-focused creators early access to hands-on footage aimed squarely at North American audiences.

Tesla Model Y lineup expansion signals an uncomfortable reality for consumers

Tesla watchers are quick to point out this isn’t the first time such a pattern has emerged.

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Just months earlier, American influencers were similarly invited to China to test-drive the refreshed Model Y Performance. Those videos dropped in the lead-up to the variant’s U.S. rollout, generating exactly the kind of pre-launch hype that helped smooth its September arrival in American showrooms.

The parallel is obviously hard to ignore, as Tesla has used overseas influencer trips before as a low-key way to build anticipation without formal announcements. With the Model Y L potentially hitting the U.S. market late this year, according to CEO Elon Musk, the timing would make sense.

Tesla Model Y L might not come to the U.S., and it’s a missed opportunity

Of course, it could still be coincidental. Tesla regularly invites creators to its Shanghai factory and events for broader promotional purposes, and the Model Y L has been on sale in China for some time. No official word has come from Tesla or Elon Musk about U.S. availability, pricing, or timing.

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Import tariffs, regulatory hurdles, and production priorities at Fremont or the new Mexican Gigafactory could still delay or alter any stateside plans.

Even so, the buzz is real. U.S. families have long asked for a more spacious, three-row Tesla SUV that doesn’t require stepping up to the larger Model X.

If the influencer campaign is any indication, the Model Y L—or a close North American cousin—could finally answer that call. For now, American Tesla fans are watching closely and wondering whether this latest China trip is just good content… or the opening act for something much bigger stateside.

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Tesla begins probing owners on FSD’s navigation errors with small but mighty change

Previously lumped under “Other,” these incidents made it harder for Tesla’s AI team to isolate and prioritize map-related issues in their reinforcement learning models. There was a lot of disagreement on how certain interventions should be reported.

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Tesla has started probing owners on how often its Full Self-Driving suite has Navigation errors with a small but mighty change last night.

In its latest Software Update, which is Version 2026.2.9.9 featuring Full Self-Driving (Supervised) v14.3.2, Tesla has introduced a targeted improvement to how owners will report interventions.

With the initial rollout of v14.3.2, Tesla introduced a new Intervention Menu that appears when a disengagement occurs. It allowed owners to choose from four different categories: Preference, Comfort, Critical, or Other.

Tesla has voided the Other option and replaced it with a new “Navigation” choice, which seems much more ideal given the complaints owners have had about navigation. This seemingly minor UI tweak, rolled out widely in recent days, marks another step in Tesla’s ongoing effort to refine its autonomous driving stack through precise, crowdsourced data.

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Tesla made this change in direct response to longstanding community feedback. For years, FSD users have noted that navigation errors—such as incorrect speed limits, suboptimal routes, or directing the vehicle to a building’s rear entrance instead of the main one—frequently force interventions.

Previously lumped under “Other,” these incidents made it harder for Tesla’s AI team to isolate and prioritize map-related issues in their reinforcement learning models. There was a lot of disagreement on how certain interventions should be reported:

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By adding a dedicated “Navigation” label, the company can now tag disengagements more accurately, feeding cleaner data into its neural networks. This supports faster iteration on routing algorithms, map accuracy, and intent-aware navigation.

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Community consensus around Tesla’s navigation system has been consistent and candid. While the end-to-end AI driving behavior in v14.x earns widespread acclaim for smoothness and safety, navigation remains FSD’s clearest Achilles’ heel.

Owners frequently cite outdated map data, failure to learn from repeated corrections, and routing decisions that feel less intuitive than Google Maps or Apple Maps. Common complaints include phantom speed-limit changes, inefficient local roads, and poor point-of-interest handling.

Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much

Many drivers report intervening on navigation far more often than on core driving maneuvers, with some estimating it accounts for the majority of disengagements outside of edge cases.

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Long-term users note that the same mapping glitches persist across years and software versions, despite thousands of collective miles of feedback. Yet the addition of the “Navigation” option has been met with optimism. It signals Tesla’s commitment to data-driven progress and suggests navigation improvements could arrive sooner.

For a community that already logs millions of FSD miles monthly, this small change could unlock meaningful gains in reliability and user trust—potentially accelerating the path to unsupervised autonomy.

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Tesla expands Robotaxi in a way that was long anticipated

Instead, it has to do with the consumer base it offers Robotaxi to, because it has not offered it to everyone in the past.

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Credit: Grok Imagine

Tesla has expanded Robotaxi in a way that was long anticipated, and it does not have to do with a new, larger geofence in a city where it already offered its partially autonomous ride-hailing suite, or a new city altogether.

Instead, it has to do with the consumer base it offers Robotaxi to, because it has not offered it to everyone in the past.

Tesla has taken a major step forward in its autonomous ride-hailing ambitions with the official launch of the Tesla Robotaxi app for Android users. Released on the Google Play Store on April 24. Titled simply “Tesla Robotaxi,” the app is now available to download directly from Tesla.

This rollout fulfills a long-anticipated expansion that opens the service to hundreds of millions of Android smartphone users who were previously unable to access it on iOS alone.

The app delivers a streamlined, driverless ride experience powered by Tesla’s automated driving technology.

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Users sign in with a Tesla Account, view the current service area map within the app, enter a destination, and receive an estimated fare and arrival time before confirming the ride. When a Model Y from the Robotaxi fleet arrives, riders confirm the license plate, enter the vehicle, fasten their seatbelt, and tap “Start Ride” on either the app or the vehicle’s touchscreen.

During the trip, passengers have access to all the same controls that iOS users do, and can adjust climate settings, seat positions, and music while tracking progress on an in-app map. The interface also allows drop-off changes or support requests if needed. After the ride, users exit, close the doors, and submit feedback.

This Android availability directly broadens the rider base for Robotaxi in its initial service areas. Unfortunately, Android users are used to being subject to delayed launches of new features available to Tesla owners.

By removing the iOS-only barrier, Tesla instantly expands the addressable market, enabling far more people to summon and use the autonomous vehicles already operating on public roads.

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The move is a foundational requirement for scaling ride volume and gathering the real-world data needed to refine the unsupervised Full Self-Driving system that powers every trip.

For the Robotaxi program itself, the launch signals steady operational progress. It prepares the service for higher utilization rates as the fleet grows and supports the transition from limited early deployments to a more robust network.

Tesla expands Unsupervised Robotaxi service to two new cities

Tesla has indicated that users outside current service areas can sign up at the company’s website for future notifications, pointing to a deliberate, phased geographic rollout.

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Looking ahead, the company plans to incorporate Cybercab vehicles to increase fleet capacity and efficiency while continuing to expand service territories. With the Android app now live, Tesla has removed a key adoption hurdle and positioned Robotaxi for the next phase of growth in autonomous urban transportation.

The infrastructure is now in place to support significantly larger rider demand as production and deployment accelerate.

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