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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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Elon Musk

Celebrating SpaceX’s Falcon Heavy Tesla Roadster launch, seven years later (Op-Ed)

Seven years later, the question is no longer “What if this works?” It’s “How far does this go?”

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SpaceX's first Falcon Heavy launch also happened to be a strategic and successful test of Falcon upper stage coast capabilities. (SpaceX)

When Falcon Heavy lifted off in February 2018 with Elon Musk’s personal Tesla Roadster as its payload, SpaceX was at a much different place. So was Tesla. It was unclear whether Falcon Heavy was feasible at all, and Tesla was in the depths of Model 3 production hell.

At the time, Tesla’s market capitalization hovered around $55–60 billion, an amount critics argued was already grossly overvalued. SpaceX, on the other hand, was an aggressive private launch provider known for taking risks that traditional aerospace companies avoided.

The Roadster launch was bold by design. Falcon Heavy’s maiden mission carried no paying payload, no government satellite, just a car drifting past Earth with David Bowie playing in the background. To many, it looked like a stunt. For Elon Musk and the SpaceX team, it was a bold statement: there should be some things in the world that simply inspire people.

Inspire it did, and seven years later, SpaceX and Tesla’s results speak for themselves.

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Credit: SpaceX

Today, Tesla is the world’s most valuable automaker, with a market capitalization of roughly $1.54 trillion. The Model Y has become the best-selling car in the world by volume for three consecutive years, a scenario that would have sounded insane in 2018. Tesla has also pushed autonomy to a point where its vehicles can navigate complex real-world environments using vision alone.

And then there is Optimus. What began as a literal man in a suit has evolved into a humanoid robot program that Musk now describes as potential Von Neumann machines: systems capable of building civilizations beyond Earth. Whether that vision takes decades or less, one thing is evident: Tesla is no longer just a car company. It is positioning itself at the intersection of AI, robotics, and manufacturing.

SpaceX’s trajectory has been just as dramatic.

The Falcon 9 has become the undisputed workhorse of the global launch industry, having completed more than 600 missions to date. Of those, SpaceX has successfully landed a Falcon booster more than 560 times. The Falcon 9 flies more often than all other active launch vehicles combined, routinely lifting off multiple times per week.

Falcon Heavy successfully clears the tower after its maiden launch, February 6, 2018. (Tom Cross)

Falcon 9 has ferried astronauts to and from the International Space Station via Crew Dragon, restored U.S. human spaceflight capability, and even stepped in to safely return NASA astronauts Butch Wilmore and Suni Williams when circumstances demanded it.

Starlink, once a controversial idea, now dominates the satellite communications industry, providing broadband connectivity across the globe and reshaping how space-based networks are deployed. SpaceX itself, following its merger with xAI, is now valued at roughly $1.25 trillion and is widely expected to pursue what could become the largest IPO in history.

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And then there is Starship, Elon Musk’s fully reusable launch system designed not just to reach orbit, but to make humans multiplanetary. In 2018, the idea was still aspirational. Today, it is under active development, flight-tested in public view, and central to NASA’s future lunar plans.

In hindsight, Falcon Heavy’s maiden flight with Elon Musk’s personal Tesla Roadster was never really about a car in space. It was a signal that SpaceX and Tesla were willing to think bigger, move faster, and accept risks others wouldn’t.

The Roadster is still out there, orbiting the Sun. Seven years later, the question is no longer “What if this works?” It’s “How far does this go?”

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Energy

Tesla launches Cybertruck vehicle-to-grid program in Texas

The initiative was announced by the official Tesla Energy account on social media platform X.

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Credit: Tesla

Tesla has launched a vehicle-to-grid (V2G) program in Texas, allowing eligible Cybertruck owners to send energy back to the grid during high-demand events and receive compensation on their utility bills. 

The initiative, dubbed Powershare Grid Support, was announced by the official Tesla Energy account on social media platform X.

Texas’ Cybertruck V2G program

In its post on X, Tesla Energy confirmed that vehicle-to-grid functionality is “coming soon,” starting with select Texas markets. Under the new Powershare Grid Support program, owners of the Cybertruck equipped with Powershare home backup hardware can opt in through the Tesla app and participate in short-notice grid stress events.

During these events, the Cybertruck automatically discharges excess energy back to the grid, supporting local utilities such as CenterPoint Energy and Oncor. In return, participants receive compensation in the form of bill credits. Tesla noted that the program is currently invitation-only as part of an early adopter rollout.

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The launch builds on the Cybertruck’s existing Powershare capability, which allows the vehicle to provide up to 11.5 kW of power for home backup. Tesla added that the program is expected to expand to California next, with eligibility tied to utilities such as PG&E, SCE, and SDG&E.

Powershare Grid Support

To participate in Texas, Cybertruck owners must live in areas served by CenterPoint Energy or Oncor, have Powershare equipment installed, enroll in the Tesla Electric Drive plan, and opt in through the Tesla app. Once enrolled, vehicles would be able to contribute power during high-demand events, helping stabilize the grid.

Tesla noted that events may occur with little notice, so participants are encouraged to keep their Cybertrucks plugged in when at home and to manage their discharge limits based on personal needs. Compensation varies depending on the electricity plan, similar to how Powerwall owners in some regions have earned substantial credits by participating in Virtual Power Plant (VPP) programs.

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Samsung nears Tesla AI chip ramp with early approval at TX factory

This marks a key step towards the tech giant’s production of Tesla’s next-generation AI5 chips in the United States.

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Tesla-Chips-HW3-1
Image used with permission for Teslarati. (Credit: Tom Cross)

Samsung has received temporary approval to begin limited operations at its semiconductor plant in Taylor, Texas.

This marks a key step towards the tech giant’s production of Tesla’s next-generation AI5 chips in the United States.

Samsung clears early operations hurdle

As noted in a report from Korea JoongAng Daily, Samsung Electronics has secured temporary certificates of occupancy (TCOs) for a portion of its semiconductor facility in Taylor. This should allow the facility to start operations ahead of full completion later this year.

City officials confirmed that approximately 88,000 square feet of Samsung’s Fab 1 building has received temporary approval, with additional areas expected to follow. The overall timeline for permitting the remaining sections has not yet been finalized.

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Samsung’s Taylor facility is expected to manufacture Tesla’s AI5 chips once mass production begins in the second half of the year. The facility is also expected to produce Tesla’s upcoming AI6 chips. 

Tesla CEO Elon Musk recently stated that the design for AI5 is nearly complete, and the development of AI6 is already underway. Musk has previously outlined an aggressive roadmap targeting nine-month design cycles for successive generations of its AI chips.

Samsung’s U.S. expansion

Construction at the Taylor site remains on schedule. Reports indicate Samsung plans to begin testing extreme ultraviolet (EUV) lithography equipment next month, a critical step for producing advanced 2-nanometer semiconductors.

Samsung is expected to complete 6 million square feet of floor space at the site by the end of this year, with an additional 1 million square feet planned by 2028. The full campus spans more than 1,200 acres.

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Beyond Tesla, Samsung Foundry is also pursuing additional U.S. customers as demand for AI and high-performance computing chips accelerates. Company executives have stated that Samsung is looking to achieve more than 130% growth in 2-nanometer chip orders this year.

One of Samsung’s biggest rivals, TSMC, is also looking to expand its footprint in the United States, with reports suggesting that the company is considering expanding its Arizona facility to as many as 11 total plants. TSMC is also expected to produce Tesla’s AI5 chips. 

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