Dmitri Dolgov

WAYMO EXPANDS BAY AREA ROBOTAXI SERVICE ACROSS PENINSULA & SILICON VALLEY Waymo continues to lead the autonomous vehicle industry with its latest expansion of robotaxi services across the Peninsula and Silicon Valley. •Waymo’s fully driverless rides are now available in San Mateo, Santa Clara, Sunnyvale, and Mountain View, connecting key tech hubs. •The autonomous vehicle industry is projected to surpass $1.2 trillion globally by 2030, with AI-powered robotaxis transforming urban mobility. •Waymo, backed by Alphabet, has logged over 20 million autonomous miles on public roads, setting the industry standard for safety and innovation. •The Bay Area remains a focal point for AI-driven transportation, fueling economic growth, job creation, and cutting-edge research. #AI #AutonomousVehicles #Waymo #Robotics #SelfDriving #TechNews #SiliconValley #Mobility #Innovation

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𝗪𝗵𝗲𝗻 𝗱𝗶𝗱 “𝗶𝗹𝗹𝗲𝗴𝗮𝗹” 𝗴𝗲𝘁 𝗿𝗲𝗯𝗿𝗮𝗻𝗱𝗲𝗱 𝗮𝘀 “𝗮𝘀𝘀𝗲𝗿𝘁𝗶𝘃𝗲”? Waymo’s autonomous cars used to be the straight-A students of the road. Now they’re making illegal U-turns and other violations — not accidentally, but because someone decided the system should behave that way. 𝗟𝗲𝘁’𝘀 𝘀𝘁𝗼𝗽 𝗽𝗿𝗲𝘁𝗲𝗻𝗱𝗶𝗻𝗴 𝘁𝗵𝗶𝘀 𝗶𝘀 “𝗔𝗜 𝗯𝗲𝗰𝗼𝗺𝗶𝗻𝗴 𝗮𝘀𝘀𝗲𝗿𝘁𝗶𝘃𝗲.” AI isn’t making these choices. 𝗛𝘂𝗺𝗮𝗻𝘀 𝗮𝗿𝗲. The problem isn’t autonomous cars going rogue. The problem is the humans training them like cutting corners is a feature, not a flaw. We’ve spent years worrying about AI turning dangerous… but maybe the real risk is humans encoding their worst impulses into the systems we’re supposed to trust. Everyone keeps calling for regulation on AI. But look closely: 𝗧𝗵𝗲 𝗿𝗲𝗴𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝘄𝗲 𝗿𝗲𝗮𝗹𝗹𝘆 𝗻𝗲𝗲𝗱 𝗶𝘀 𝗼𝗻 𝘁𝗵𝗲 𝗵𝘂𝗺𝗮𝗻𝘀 𝗶𝗻 𝗰𝗵𝗮𝗿𝗴𝗲. Because if the values going in are compromised, the outputs will be, too — no matter how “intelligent” the system becomes. https://lnkd.in/eRJ_pUXP

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🚗💡 The Autonomous Vehicle (AV) industry is really starting to take shape, and the latest partnership between Waymo and Toyota is a big step forward. Their strategic collaboration aims to redefine the future of transportation, with a focus on innovation, safety, and scalability. As leaders in the tech and automotive sectors continue to converge, it's exciting to see how these partnerships will accelerate the development of AVs and their integration into our daily lives. This is just the beginning, and the road ahead is filled with opportunities to revolutionize how we think about mobility. #AutonomousVehicles #Innovation #Partnerships #Waymo #Toyota https://lnkd.in/gmqd-mC8

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In the robotaxi race between Google's Waymo and Tesla, we are already seeing the different strategy between both companies. Waymo needs previously mapped out roads and goes city by city, whereas Tesla doesn't because it has real drivers showing its AI every day how to drive. Now the state of Texas has given Tesla a state wide license. Provided the software is ready, this means all owners of newer Tesla's could send their car to earn money for them. This could be tens of thousands vehicles. Imagine Tesla in 2026 being able to produce thousands of cars each week which can drive out of the factory and start offering ridesharing services. The economical model can be that you pay for a Tesla a monthly fee but if you let it join the Tesla Network more than a certain percentage, it potentially can earn more than you pay. So free Teslas are possible. Tesla would only have to show this on some small scale for potentially large financial groups to negotiate buying millions of cars. Car ownership would be a thing of the past. Car insurance, service stations, public parking, Uber, ... could all disappear in the next 5 years. AI is going to transform society more in the next 5 years than any technology has in the last 100. Are you ready for the AI revolution? https://lnkd.in/ewV9KtWU

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WAYMO ACHIEVES MILLION-MILE VALIDATION FOR ITS AUTONOMOUS SYSTEM Waymo has announced that its autonomous driving system has completed over 1 million miles of validated real-world testing under regulatory standards. These miles span diverse environments, including urban centers, highways, and rural roads, strengthening the safety and reliability of Waymo’s driverless technology. The company reports a 70% reduction in accident rates compared to human drivers in similar conditions. This achievement brings Waymo closer to expanding fully autonomous ride-hailing services at scale. #Waymo #AutonomousVehicles #AI #Mobility #Innovation #TransportationTech #Sustainability

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Robotaxis may be scaling, but drivers aren’t slowing down. In markets like San Francisco and Phoenix, AVs are starting to roll out at scale. But according to Gridwise Analytics data cited by Axios, driver activity and earnings remain steady, even with autonomous fleets entering the mix. Thank you to the Axios team for the mention in this piece, which explores how gig drivers are navigating this transition. For now, AVs are supplementing, not replacing, human labor. As demand for ride-hailing continues to grow, understanding how AVs and human labor coexist will be a key storyline in the coming years. If you're digging into the numbers, here are two pieces that go deeper. 2025 Gridwise Analytics 2025 Annual Gig Mobility Report: https://lnkd.in/dQjXXSKc Gridwise x S&P Global Mobility AV Whitepaper: https://lnkd.in/dJF3Hp6M post&utm_campaign=organic linkedin Read the full article on Axios here: https://lnkd.in/dvynSv9T #GigEconomy #AVs #UrbanMobility #DriverData #GridwiseAnalytics #FutureOfWork #RideshareTrends

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AI: Friend or Foe? It depends on where you ask the question. In San Francisco and LA, Waymos have literally been burned. Fear, skepticism, and frustration boiled over into acts of destruction. AVs are easy targets of societal frustration that don't fight back (for now). But in Phoenix, Austin, and Atlanta? Waymos are quietly operating, shuttling people around without the same backlash. So why the difference? * Culture & perception: Tech-saturated SF sees every experiment on its streets. In newer markets, people just see the utility. * Trust vs tension: Communities that feel AI is “for them” treat it as a friend. Communities that feel it’s “done to them” see a foe. * Framing matters: If the story is disruption, people resist. If the story is service, people adopt. AI is neither friend nor foe on its own - it’s how we roll it out, communicate it, and earn trust that decides the outcome. 🔥 In your city - do you see people lighting the match to AI or will they enjoy the ride?

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Tesla just expanded their Robotaxi geofence in ATX. It's now 243 square miles, 3.7x larger than Waymo's. However, the Robotaxi fleet is only 25% of Waymo's size. And there remains human supervisors in the car during rides. I think this is a regulatory thing. Does Tesla's lack of mapping and simpler sensor suite mean that it can move faster and expand more than Waymo? Elon certainly thinks so.... "Tesla autonomous driving might spread faster than any technology ever. The hardware foundations have been laid for such a long time that a software update enables self-driving for millions of pre-existing cars in a short period of time."

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Waymo raising capital at this scale reflects how the autonomous vehicle conversation has evolved. The problem is no longer model capability. It is operational depth. Autonomy today is constrained by questions of reliability, deployment economics, regulatory coordination, and public safety at scale. Once vehicles move beyond pilots and into daily city operations, the complexity shifts from algorithms to systems. Fleet management, incident handling, infrastructure variability, and long-term cost structures begin to dominate outcomes. Large funding rounds signal that the market understands this transition. Capital is being allocated not to prove feasibility, but to sustain execution across geographies and conditions. The next phase will separate technical achievement from commercial durability. Expansion will expose unit economics, insurance frameworks, and the true cost of maintaining consistency across environments. For the ecosystem, this is a familiar inflection point. Early breakthroughs are behind us. What remains is the harder work of turning autonomy into dependable infrastructure. That is where long-term value will be decided. #waymo #funding #tech

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Bad press around autonomous driving is inevitable. Especially when a headline involves a child. Recently, Waymo faced intense scrutiny after one of its vehicles struck a child near a school. The child was thankfully only lightly injured, but the story spread fast, and the reaction was strong. As it should be. What’s getting less attention is the uncomfortable nuance. According to Waymo’s data, the system detected the child immediately, braked hard, and reduced speed significantly before impact. Their internal analysis suggests a typical human driver, even an attentive one, would likely have hit the child at a much higher speed given the same conditions. That does not make the incident acceptable. But it does challenge the way we frame these conversations. We tend to ask: “Did the autonomous system fail?” We rarely ask: “Compared to what baseline?” Human driving sets a very low bar. We just don’t notice it because human errors are normalized. The real question isn’t whether autonomous systems are perfect. They’re not. It’s whether they can consistently make fewer and less severe mistakes than humans, especially in chaotic, high-risk environments like school zones. Public scrutiny is necessary. Transparency is non-negotiable. But progress in safety often looks worse before it looks better, because machine mistakes are visible, logged, and headline-worthy in a way human mistakes never are. If we want safer streets, the comparison has to be honest.

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Human drivers make mistakes.  Algorithms learn from them. Waymo is quietly rewriting the rules of road safety. Just read Waymo’s latest safety report—50 million self-driven miles across Phoenix and SF. And the numbers are surprisingly solid. → 88% fewer property damage claims compared to human-driven cars. → Only 13 airbag-triggering crashes (vs. 78 expected with humans) → Just 36 crashes with injuries (vs. 190 projected)—that’s an 81% reduction. Waymo also ran a model with Swiss Re. Humans would've triggered 26 insurance claims. Waymo triggered just 2. What's even more impressive is, most of the incidents weren’t even Waymo’s fault. — One got hit during a police chase.  — Another, rear-ended while waiting at a red light. Earlier this year, there was a software recall (it misinterpreted objects like gates and chains), but it was resolved quickly and caused no injuries. While we’re still debating whether we’d ever trust a driverless car, these vehicles are already logging millions of miles, learning as they go— and in many cases, outperforming us. It made me wonder: What if the safest “drivers” of the future don’t drive at all? Not saying we’re fully there yet. But 50 million miles in, it’s worth paying attention. Would you trust it with your commute?

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Waymo's Approach to Self-Driving: Building the World's Greatest Driver As Waymo gears up to start testing in NYC, here is Co-CEO Tekedra N. Mawakana explaining their "One Driver" approach at last year's All-In Summit: " We drive in a week more than a human drives in a lifetime." "You can say that as a company that runs fleets, but we're the only company where it's one driver." "That's not the way the world is organized right now." "Everyone has a lot of drivers, and all of those drivers have different capabilities." "This is one driver learning all the time in unison." "What can we demonstrate that's possible?" "What are policy makers five years from now really going to want to know and how will they be able to derive from what we're doing today?" Recorded at the 2024 All-In Summit Join us at the 2025 All-In Summit: allin.com/summit #selfdriving #ai #autonomousvehicles #waymo #robotaxi #cars #future #startups #tech #allin #podcast #clips

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Waymo just raised $16 billion at a $126 billion valuation. But the real story isn't in the fundraise. It's in the talent war hiding in plain sight. We analyzed compensation data across the entire Automotive & AV sector, from legacy automakers to autonomous driving pure-plays. What we found tells you everything about who's positioned to win. At the entry level, the gap is noticeable. At staff level, it's a canyon. And pay ranges widening is characteristic of how pay bands evolve as you go higher up in level. Waymo, Aurora, and Zoox are paying senior engineers $400K-$500K+. Staff engineers at Waymo are clearing $700K-$900K. Meanwhile, Ford and GM hover around $150K-$250K for similar roles. That's not a compensation gap. That's a statement about where the future is being built. The graphic below highlights pay at different normalized levels via the Levels.fyi software engineer standard level set between 2024 and 2025 so we can compare companies apples to apples. The companies treating AI and autonomy as their core product (not a side project) are paying accordingly. They understand that the engineers who can make a car drive itself are among the scarcest, most valuable people in tech. Pay has to match. When Waymo says they achieved a 90% reduction in serious injury crashes across 127 million autonomous miles, those aren't just safety stats. They're the compound result of world-class engineering talent, retained over years, solving problems no one else can solve. The fundraise validates it. The comp data proves it. The autonomous vehicle race won't be won by who has the most cars in production right now. It'll be won by who has the best engineers, and who can keep them. Curious how your team stacks up? We built a benchmark tool to crunch cohorts like this across any industry, level, or location: https://lnkd.in/gC4EGrB7

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Amazon’s Zoox: Redefining Safety & Trust in the Robotaxi Race 🚖 The future of urban mobility is taking shape in Fremont, California—where Amazon-owned Zoox has just achieved a historic milestone: certification that its robotaxi meets the highest U.S. crash safety standards. While competitors like Waymo and Cruise have already rolled out limited robotaxi services in Phoenix and San Francisco, Zoox has chosen a different path—designing a purpose-built, autonomous vehicle from the ground up. No steering wheel. No pedals. Just a spacious, four-passenger cabin that moves forward or backward with equal ease. 🔑 What Makes Zoox Different? Safety First, Not Speed to Market: With oversight by former NHTSA chief Mark Rosekind, Zoox has built in 100+ safety innovations—including a groundbreaking horseshoe airbag system that protects passengers from all sides. Design for Experience: By eliminating traditional driving controls, the cabin feels less like a car ride and more like a shared, high-tech transit space. Sustainable & Scalable: Its 132 kWh battery enables 16 hours of operation per day, supporting urban ride-sharing without frequent downtime. Amazon’s Patience: Unlike venture-backed startups chasing short-term returns, Zoox has Amazon’s financial muscle and time horizon—prioritizing long-term trust over quick wins. 🚦 The Road Ahead Zoox still needs regulatory approval from California DMV and U.S. DOT before commercial rides begin. Incidents involving other robotaxis have heightened scrutiny, but Zoox’s cautious, safety-first approach may give it an edge in building public trust. 🌍 Why This Matters Urban transportation is a multi-trillion-dollar market, ripe for disruption. A safe, scalable, electric, and autonomous mobility system could transform how cities move—not just reducing congestion, but also cutting emissions and redefining accessibility. For Amazon, Zoox isn’t a “get-rich-quick” play—it’s a decade-long bet on the mobility revolution. And for the rest of us, it’s a signal that the future of transportation is closer than we think. 💡 My takeaway: In innovation, trust is the ultimate currency. Zoox shows that winning in autonomous mobility isn’t about being first—it’s about being safe, reliable, and human-centered. #AutonomousVehicles #Innovation #Amazon #FutureOfMobility #Safety

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When it comes to autonomous driving, Tesla and Waymo couldn’t be more different in how they approach the problem, and what they believe it will take to solve it. Waymo is all-in on the “hardware-heavy” school of thought: LiDAR, radar, HD maps, redundant compute, and highly curated geo-fenced environments. It’s a masterpiece of engineering, no doubt. And it works, but only in specific cities, under tightly controlled conditions, and with a very high operational cost. Tesla, on the other hand, is betting on vision and scale. No LiDAR. No HD maps. Just neural networks trained on billions of real-world miles, constantly updated from a global fleet of cars. Less hardware. Lower cost. More scale. And most importantly, a direct path to consumer vehicles, not just robotaxi pilots. From a tech perspective, the contrast is clear: • Waymo builds autonomy like it’s building a #NASA mission. • Tesla builds it like it’s scaling a #smartphone feature. I’m leaning toward Tesla’s approach, not because it’s perfect, but because it’s data-rich, less dependent on expensive hardware, and more #economically viable in the long run. Of course, the race isn’t over. #Regulations, edge cases, and safety validation will shape the outcome. But if autonomy is ultimately a software problem at scale, I think Tesla may be closer than we think. HITEC Angeles Investors The Tech Series Porsche AG Pirelli NASA - National Aeronautics and Space Administration General Motors Rivian BYD U.S. Department of Transportation OpenAI

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