Seval Oz

Autonomy is heating up. 🔥 Waymo just announced it’s launching in Atlanta — another major market stepping into the driverless future. 🚗⚡ As more cities light up for AVs, one thing becomes clear: The curb isn’t ready… but it needs to be. OpenCurb OS is built to orchestrate the chaos behind the scenes — coordinating pickups, drop-offs, and deliveries for AVs at scale. From Austin to Atlanta, we’re ready to help the world’s busiest parking lots become autonomy-ready infrastructure. Let’s make the curb the smartest part of the city. 🔗 Source: Waymo on X https://lnkd.in/gzAj84EC 📍Learn more: https://lnkd.in/gJKu2Y8S

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Autonomous vehicles spent years in pilot mode—never quite arriving. But if you ask a San Franciscan in 2025, that’s all changed. In SF, Waymo now accounts for 27% of rideshare bookings (!!), surpassing Lyft to become the second-largest operator in the market (per the below Bond Cap report). For public safety leaders in other big cities, this shift signals both opportunity and responsibility. AVs seem to deliver better safety outcomes over millions of miles driven—fewer crashes, fewer injuries per some studies—but also challenge how cities think about traffic enforcement, infrastructure, and emergency response in a world with fewer drivers. From an emergency management perspective, partnering with AV fleet deployers could unlock new capabilities: dynamic rerouting to clear lanes or areas for emergency vehicles, real-time passenger notifications, and coordinated evacuation at fleet scale. Yet city-scale driverless fleets also introduce an expanded set of vulnerabilities—and we can’t afford to be reactive. Proactive engagement and planning will be key to helping AVs support, rather than undermine, urban safety and resilience. Link to source: https://lnkd.in/eiPSSG-f

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Robotaxis Revolutionize Urban Mobility The year 2025 marks a pivotal moment for autonomous transportation as robotaxis become accessible to the public in more than a dozen cities worldwide. After years of rigorous beta testing, companies like Waymo, Cruise, and others have received the green light from regulators to expand their fleets, allowing users to hail self-driving vehicles seamlessly via mobile apps. This breakthrough stems from advancements in AI, sensor technology, and mapping systems that enable these vehicles to navigate complex urban environments safely. The integration of lidar, radar, and cameras ensures real-time decision-making, reducing human error which contributes to most road accidents. Competition in the sector has intensified, with major players investing billions to refine their technologies and expand geographically. For instance, services that were once limited to select areas in the US have now spread to cities in Europe and Asia, demonstrating the global scalability of #robotaxi operations. Beyond convenience, robotaxis address urban challenges such as traffic congestion and pollution by optimizing routes and promoting shared rides. Early data from operational cities shows decreased wait times and improved accessibility for underserved communities. As adoption grows, ongoing regulatory oversight ensures safety standards are met, with real-time monitoring and over-the-air updates preventing potential issues. This evolution not only transforms personal mobility but also paves the way for integrated smart city infrastructures. What are your thoughts on the rise of robotaxis? Would you trust a self-driving taxi for your daily commute? Share your experiences or concerns below! #Robotaxis #AutonomousVehicles #UrbanMobility #TechInnovation #FutureTransport

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Autonomy Markets: Is Autonomous Vehicle Growth a Zero-Sum Game for Uber?📉📈 Waymo just repriced the robotaxi market with a $126B valuation. Meanwhile, Uber released an earnings supplement on autonomous vehicles featuring a Myths vs. Realities section highlighting that in their opinion autonomous vehicles will expand the total addressable market, benefiting the company. The Debate: The Bull Case 🐂: If the market expands 30x due to lower costs and higher safety, Uber wins even with a smaller market share. The Bear Case 🐻: Once consumers experience the consistency of a dedicated autonomous vehicle network, they won't want to go back to a hybrid network. Personal ownership and dedicated fleets will eat into Uber's market share over time. Are you a bull or a bear? Let us know in the comments below. Autonomy Markets is co-hosted by Grayson Brulte and Walter Piecyk.

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Elon Musk said Tesla's robotaxis would likely be available to "half the population of the U.S." by the end of this year, soon after launching a test service for select fans in Austin this summer. Waymo launched a similar trial robotaxi service more than eight years ago and now operates in areas with about 3% of the U.S. population. Musk aims for growth at a "hyper-exponential rate," while Waymo has spent years fine-tuning its technology in different cities before opening to the general public. "There is a lot of risk in doing this incorrectly," according to a Waymo executive. The two companies' approaches to the robotaxi business are starkly different in how they use technology and plan to enter new markets. Chris Kirkham, Rachael Levy, and I look at how this could shape the future of driverless taxis. https://lnkd.in/g8HRc5-Q

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Swiftly ascending from local roots to international stage: As highlighted in our note From Horsepower to Brainpower – AI Takes the Wheel, lessons learned from EV disruption should make vehicle autonomy possible for global players. So far, China and the US robotaxi ecosystems are leading the global narrative of L4+ robotaxis via a more established food chain. Recent legislation in the US pushing robotaxis could keep Beijing steadfast in its efforts to grow the robotaxi market, making significant strides in developing a comprehensive regulatory framework and scaling up operationally. We model a 70%+ five-year CAGR for robotaxi sales, to which risk looks skewed to the upside.

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While Tesla made headlines for launching robotaxis in Austin this week, another company has been operating there, and in a much larger area, for months: Waymo. Safety experts have found that Waymo is much safer than both Tesla and human drivers. And their gradual rollout is winning over residents in every city they've come to. But concerns over labor, privacy and profitability loom for a company eager to transform the very fabric of American cities. My cover story, featuring Tekedra N. Mawakana and Dmitri Dolgov, here: https://lnkd.in/e8US7Qhz

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Tesla Q4 FY25: A Masterclass in Scale, Margin Discipline and Strategic Optionality Tesla’s Q4 FY25 income statement tells a story that goes far beyond headline revenue. This graphic captures something deeper: how Tesla is structurally positioning itself as a vertically integrated, multi-engine growth platform rather than a single-product automaker. At $24.9B in revenue (+3% YoY), Tesla continues to operate at a scale most OEMs are still chasing. Automotive remains the backbone at $17.8B, but what’s increasingly important is how Tesla makes that money. Regulatory credits ($0.5B) and leasing ($0.4B) continue to add high-margin resilience, while Energy Generation & Storage at $3.8B (+25% YoY) quietly compounds into a meaningful second pillar. Services at $3.4B (+18% YoY) reinforce Tesla’s ecosystem lock-in across charging, software, aftersales. The real signal is on the right side of the chart. Despite $19.9B in cost of revenue, Tesla delivers $5.0B in gross profit, translating to a 20% gross margin (+4pp YoY) ….a level traditional OEMs can only envy. This is not accidental. It reflects relentless cost engineering, supply chain leverage, in-house manufacturing and platform reuse across vehicles, batteries, power electronics and software. Operating discipline stands out even more. Operating expenses of $3.6B support a global footprint, continuous AI and autonomy development, factory expansions and energy deployments … yet Tesla still posts $1.4B in operating profit (6% margin). R&D at $1.8B isn’t bloat; it’s an investment in Full Self-Driving, Optimus, next-gen vehicle platforms and energy intelligence. SG&A at 7% of revenue remains remarkably lean for a company of this scale. Below the line, $0.9B in net profit reflects a business absorbing restructuring, tax and non-core adjustments while continuing to invest aggressively. Importantly, interest income of $0.4B highlights Tesla’s balance-sheet strength. Simply cash as a strategic weapon, not a liability. Operationally, 434K vehicles produced and 418K delivered underline Tesla’s ability to flex production while managing inventory in a volatile demand environment. For sure something legacy OEMs, even with brands like Toyota, Volkswagen, Ford, GM, BMW, Mercedes-Benz and also Stellantis, continue to struggle with. My 2 Cents? Tesla is no longer just competing with automakers. It’s operating closer to a technology-enabled industrial platform, blending manufacturing efficiency, energy infrastructure, AI, also software economics. Closer in mindset to Apple, NVIDIA, Amazon and Alphabet Inc. than to traditional auto peers. This income statement isn’t flashy. It’s disciplined. And discipline at scale is where enduring dominance is built. Graphic App Economy Insights

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Gasgoo Munich- On March 16, LiDAR manufacturer 禾赛科技 announced an expanded strategic partnership with autonomous delivery vehicle developer 新石器无人车Neolix. Under the agreement, Hesai will remain the primary LiDAR supplier for Neolix's next-generation Level 4 autonomous urban delivery vehicles, commonly known as RoboVans. Read more: https://lnkd.in/g__346zY #Hesai Technology #Neolix #LiDAR

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Autonomous mobility is expanding across Atlanta - and Beep is proud to be part of it. As highlighted in recent coverage, Beep will develop and operate ADA-accessible autonomous shuttles for the Cumberland Autonomous Mobility Network, integrating with existing public transit ahead of a planned 2027 launch. Beep is also partnering with the City of Atlanta on an autonomous shuttle pilot along the Atlanta BeltLine, with operations launching as soon as spring 2026. These projects reinforce our commitment to improving access, strengthening transit, and delivering real-world autonomous mobility. 🔗 Read more: https://lnkd.in/e3PGf4rV Atlanta Beltline Cumberland Community Improvement District

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Anthropic's Project Vend fails, while Waymo is thriving. Why? And how is this related to #moltbook and #openclaw -- Prologue Waymo vehicles make "life-or-death" decisions every day, in open environments, among humans, cars, cyclists, and chaos, and they do it at scale. Anthropic's Project Vend, by contrast, put an AI in charge of a vending machine business: pricing snacks, managing inventory, handling suppliers. And it couldn't reliably manage the economics. That should feel surprising. But it isn't. Because the gap here isn't intelligence. It's systems engineering. Read again: IT IS SYSTEMS ENGINEERING. Albeit an AI system, it is still, a system. We are not close to an era where we can let AI build its own engineering, unless the environment is highly constrained: a simple CLI tool, or a social network for agents - maybe. -- Similarity At a high level, Project Vend and Waymo look similar: • Both operate in the real world • Both take autonomous actions • Both deal with uncertainty and edge cases • Both can cause real damage if they fail And importantly: • Neither is "just an LLM" So why does one work, and the other collapse? -- Differences Waymo is a complete, end-to-end AI system. Not a model with tools. A system. It has: • Clearly bounded domains and objectives • Redundant sensors and inputs • Continuous verification loops • Explicit safety cases • Tight feedback between action and reality • Rich observability for humans, with live controllability • Years of accumulated edge-case learning • Every decision is constrained, validated, and monitored. Project Vend, by design, exposed the opposite. • Even with a strong model: • Memory was shallow and brittle • Economic feedback loops were weak • Verification was mostly implicit • Errors compounded instead of being corrected • No real understanding of consequences over time At least based on what I could infer from the blog [1]. The AI wasn't irrational, it was underspecified, or more accurately, under-engineered. -- Conclusion: Waymo proves something important: Trustworthy autonomy isn't achieved by smarter models alone. It's achieved by engineering the environment around the model. Project Vend failed because autonomy without systems collapses under reality. This matters far beyond vending machines. If we want AI agents to manage money, operations, workflows, or organizations, we need to stop asking "is the model good enough?" And start asking: • Where is memory grounded? • Where is verification explicit? • Where do errors get caught? • Who can observe, intervene, and correct? • What happens when incentives drift? Waymo answers these questions systemically. Most agentic AI today does not. So please accept this warning: Be careful with #OpenClaw (ex #clawdbot / #moltbot). #moltbook working (so cool!) isn't evidence that you should let these agents operate for you, it works because it's a closed world where agents can only break their own toys, not your life.

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Zoox, the self-driving vehicle division of Amazon, has begun initial testing in the nation's capital, paving the way for autonomous robotaxis to descend in the near future. https://lnkd.in/eaCrAkeF #startup #startups #technology #tech #innovation #dc #dmv #washingtondc #business #businessarticle #businessnews #av #avs #selfdriving #autonomous #autonomousvehicles #zoox #amazon

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카카오모빌리티(Kakaomobility) launches proprietary #AI-driven late-night robotaxis in Gangnam, scaling urban autonomous tech for a 2026 fare rollout. #AutonomousDriving #Mobility #TechNews https://lnkd.in/gWujVzd8

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#California is taking steps to rein in the lawless #robotaxi industry: “Under the new rules, police can cite #AV companies when their vehicles commit moving violations. The rules will also require the companies to respond to calls from police and other emergency officials within 30 seconds, and will issue penalties if their vehicles enter active emergency zones.” Via BBC News https://lnkd.in/eg9KP2TA

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Key issues that the autonomous vehicle industry needs to face in 2026: - Allowing a reasonable level of local governance to address local issues - Autonomous trucking scale-up takes longer than companies think - Beyond the FAANG-sponsored robotaxies, industry is pivoting hard into L2+++ - Will driver monitoring actually solve the L2 supervision problem? Jury is still out - Improved regulatory oversight of advanced Level 2 features, beyond NHTSA collecting SGO data But .. I recorded this in December 2022. Surprise! Impressive technical progress in getting highly automated vehicles on roads since then, but the core big challenges I identified three years ago haven't changed much. (6 minute podcast audio clip)

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A Waymo vehicle drives into oncoming traffic. The era of isolated autonomy is ending. We are entering the era of Autonomy 2.0 - orchestrated mobility and integration into our communities. Infrastructure has always been the Industry Catalyst. History is not merely a sequence of inventions, but a record of infrastructures built to harness them. Isolated concepts remain niche; integrated systems redefine economies and nations. We are captivated by the magic of self-driving vehicles, delivery drones, and automated systems. Avride, Waymo, Zoox, Cruise, Motional, Tesla, Gatik, Aurora, Coco, Kodiak, TuSimple, Starship Technologies, General Motors, Nuro, Starsky Robotics, Refraction AI, . . . But we are neglecting the silent partner in this revolution. Without INTELLIGENT INFRASTRUCTURE, we will propagate the same damn traffic congestion and gridlock. Investors are forcing companies to go public so they can pass the rotten potato to the public and sell. https://lnkd.in/gGxvij5M We need to stop betting on the vehicle alone and start investing in the stage it performs on. The truth is, it is far more than the vehicle; a new multi-trillion-dollar Industry requires INTELLIGENT INFRASTRUCTURE. Autonomy Institute, Intelligent Infrastructure Commerce & Defense Act https://lnkd.in/gHmJTctD

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