Thomas Dohmke

London Calling! Waymo is coming in 2026! The team is bringing their fully autonomous ride-hailing service across the pond. Waymo's ride-hailing service will work in partnership with London’s extensive network of bus, tube, bike, and pedestrian infrastructure, which will be available via the Waymo app. Over the coming months, the team is laying the groundwork for the service in collaboration with their fleet operations partner Moove. The team will continue to engage with local and national leaders to secure the necessary permissions for the commercial ride-hailing service in London. Kind of full-circle for the JLR I-pace to come back as a robotaxi and provide a service in London! In the U.S., the Waymo Driver has already driven over one hundred million fully autonomous miles on public roads and provided more than ten million paid rides. London, first, then Europe... Stay tuned.

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🚗 Waymo’s Autonomous Driving: A Technical Overview & Safety Impact Waymo Driver has accumulated 96 million rider-only miles as of June 2025, delivering compelling safety improvements over human drivers - 91% fewer serious injury or worse crashes, 79% fewer airbag deployments and 80% fewer injury crashes overall, validated through rigorous comparisons using NHTSA’s Standing General Order crash data. At the core of Waymo’s technology lies an advanced AI and machine learning framework that integrates: • Real-time sensor fusion: Combining lidar, radar, and a 360° multi-camera system to construct a rich, high-fidelity 3D environmental model • High-definition mapping: Detailed geospatial data of roads, signals, and key driving landmarks to enhance localization accuracy • Predictive modeling: ML algorithms anticipate behaviors of vehicles, pedestrians, cyclists, and other road users for proactive decision making • Trajectory planning: AI computes safe and efficient navigation paths (perception, prediction, planning) dynamically in complex and evolving scenarios This combination enables Waymo’s fully autonomous system to operate safely without human intervention, using continuous learning from billions of simulated and real-world miles to adapt and improve. #ai #artificialintelligence #machinelearning #autonomousvehicles

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Zoox just launched public robotaxi rides in San Francisco. Waymo continues expanding across cities and freeways. That sounds like progress. From a systems-engineering perspective, it signals something else. Robotaxi fleets are scaling faster than their verification frameworks. Every new deployment zone changes pedestrian behavior, occlusion geometry, cyclist interaction, and edge-case combinations. As the operating environment expands, scenario distributions shift — and validation assumptions decay. This isn’t a software bug story. It’s a boundary problem. Here’s why expansion inevitably outruns verification. https://lnkd.in/gxi4aFbW

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Today during several calls I was asked about my views on AI and vehicle autonomy. To answer that question properly, I had to reference the behavior model behind the E2X Vehicle Node architecture we are developing at IgniBlu Technologies. There’s a lot of excitement around autonomous vehicles right now—new models, new architectures, and large-scale deployments. But there is still a fundamental design challenge that I believe the industry has not fully solved. Most autonomous vehicle systems today are trained primarily through object recognition and GPS positioning. In other words, the vehicle is taught to “see” things like stop signs, lane markings, pedestrians, and other vehicles, and then react accordingly. The issue is that road infrastructure was designed for human recognition—not machine recognition. A stop sign, for example, was created for human eyes and human cognition. Training vehicles to operate primarily through visual object recognition is essentially forcing machines to behave like humans. It’s like putting eyes on something that was never originally designed to rely on vision in the first place. If we want to reach the level of autonomy people are excited about, we need to rethink the model. Autonomous systems should operate more like a person navigating without sight. When someone loses their vision, other senses become heightened—allowing them to navigate safely through sound, touch, spatial awareness, and environmental cues. Vehicles can achieve a similar capability through intelligent infrastructure. Instead of relying primarily on vision, infrastructure can communicate directly with vehicles through telemetry and digital signaling—providing vehicles with the environmental awareness needed to act safely and appropriately, even without relying solely on visual interpretation. This is one of the principles behind the E2X architecture we are building at IgniBlu Technologies: a system where infrastructure, vehicles, and edge intelligence work together to provide vehicles with machine-native awareness of their environment. Autonomy becomes far more reliable when vehicles are not just seeing the road, but when the road itself is communicating with the vehicle. www.igniblu.com

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Just downloaded Tesla Robotaxi in SF, a real threat to Uber, Lyft, and Grab? Most experts measure Robotaxi by today’s metrics: cost of operations, active users, global adaptability. By that logic, scaling looks impossible. But Tesla flips the script. Unlike Waymo’s costly retrofits, a Tesla only needs a software update to become a Robotaxi. With 1.7M+ Hardware 4.0 vehicles already on the road, the scale potential is unmatched. Cars shift from being liabilities to income-generating assets overnight. This isn’t just product innovation, it’s a redefinition of value. At ElasticDash we’re doing the same for QA. Today, QA costs are labor-driven, with humans building and maintaining tests. Our AI agents change that: they build and adapt end-to-end tests automatically as your app evolves. Just as Tesla is rewriting mobility economics, we’re rewriting QA economics. ElasticDash is on the way.

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🚖 Waymo Cleared to Expand Robotaxi Service Across Silicon Valley 🗺️✅ Waymo, Alphabet’s autonomous vehicle division, has secured regulatory approval to expand its robotaxi operations into more areas of Silicon Valley. This move marks a significant milestone in the commercialization of self-driving technology and underscores growing confidence in autonomous vehicles. 🔑 Key Points: 🔹 Service Expansion – Waymo’s robotaxis will now operate in additional cities and neighborhoods, offering more residents and commuters access to driverless rides. 🔹 Safety Focus – The approval follows rigorous safety evaluations, reinforcing Waymo Community’s reputation as a leader in autonomous vehicle reliability. 🔹 Competitive Edge – The expansion intensifies the race against rivals like Cruise and Tesla, as companies vie for dominance in the AV market. ⚠️ Why It Matters: Waymo’s growth signals a turning point for autonomous transportation, bringing self-driving technology closer to mainstream adoption. It also highlights the role of regulatory trust in scaling cutting-edge innovations. 🔄 What You Should Know: ✅ Tech Behind the Wheel – Waymo’s AI combines lidar, cameras, and machine learning to navigate complex urban environments. ✅ User Experience – Riders can hail rides via an app, with vehicles operating 24/7 in approved zones. ✅ Public Sentiment – While many embrace the convenience, debates persist about safety, job displacement, and data privacy. 🌍 The Bigger Picture: Waymo’s expansion is a step toward redefining urban mobility, reducing reliance on personal cars, and advancing sustainable transport. As robotaxis scale, they could reshape city planning, emissions, and daily commutes globally. #Waymo #Robotaxi #AutonomousVehicles #SiliconValley #TechInnovation #FutureOfTransport #TechNews #StudiosEerb

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BREAKING: Tesla will launch their fully autonomous robotaxi service on June 12th! This is the Americas first fully autonomous robotaxi service without any LiDAR (Waymo is already active but their cars have a LOT more hardware on them including the expensive LiDAR equipment). I have tried and love Waymo as it feels nice to be alone in a car without another persons music, talking ect. I don’t think people realize how huge this is. If this initial launch in Austin Texas goes well, the scaling will be very fast.

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Recently, I posted about research showing that Waymo’s autonomous vehicles are 10X safer than human drivers (https://lnkd.in/gHw7drrc). The data is clear: when we apply proven technology, outcomes dramatically improve—even if we’re naturally hesitant to move beyond the familiar. That lesson hit close to home last week. My teenage daughter was driving on a Los Angeles freeway during stop-and-go traffic. She was rear-ended by another vehicle traveling over 30 miles an hour—hard enough that the other driver’s airbags deployed. Thankfully, no one was seriously injured. Our car—a newer model equipped with modern safety tech—helped her anticipate and react, but the driver behind her didn’t have those same tools and couldn’t brake in time causing the accident. In hiring, the stakes are thankfully lower, but the dynamic is strikingly similar. Outdated hiring methods like “resumes” and “unstructured interviews” aren’t up to today’s talent challenges like truly measuring the potential of a candidate through skills-based hiring, or ensuring that every candidate is assessed fairly and with integrity by following clear policies around AI use. These older tools often overlook actual ability and can’t reliably guard against unethical behavior—and that means missed potential, inconsistent decisions, and sometimes, the wrong fit resulting in negative economic impact. That’s why at Criteria Corp, we help companies hire for potential through a broad portfolio of science-backed predictive assessments (https://lnkd.in/geXe97YJ) and interviewing technologies (https://lnkd.in/gW268aem). Of course, not every organization can upgrade instantly—sometimes budget, awareness, or inertia get in the way. But the risks of standing still can be higher than we think: poor-performing hires, increased turnover, higher costs, and lost productivity. Better hiring, like better driving, is about putting the best technology to work—not just what’s familiar, but what’s proven to deliver fairer, more accurate, and more predictive results.

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If you are a CEO or an aspiring Chief Policy Officer anywhere, do click into the Time article and read it. It’s a masterclass in how to run a great public policy and communication campaign. Waymo’s technology is definitely world class. No doubt about it. After I rode Waymos for a week in SF last year, I cannot understand why Singapore doesn’t have ride-share AVs. I would take a machine driving me around any time over those horrible human drivers behind the wheels of our buses, taxis and ride-share cars. (It’s why I have switched to trains these days as the line I am on has autonomous trains.) But, equally critical to their success over all other AV-competitors (Tesla included) has been their excellent policy and communication strategies. It’s all about safety. It’s all about earning trust. It’s about working with stakeholders in every city that they have launched or will be launching. It’s about being transparent with your real-world data so peer-reviewed studies can be done by independent researchers. And more importantly, it’s about taking the bull by its horns and talking authentically about the risks and benefits of AV.

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Whether it’s slippery surfaces, snow accumulation, or low visibility, winter weather presents a very real challenge for autonomous vehicles and human drivers alike. Building an all-weather Driver is essential for Waymo to reliably serve riders in more places across the globe, and we’re combining state-of-the-art hardware and AI to make it happen. Take a look under the hood at how we’re validating the Waymo Driver for winter weather and what’s to come from our 6th-generation technology.

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Lessons from YC: Culture Isn’t a Slide Deck YC didn’t just change how we built products. It changed how we worked together. Before YC, “culture” was something we’d figure out later. We thought it meant perks, team dinners, or a list of values on the wall. But inside YC, culture meant one thing: how fast your team can move without breaking. That’s when it clicked. Culture isn’t what you say. It’s what you tolerate. If someone cuts corners and you let it slide, that’s your culture. If someone owns their mistake and you celebrate it, that’s your culture. We started treating culture like product — build, test, iterate. That's when we realized small habits create the real DNA: how you communicate under pressure, how you make decisions, how you handle bad days. YC pushed us to grow up as a team, not just as founders. Because a product might attract customers but culture is what keeps them.

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Stardew Valley meets Enterprise RAG? 🚜 🤖 One of the hardest challenges in moving Generative AI from prototype to production is authorization. How do you ensure the LLM only retrieves data the specific user is allowed to see? Our friends Sohan Maheshwar at AuthZed and Rohit Ghumare at motia just dropped a fantastic reference architecture solving exactly this. Using a Stardew Valley "harvest logbook" as the use case, they demonstrate how to build a complete, multi-tenant RAG pipeline. The Stack: ⚡ Orchestration: motia (Event-driven workflows) 🧠 Memory: Pinecone (Vector search & storage) 🔒 Security: #SpiceDB (Fine-grained authorization) This is a masterclass in building secure, context-aware AI applications. Check out the full tutorial below. 👇 #GenerativeAI #RAG #VectorDatabase #Pinecone #Authorization #Engineering #KnowledgeableAI

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Slowly, then quite suddenly. Alphabet’s Waymo is expanding its driverless taxi service to highways in Los Angeles, Phoenix, and San Francisco, marking the first paid robotaxi operation on freeways without a safety driver. The move signals a shift from controlled urban zones to high-speed, high-risk environments, testing both public trust and technical maturity in autonomous systems. In fact: • Highway integration: Waymo cars will now travel up to 65 mph, connecting major destinations such as San Jose International Airport. • Engineering leap: Co-CEO Dmitri Dolgov called highway autonomy “a profound engineering feat—easy to conceive, hard to master.” • Fleet scale: Waymo runs 250,000 weekly rides with a 2,000-vehicle fleet, mainly Jaguar I-Pace EVs equipped with proprietary sensors and computing stacks. • Competitive escalation: Tesla, Zoox, and others are expanding rival pilots, intensifying the race to commercialize full autonomy at scale. • Safety infrastructure: Waymo will collaborate with highway patrol to handle technical failures and emergency pullovers. Waymo’s highway expansion is the most consequential test yet of whether autonomy can handle real-world complexity at speed. It moves self-driving from novelty to transport infrastructure, forcing regulators, insurers, and the public to confront automation risk directly. The company that proves safety and scalability first will define the economics of autonomy. https://lnkd.in/enddV6yB

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