Soha Pouya

The autonomous vehicle industry is at a crossroads. Waymo's co-CEO Tekedra Mawakana recently warned that robotaxi companies must go beyond marketing and deliver concrete safety proofs to regulators and the public. With recent incidents involving competitors like Cruise, the pressure is on to establish standardized safety metrics and transparent validation processes. Key challenges include: 1. Data transparency: Companies must share safety test results and incident reports openly. 2. Human-in-the-loop verification: Autonomous systems need rigorous human oversight during edge-case scenarios. 3. Regulatory alignment: Collaborating with agencies to create measurable safety benchmarks. For tech founders building mobility solutions, here's what to prioritize: - Invest in real-world safety testing with third-party validation. - Develop public dashboards to track safety KPIs in real time. - Advocate for industry-wide safety protocols that regulators can audit. The path to mass adoption isn't just about innovation—it's about trust. How will your team balance speed with safety in autonomous tech development? Let's discuss.

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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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🚨 Stop the 6-8 Hour Manual Log Analysis Grind! 🚨 The complexity of RDK-B embedded software has made traditional firmware diagnostics obsolete. We're fighting gigabytes of data with simple grep commands, leading to diagnostic fatigue and long Mean Time to Resolution (MTTR). That's why we engineered ORCA (Optimized Root Cause Analysis)—a game-changing Multi-Agent System (MAS) built on LangGraph. Here are the core innovations we deployed to achieve a 3X speedup, slashing diagnostic time to ~90 minutes: 🔹 Agentic Reasoning: We replaced static scripts with a Supervisory MAS that uses a cyclical, stateful workflow for self-correction and deep causal analysis across subsystems . 🔹 Model Agility: Introducing the Prompt Optimizer Agent—our custom middleware that dynamically "compiles" instructions for models like Llama 3, Claude 3.5 Sonnet, and Mistral, ensuring high-fidelity reasoning no matter the LLM backbone. 🔹 Code-Level Precision: We integrated Tree-sitter for robust syntactic C++ source code analysis, correlating log errors directly to function definitions within the complex Yocto build environment. The result? We're not just finding errors; we're identifying the Temporal-Causal Nexus—revealing that a "instability" is often a downstream symptom of a error event. This system is transforming how we diagnose Issues. What role do you see Agentic AI playing in the future of embedded systems diagnostics? Share your thoughts below! #EmbeddedSystems #RDKB #AI #MultiAgentSystems #LangGraph #Firmware #RootCauseAnalysis #LangChain #IoT #SoftwareEngineering

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Thread: Waymo’s robotaxis go driverless in Nashville Waymo’s robotaxi service in Nashville is now operating driverless in select zones and hours, marking a notable milestone for city-scale autonomous mobility. This shift, highlighted in Mashable’s coverage, moves us from pilots to more scalable, on-demand rides in a real urban environment. 1) What happened - In Nashville, Waymo’s robotaxis are running without a human safety driver in defined areas, signaling a significant step toward fully driverless operation in a city context. The change focuses on real-world testing and service at scale, beyond controlled corridors. 2) Why it matters - It demonstrates maturity in sensing, mapping, and decision-making needed for driverless rides in busy streets. - It pushes the industry toward evaluating not just feasibility, but reliability, rider experience, and city integration at scale. 3) What this means for riders and businesses - Riders gain the potential for more predictable travel times and around-the-clock service in certain neighborhoods. - For businesses, it opens opportunities in on-demand mobility, last-mile logistics, and new data-driven service models. - City stakeholders should watch implications for curb management, safety oversight, insurance models, and accessibility. 4) What to watch next - Safety performance across weather, peak hours, and edge cases. - Customer experience: wait times, ride quality, accessibility for all users. - Regulatory and policy updates that shape deployment speed and governance. - The business case: cost structures, partnerships, and ROI for large-scale adoption. Takeaway for leaders: this aligns with a broader trend toward driverless mobility becoming a tangible, city-backed service. If you’re in mobility, real estate, urban planning, or customer experience, now is the time to explore pilots, partnerships, and responsible deployment strategies. Read the full article for details: https://ift.tt/6TwNh0F #Waymo #Robotaxi #AutonomousVehicles #Nashville #Mobility #Transportation #FutureOfMobility #TechNews #Innovation #TAMK #TampereUniversity #BusinessTampere #emobility #mobility #ITSFinland #ITSfactory #Spotlog #byAI

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The quiet revolution in AI inference ⚡ Why pay for expensive API calls when you can run state-of-the-art models on your own hardware? Tools like OpenAI Triton and NVIDIA TensorRT are making optimized inference accessible to everyone. Achieve cloud-level performance without the cloud bills. Faster, cheaper, and more private. The future is local. What's your go-to for optimized inference? #AIEngineering #InferenceOptimization #Triton #TensorRT #AIEngineer

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.@TechCrunch Waymo’s Tekedra Mawakana on Scaling Self-Driving Beyond the Hype: Waymo co-CEO Tekedra Mawakana takes the Disrupt Stage at TechCrunch Disrupt 2025 (Oct 27–29, SF) to share the realities of scaling autonomous vehicles — from safety to regulation to the road ahead. http://dlvr.it/TN6PSW #tech #startups #VC

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🚀 How are former Waymo engineers revolutionizing the construction industry? Meet Bedrock Robotics! 🏗️🤖 Key Insights: - Former Waymo engineers have founded Bedrock Robotics with an impressive $80M funding. - Their mission is to automate construction processes, enhancing efficiency and safety. - This move showcases the growing intersection between AI and traditional industries. Value & Context: The construction industry, often slow to adopt new tech, is ripe for transformation. With automation, we could see a future where construction projects are completed faster and with fewer accidents. Imagine AI-powered robots managing construction sites—this isn't just sci-fi anymore. Engagement Prompt: What do you think about AI entering the construction industry? Have you seen similar innovations in your field? Feel free to share this post with others who are passionate about AI and innovation. Personal Reflection: Every leap in technology opens new doors. As we embrace AI in various sectors, we must also consider the skills and training needed to work alongside these advancements. 🚀 #Robotics #AI #ConstructionInnovation #TechTrends #FutureOfWork @Waymo @TechCrunch

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– Always providing the latest updates on tech innovations and trends. #TechNews – Waymo discusses the significance of their robotaxi expansion in San Francisco. #Waymo #Transportation – Recent jury verdict reveals Apple owes Masimo $634 million for patent infringement. #Apple #PatentInfringement – Disney and YouTube TV have reached an agreement to end service blackout issues. #Disney #YouTubeTV – Leaked documents uncover payments OpenAI makes to Microsoft. #OpenAI #Microsoft – Tesla shares a detailed safety report following requests for more data on their autonomous driving systems. #Tesla #AutonomousDriving – Comprehensive list released discussing tech layoffs of 2025. #TechLayoffs #Startups – WhatsApp plans to enable third-party chat integration in Europe shortly. #WhatsApp #Apps – Apple adjusts its app review guidelines, restricting apps that share user data with third-party AI. #Apple #Privacy – ChatGPT rolls out pilot group chats in several countries including Japan and New Zealand. #ChatGPT #AI

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Waymo is one of San Francisco’s best examples of an innovative company delivering world-class services with global impact. The autonomous mobility future starts here in San Francisco, and it is overwhelmingly popular. According to recent polling from Advance SF, a significant majority of San Franciscans feel Waymo is making their city safer, hold Waymo as a source of civic pride, and believe Waymo should be allowed in more cities around the U.S. Our partners at the Bay Area Council, San Francisco Chamber of Commerce, and sf.citi agree that our region benefit when homegrown technologies are developed and embraced here and then spread across the state. Waymo reinforces our position as a global leader in transportation and technology innovation. 

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On-device AI becomes powerful only when it works reliably on real hardware. In this Melange Walkthrough, Yeonseok Kim and Sun-Q Kim break down how the full on-device pipeline works, from model selection and quantization to real-device benchmarking and SDK deployment. Select. Benchmark. Deploy. This is how production-ready on-device AI should operate. Watch the full walkthrough below. #OnDeviceAI #EdgeAI #MobileAI #AIInfrastructure #ZETIC #Melange

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The end of human drivers? Tried Tesla Robotaxi in the Bay Area for the first time, 8.8 miles from Meta SF to Daly City station for $18. Unlike Waymo, Tesla’s Robotaxi can take the freeway. The ride was smooth, and the decision-making felt far closer to human than “bot-like.” What surprised me most: it’s just a regular Model Y. With the built-in rear screen, any Tesla could potentially be activated as a Robotaxi. That’s scalability at an entirely different level. Waymo might have an early lead, but Tesla’s vision-only approach gives it massive coverage and faster rollout potential. If this scales, Uber, Lyft, and even car ownership itself could be disrupted faster than expected. This is exactly why I quit my job to go all-in on ElasticDash We’re entering a new industrial revolution, the real question is: will you shape it, or be forced to adapt?

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🚗🤖 Waymo introduces its new simulation system for autonomous vehicles 🌍✨ Waymo takes a giant step forward in autonomous driving development with the launch of its Waymo World Model, a next-generation simulation system powered by Genie 3. Unlike traditional approaches—which train models solely on real-world, on-road data—this system leverages a much broader understanding of the world. Thanks to its pre-training on a massive and diverse set of videos, Genie 3 enables the simulation of situations that were never directly observed by the real-world fleet, including rare and long-tail scenarios that are critical for the safety and robustness of autonomous systems. 🔍 What makes it different? Knowledge transfer from 2D video to 3D LiDAR outputs, tailored to Waymo’s specific hardware. A combination of cameras (visual detail) and LiDAR (precise depth and geometry). The ability to generate almost any scene, from everyday driving to rare, extreme events. This breakthrough redefines how autonomous driving systems are trained and validated, accelerating innovation and raising safety standards across the industry. 🚀 The future of autonomous simulation is already here—and it’s powered by Waymo. https://lnkd.in/eK63bh6A Video © Waymo. All rights reserved

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The Power of Data: More Data. More Compute. Better Models. Waymo's recent blog post (https://lnkd.in/gydNP68D) highlights a powerful truth: performance in robot autonomy scales with data and compute. They show the impact of real data, how larger models, trained on vast diverse datasets, are yielding breakthrough capabilities in autonomous driving. This echoes a theme we’ve seen in the robotics community. Covariant, in their RFM-1 update last year (https://lnkd.in/gVrHx2Sz), made the case that the difference between good and great performance in robotic manipulation comes down to real-world data and massive amounts of it. At Diligent Robotics, we have always placed a high value on experience our robots can collect out in the WILD in the hands of real users. Our robots have logged hundreds of thousands of hours operating inside complex, dynamic indoor environments like hospitals where the stakes are high and the variability is endless. This hard-earned experience is what allows us to deliver reliable and scalable autonomy, coexisting gracefully with our human co-workers and adapting fluidly to real-world challenges. The future of robotics won’t just be built in simulation or labs. It will be forged in the noisy, unpredictable, people-filled places where robots work alongside us. I'm extremely proud to say that this is where Team Diligent shines. We've taken years to hone our operational execution muscle and this team is ready to go, exciting times! #Robotics #AI #Autonomy #DataDriven #PhysicalAI

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