According to Sawyer Merritt, Tesla's Full Self-Driving (FSD) V14 system, which relies solely on camera-based AI perception, demonstrated strong performance in severe fog conditions. In a recent real-world test with the Cybertruck, the AI successfully navigated challenging visibility, even maneuvering around a stopped vehicle on the roadside (Source: Sawyer Merritt, Twitter, Jan 16, 2026). This test highlights advancements in AI computer vision and machine learning algorithms, showcasing the viability of camera-only autonomous systems for adverse weather. The results suggest significant business opportunities for camera-centric AI solutions in automotive safety and scalability, as traditional sensor suites like LiDAR may not be strictly necessary for reliable autonomous driving in poor visibility scenarios.

According to @ai_darpa on Twitter, Tesla's Robotaxis now operate Full Self-Driving (FSD) capabilities without relying on LiDAR technology, validating Elon Musk's 2019 prediction that LiDAR would be unnecessary for autonomous vehicles (source: @ai_darpa, Dec 16, 2025). This strategic shift has significant implications for the AI and autonomous driving industry. Notably, a major LiDAR supplier for Volvo recently filed for bankruptcy, highlighting a market transition toward vision-based AI solutions over hardware-centric approaches. The business opportunity now lies in advanced computer vision, deep learning, and sensor fusion algorithms, as automotive OEMs and AI startups pivot to software-driven autonomy. Industry leaders are expected to invest more in scalable AI software platforms, reducing dependence on costly sensor hardware and opening new avenues for data-driven mobility services.