오늘 회사 블라인드글

그러하다.. 김치보유비중 10% 쉽게 넘길거 같음

FSD v14: Tesla's Simulator for AI Training Using Real-World Data FSD v14 will utilize an AI model heavily reliant on high-definition maps created using data from Tesla's vehicle fleet. Given this reliance on proprietary map data, a natural question arises: why not simply use existing commercial mapping solutions from companies like Google or Baidu? The answer, crucially, lies in Tesla's development of a sophisticated real-world simulator. Tesla's patent WO2024073741A1 details Tesla's simulator, which transforms fleet-collected ground truth data into realistic virtual environments for AI training. The system leverages sophisticated 3D modeling and environmental variation techniques to produce high-fidelity training data. This system allows for extensive and diverse training scenarios, which could be crucial for addressing variations in FSD performance. It's been observed that FSD v13's capabilities differ between high-volume models (M3/MY) and lower-volume models (MX/Cybertruck). The simulator offers a potential solution by generating the specific training data needed for each model. The simulator enables the creation of extensive training datasets encompassing edge cases and rare events that would be impractical or impossible to collect in the real world. This creates a strong foundation for robust AI training. [FIG. 10: Populated traffic environment showing dynamic objects and lane graphs] [FIG. 13: Segmented geography model demonstrating efficient computational resource allocation]