Insights, engineering deep-dives, and the future of autonomous vehicle development
How AI-powered scenario search is revolutionizing the way AV teams validate their systems and discover critical edge cases that traditional testing methods miss.
Technical deep-dive into our infrastructure: from video ingestion to embedding generation, how we process thousands of hours of driving footage at scale.
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Comparing OpenCLIP's multimodal approach against traditional computer vision methods for understanding and categorizing driving scenarios.
Key insights from our Y Combinator experience and what we learned about building AI infrastructure for enterprise customers.
How we architected our storage and processing systems to handle massive amounts of driving data while maintaining performance and cost efficiency.
Analysis of semantic search effectiveness compared to manual tagging systems for video content discovery in autonomous vehicle development.