Beamr CTO Tamar Shoham and the AI research team showcase benchmark results, demonstrations, and validation of ML-safe video compression across machine vision models.

How to addresses the growing challenge for autonomous vehicle and physical AI teams: storing, moving, and processing video datasets at petabyte scale.

• Tamar Shoham, CTO - How Much Can You Compress Before the Model Notices?

• Ronen Nissim, AI Tech Lead - Measuring Compression Sensitivity in Generative VLM Pipelines

• Ethan Fenakel, Computer Vision Researcher - Video Compression Impact on 2D Object Detection

• David Tomarov, Computer Vision Researcher - Video Compression Impact on Lane Detection

Watch here https://beamr.com/ml-safe-webinar