Memories.ai's core technology is based on Large Visual Memory Models, a multimodal AI system. The technology enables video content analysis through the following key mechanisms:
- visual feature extraction: Parsing objects, scenes, and actions in video frames using deep convolutional neural networks to build visual indexing libraries
- chronological modeling: Processing video timing information using 3D CNN or Transformer architectures to understand the continuum of action development
- multimodal fusion: Combining ASR speech recognition and OCR text recognition to realize joint analysis of audiovisual text
- memory compression: Compression of hours of video into retrievable memory vectors by filtering key frames through an attention mechanism
This combination of technologies gives the system human-like video comprehension capabilities, including scene recognition (accuracy 921 TP3T), behavioral classification (F1-score 0.87), and semantic associations (recall 881 TP3T), with processing speeds up to 4x the speed of real-time video analysis.
This answer comes from the articleMemories.ai: an AI visual memory tool for analyzing video contentThe
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