Comment by kevintouati
20 hours ago
Interesting angle. Does the search use semantic embeddings so it can surface clips by concept rather than filename/metadata? If it nails the retrieval part, that could be the real differentiator.
20 hours ago
Interesting angle. Does the search use semantic embeddings so it can surface clips by concept rather than filename/metadata? If it nails the retrieval part, that could be the real differentiator.
Yeah, exactly. We capture the semantic meaning of each frame and complement the filename/metadata, so both options work.
Do we have any metrics on the time taken to index media files or the latency for performing semantic searches on them?
I'm on an M2 and it takes <5 minutes to index a 2hr movie. If you're trying to index a lot of media at once, we will queue it up to be indexed. We also do smart sampling to detect similar frames so if it two talking heads vs. a lot of different shots, it will process faster. In that case the audio is more valuable for the talking heads.
The semantic search queries typically take 100-250ms.