This is a really cool implementation—embeddings still often feel like magic to me. That said, this exact use case is sort of also my biggest point of concern with where AI takes us, much more so than most of the common AI risks you hear lots of chatter about. We live in a world absolutely loaded with cameras now but ultimately retain some semblance of semi-anonymity/privacy in public by virtue of the fact that nobody can actually watch or review all of the video from those cameras except when there is a compelling reason to do so, but these technologies are making that a much more realistic proposition.

The presence of cameras everywhere is considerably more concerning than the status quo, to me at least, when there is an AI watching and indexing every second of every feed—where camera owners or manufacturers or governments could set simple natural language parameters for highly specific people or activities notify about. There are obviously compelling and easy-to-sell cases here that will surely drive adoption as it becomes cost effective: get an alert to crime in progress, get an alert when a neighbor who doesn't clean up after his dog, get an alert when someone has fallen...but the potential implications of living in a panopticon like this if not well regulated are pretty ugly.

> Check if a video chunk contains mostly still frames. Extracts 3 evenly-spaced frames as JPEG and compares file sizes.

I believe you could use a combination of select and scene parameters in ffmpeg to do this automatically when a chunk of video is created each time.

Multimodal AI will lead to an interesting arms race in ad detection vs ad insertion. I played around with AI ad removal with older Gemini models, but it seems like this would be even more powerful to instantly identify ads (and potentially mute or strip them out).

https://notes.npilk.com/experiments-with-ai-adblock

Can I give it a photo of a person and ask it to search for the person in the video?

I picked up a Rexing dash cam a few months back and after getting frustrated with how clunky it is to get footage of it, I decided to look into building something out myself to browse and download the recordings without having to pull the SD card. While scrolling through the recordings, I explicitly remember thinking it would be nice to just describe what I was looking for and run a search. Looking forward to incorporating this into my project.

Thanks for sharing!

In the demo bro shows how to search for "a car with a bike rack on the back that cut me off at night." Given the grudge he must've held from being cut off, I strongly suspect that finding this specific car was his main motivation for building the project in the first place

Could this be used for creating video editing software?

Imagine a Premiere plugin where you could say "remove all scenes containing cats" and it'll spit out an EDL (Edit Decision List) that you can still manually adjust.

Where is the Exit to this dystopia?

Damn, I need to going with my embeddings project. I've currently got a prototype for using embeddings (not gemini in my case) for making a game that's kinda reverse connections:

collections.lwarfield.dev

Very interesting (not for a dashcam, but for home monitoring).

This seems like something that would be very expensive to run. Do you have some representative figures at a particular resolution and frame rate?

this can be done locally https://github.com/intel/openvino-ai-video-retrieval-analysi...

I work in content/video intelligence. Gemini is great for this type of use case out of the box.

Very impressive! A webhook could be configured to trigger an alarm if a semantic match to any category of activities is detected, and then you basically have a virtual security guard and private investigator. Well played.

This is a big leap true multimodal search without text bottlenecks makes video querying feel finally native and insanely practical.

I wonder if the underlying improvements in visual language learning will allow for even more efficient search. The First Fully General Computer Action Model -> https://si.inc/posts/fdm1/

I don't quite understand the 5 second overlap. I assume it's so that events that occur over the chunk boundary don't get missed, but is there any examples or benchmarking to examine how useful this is?

Is there a decent open video embedding model out there? I’d love to play with this without uploading video.

What a brilliant idea! is this all done locally? That's incredible.

Total aside here but is that you driving the pickup I assume?

This is great, thanks for sharing

I wonder how well this would work with dance videos.

That's quite interesting, well done! I haven't thought of this use case for embeddings. It open the door to quite many potential applications!

Does anyone know of an open weights models that can embed video? Would love to experiment locally with this.

What is your experience so far with the quality of the retrieved pieces?

Nice use of native video embedding. How do you handle cases where Gemini's response confidence is low? Do you have a fallback or threshold?

very cool, anybody have apparent use cases for this?

Why just the dash cam?

> No transcription, no frame captioning, no intermediate text.

If there is text on the video (like a caption or wtv), will the embedding capture that? Never thought about this before.

If the video has audio, does the embedding capture that too?

Today I learned that Gemini can now natively embed video..

Cool Project, thanks for sharing!

why not skip the text conversion? is it usable at all?

[dead]

[dead]

[dead]