[HN Gopher] Qwen3-VL can scan two-hour videos and pinpoint nearl...
___________________________________________________________________
Qwen3-VL can scan two-hour videos and pinpoint nearly every detail
Author : thm
Score : 54 points
Date : 2025-11-30 07:27 UTC (2 days ago)
(HTM) web link (the-decoder.com)
(TXT) w3m dump (the-decoder.com)
| thot_experiment wrote:
| anyone have a tl;dr for me on what the best way to get the video
| comprehension stuff going is? i use qwen-30b-vl all the time
| locally as my goto model because it's just so insanely fast,
| curious to mess with the video stuff, the vision comprehension
| works great and i use it for OCR and classification all the time
| xrd wrote:
| How much VRAM do you need for local usage may I ask?
| moralestapia wrote:
| To me, this qualifies as some sort ASI already.
| visioninmyblood wrote:
| I was using this for video understanding with inference form
| vlm.run infra. It definitely has outperformed Gemini which
| generally is much better than openai or Claude on videos. The
| detailed extraction is pretty good. With agents you can also crop
| into a segment and do more operations on it. have to see how the
| multi modal space progresses:
|
| link to results:
| https://chat.vlm.run/c/82a33ebb-65f9-40f3-9691-bc674ef28b52
|
| Quick demo: https://www.youtube.com/watch?v=78ErDBuqBEo
| djmips wrote:
| Does anyone else worry about this technology used for Big Brother
| type surveillance?
| reactordev wrote:
| Where have you been the last decade? It's already in use, or
| models like it, by companies selling access to _The State_
|
| https://deflock.me
|
| Not to mention cloud platforms that collect evidence and
| process it with _all the models_ and store that information for
| searching...
|
| https://www.revir.ai
| mptest wrote:
| or if you prefer your depression in book format: surveillance
| capitalism by zuboff pegasus: a spy in your pocket laurent
| richard
| eurekin wrote:
| No mention of palantir?
| spwa4 wrote:
| It's so weird how that works with transformers.
|
| Finetuning an LLM "backbone" (if I understand correctly: a fully
| trained but not instruction tuned LLM, usually small because
| students) with OCR tokens bests just about every OCR network out
| there.
|
| And it's not just OCR. Describing images. Bounding boxes. Audio,
| both ASR and TTS, all works better that way. Now many research
| papers are only really about how to encode image/audio/video to
| feed it into a Llama or Qwen model.
| zmmmmm wrote:
| It is fascinating. Vision language models are unreasonably good
| compared to dedicated OCR and even the language tasks to some
| extent.
|
| My take is it fits into the general concept that generalist
| models have significant advantages because so much more latent
| structure maps across domains than we expect. People still talk
| about fine tuning dedicated models being effective but my
| personal experience is it's still always better to use a larger
| generalist model than a smaller fine tuned one.
| eurekin wrote:
| Insane if true... now I wonder, if I use it to go through some
| old dance routing video catalogue to recognize and write
| individual move lists
___________________________________________________________________
(page generated 2025-12-02 23:00 UTC)