5 ms·

So film the sky during charging and run a llm on it?

Neywiny 4mo ago
Or an image detection model. Fraction of the compute and can run even on edge embedded. And easy to train with your own data
- kklisura 4mo ago
  Or something like this https://www.youtube.com/watch?v=YZkLQsv3huo https://www.youtube.com/watch?v=YZkLQsv3huo
dghlsakjg 4mo ago
Clouds and nighttime are a barrier to visual detection. Even with good effectiveness the conditions needed for that would mean that you have far less than 50% uptime, and your downtime is predictable to your adversary. A cheap radar takes an order of magnitude less power to run on hardware that is cheaper than an LLM and can see way farther than a camera.
- energy123 4mo ago
  Radar can't effectively see the new low-altitude small fiber optic spool first-person drones that are redefining frontline war. The solution is going to be multi-modal (optical + audio) and imperfect. The above poster is correct that an ordinary camera with computer vision (not an LLM, of course) is going to be part of the multimodal defense in depth. Shahed-type one-way attack drones are important to defend against, but not as impactful in terms of frontline body count, given they just slam into a pre-programmed target.
  - dghlsakjg 4mo ago
    My comment was about Shaheds like the article we are commenting on. for what you are talking about, audio is a great option
  - MobiusHorizons 4mo ago
    The article and this thread are about shaheed style drones. As far as I know, stopping fiber optic fpv drones leans more on physical barriers that catch the fiber (eg road nets) rather than trying to detect and destroy the drone. It’s usually too late by the time you can hear or see a drone that size.
    - energy123 4mo ago
      > It’s usually too late by the time you can hear or see a drone that size. What does the asymptote looks like as defender and aggressor keep iterating. Who has the advantage? Can optical technology get so good at detecting (at least when it isn't raining) that eventually the balance shifts in favor of the defender?
LtWorf 4mo ago
Language models are terrible at computer vision. I don't know why you think that a software to generate words would be able to see flying objects in a picture.

Or an image detection model. Fraction of the compute and can run even on edge embedded. And easy to train with your own data

kklisura 4mo ago
Or something like this https://www.youtube.com/watch?v=YZkLQsv3huo https://www.youtube.com/watch?v=YZkLQsv3huo

dghlsakjg 4mo ago

Clouds and nighttime are a barrier to visual detection. Even with good effectiveness the conditions needed for that would mean that you have far less than 50% uptime, and your downtime is predictable to your adversary. A cheap radar takes an order of magnitude less power to run on hardware that is cheaper than an LLM and can see way farther than a camera.

energy123 4mo ago
Radar can't effectively see the new low-altitude small fiber optic spool first-person drones that are redefining frontline war. The solution is going to be multi-modal (optical + audio) and imperfect. The above poster is correct that an ordinary camera with computer vision (not an LLM, of course) is going to be part of the multimodal defense in depth. Shahed-type one-way attack drones are important to defend against, but not as impactful in terms of frontline body count, given they just slam into a pre-programmed target.
- dghlsakjg 4mo ago
  My comment was about Shaheds like the article we are commenting on. for what you are talking about, audio is a great option
- MobiusHorizons 4mo ago
  The article and this thread are about shaheed style drones. As far as I know, stopping fiber optic fpv drones leans more on physical barriers that catch the fiber (eg road nets) rather than trying to detect and destroy the drone. It’s usually too late by the time you can hear or see a drone that size.
  - energy123 4mo ago
    > It’s usually too late by the time you can hear or see a drone that size. What does the asymptote looks like as defender and aggressor keep iterating. Who has the advantage? Can optical technology get so good at detecting (at least when it isn't raining) that eventually the balance shifts in favor of the defender?

LtWorf 4mo ago

Language models are terrible at computer vision. I don't know why you think that a software to generate words would be able to see flying objects in a picture.