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WALDO: Whereabouts Ascertainment for Low-Lying Detectable Objects

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Re: WALDO: Whereabouts Ascertainment for Low-Lying Detectable Objects

#21

Post by wongarsu »

ulnarkressty wrote: post #4

What would be legitimate civilian uses for this technology apart from [0]? After the 10k drone swarm the other day and the pager attacks all I can think of is slaughterbots, which is genuinely freaking me out. [0] - https://xkcd.com/2128/

Buy satellite images of walmart parking lots, run this model to count the cars. Repeat this every week, buy walmart stock when the number goes up and short walmart when the number goes down.

Buy satellite images of container ports, count the number of containers, predict performance of economy based on containers and invest accordingly.

Presidential candidate has an open-air rally and you want to figure out how many people are attending? Buy a satellite image scheduled for that exact hour and let WALDO count the people.

Financing a number of large construction projects but don't trust the progress reports? Buy regularly scheduled satellite images and let WALDO count the number of trucks and construction vehicles.

Want to invest in the construction business? Guess what, buy satellite images, count trucks and construction vehicles, make investment decisions based on that

Re: WALDO: Whereabouts Ascertainment for Low-Lying Detectable Objects

#22

Post by PTOB »

AtlasBarfed wrote: post #19
throwup238 wrote: post #3

> 'arm/mil' --> this class detects certain types of armored vehicles (very unreliable for now, don't use it yet) Living near a bunch of the military bases, this is what I really need. My suburban defense system keeps mistaking USPS trucks for APCs. I haven’t received any mail for months. Sidenote: what are the export restriction?

Ai is going to super charge off grid antigov nuts libertarians?

Not just them. I predict it will extend to all classes of folks who use popular schemas for naming taken from self-isolating social forums.

Re: WALDO: Whereabouts Ascertainment for Low-Lying Detectable Objects

#23

Post by walrus01 »

wongarsu wrote: post #21
ulnarkressty wrote: post #4

What would be legitimate civilian uses for this technology apart from [0]? After the 10k drone swarm the other day and the pager attacks all I can think of is slaughterbots, which is genuinely freaking me out. [0] - https://xkcd.com/2128/

Buy satellite images of walmart parking lots, run this model to count the cars. Repeat this every week, buy walmart stock when the number goes up and short walmart when the number goes down. Buy satellite images of container ports, count the number of containers, predict performance of economy based on containers and invest accordingly. Presidential candidate has an open-air rally and you want to figure out how many…

There's multiple commercial data feed providers for AIS from pretty much every sizable cargo ship in the world (that isn't operating in some weird grey market economy like the Russian sanctions-evading tankers), which are already used to correlate aerial and SAR data with the self-reported AIS positions of vessels.

Re: WALDO: Whereabouts Ascertainment for Low-Lying Detectable Objects

#24

Post by rasz »

adontz wrote: post #7

I wonder if these achievements are related to war in Ukraine. Do scientists suddenly receive more funding or something? Or it just happens? Is there a non public version with very reliable arm/mil? Is there a version which can reliably distinguish T-80 with and without Z?

Iv seen Ukrainians experimenting with YOLO and it was terrible. Every second bush/tree was flipping between person/tree/rock/nothing. Looks like the model was trained on clean urban environment videos.

Re: WALDO: Whereabouts Ascertainment for Low-Lying Detectable Objects

#25

Post by mapt »

wongarsu wrote: post #20
adontz wrote: post #7

I wonder if these achievements are related to war in Ukraine. Do scientists suddenly receive more funding or something? Or it just happens? Is there a non public version with very reliable arm/mil? Is there a version which can reliably distinguish T-80 with and without Z?

A big part is that training image detection is incredibly easy today. YOLO is a great network with reasonably intuitive tooling. Anyone with a set of images can start labeling them, copy-paste a couple lines into a jupyter notebook and make a decent YOLO finetune. The difficulty is in the training data, both acquiring it and labeling it. Hence why the readme of WALDO alludes so much to their semi-synthetic data. That…

Commercial satellite images? With somewhere between 30cm and 100cm resolution? Looking for the letter 'Z' painted on a sidewall of the vehicle?

Rough.

Medium altitude aerial drone imagery would do it, though - just a matter of building something so cheap & plentiful that it's not worthwhile to shoot down.

Who knows, maybe we've given Ukraine the keys to the castle and they're getting a steady stream of 10cm imagery from the NRO.

Re: WALDO: Whereabouts Ascertainment for Low-Lying Detectable Objects

#26

Post by throwup238 »

stephanst wrote: post #16
throwup238 wrote: post #3

> 'arm/mil' --> this class detects certain types of armored vehicles (very unreliable for now, don't use it yet) Living near a bunch of the military bases, this is what I really need. My suburban defense system keeps mistaking USPS trucks for APCs. I haven’t received any mail for months. Sidenote: what are the export restriction?

that class never really worked and has been removed from the new version of WALDO FYI, it’s not a military thing and shouldn’t be used as such

Don’t worry this is a suburban defense system. Purely civilian targets.

I created it after joining my neighborhood NextDoor.

Re: WALDO: Whereabouts Ascertainment for Low-Lying Detectable Objects

#27

Post by stephanst »

throwup238 wrote: post #9
ulnarkressty wrote: post #4

What would be legitimate civilian uses for this technology apart from [0]? After the 10k drone swarm the other day and the pager attacks all I can think of is slaughterbots, which is genuinely freaking me out. [0] - https://xkcd.com/2128/

> The basic model shared here, which is the only one published as FOSS at the moment, is capable of detecting these classes of items in overhead images ranging in altitude from about 30 feet to satellite imagery with a resolution of 50cm per pixel or better. It's not just for drones, it's for any overhead imaging. This can be used for all kinds of things like search and rescue, traffic monitoring, watching for wildfi…

it is being used a lot for disaster response and traffic monitoring yep. Also surprisingly to me for analytics on utilisation of all kinds of infrastructure y trading firms. One of the bigger motivations to make it free was to see where people use the base model to understand whether there is a market there for a fine-tuned / more specialized version.

Re: WALDO: Whereabouts Ascertainment for Low-Lying Detectable Objects

#28

Post by stephanst »

throwawaymaths wrote: post #18

I worked for a place where we needed to know with precision where in space a large object was relative to a large area we had full control over. I wonder if this could be used in reverse by say dropping QR codes on the ground, using the algorithm to track relative positions and doing the reverse operation from there

you don’t need AI for that, classic computer vision will work fine ;)

Re: WALDO: Whereabouts Ascertainment for Low-Lying Detectable Objects

#29

Post by stephanst »

rasz wrote: post #24
adontz wrote: post #7

I wonder if these achievements are related to war in Ukraine. Do scientists suddenly receive more funding or something? Or it just happens? Is there a non public version with very reliable arm/mil? Is there a version which can reliably distinguish T-80 with and without Z?

Iv seen Ukrainians experimenting with YOLO and it was terrible. Every second bush/tree was flipping between person/tree/rock/nothing. Looks like the model was trained on clean urban environment videos.

generalisation is 90% of the problem yep. This model is trained with a lot of augmentations and quite diverse data, but it still really needs fine tuning to specific use cases to get great efficiency unless you don’t care about false positives.

Re: WALDO: Whereabouts Ascertainment for Low-Lying Detectable Objects

#30

Post by stephanst »

wongarsu wrote: post #20
adontz wrote: post #7

I wonder if these achievements are related to war in Ukraine. Do scientists suddenly receive more funding or something? Or it just happens? Is there a non public version with very reliable arm/mil? Is there a version which can reliably distinguish T-80 with and without Z?

A big part is that training image detection is incredibly easy today. YOLO is a great network with reasonably intuitive tooling. Anyone with a set of images can start labeling them, copy-paste a couple lines into a jupyter notebook and make a decent YOLO finetune. The difficulty is in the training data, both acquiring it and labeling it. Hence why the readme of WALDO alludes so much to their semi-synthetic data. That…

Yep exactly. Commercial satellite inagery isn’t great for detecting anything the size of a tank (yet) but drones will get you there. The real difficulty for detecting anything like this is the training data, IMO that’s the interesting part of the problem. The actual AI models are democratized and getting better every day, but few people focus on the training data. I have my own pipelines for generating data that I have been improving over >3 years, which I have used for commercial clients to make AI systems for specific use cases. WALDO is a way of dogfooding those data synth methods. I am constantly toying with the idea of opening up the data synth stuff as a service company or as an API, but my feeling is there is not quite enough demand yet to warrant that. This is changing very quickly though and now might be the right time…
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