I work for USGS EROS Data Center and this is basically our life. Taking remote sensing data and generating various models to determine all sorts of things. Yes, I agree with much of what people are saying. This means very little to the public except when it matters. Some of the projects I work on determine famine early warning systems across the globe so that governments can make sure they have enough food for their populations. Others depend upon the health of crops. How people are using the land (land cover). How much cheatgrass and other things are there that affects rangelands (it cuts the tongues of cows for instance). We use super computers (Cray HPCs with GPUs) and deep learning (PyTorch/Keras/TF). But, given all of the above, I'm not sure how this would help me to do my job.
IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
51–60 of 90 posts
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#52The demo misidentifies West Bengal, India flood to a location in Pakistan. Either the title is incorrect or the model is simply wrong. The demo should have been proof read before publishing :/ https://youtu.be/9bU9eJxFwWc?t=28
Well, it also says Indus which is in Pakistan. But, good catch, weird mistake!
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#53I wish the press release had a bit more detail about what this model actually does and whether it's actually useful for the suggested use cases. However, make no mistake: this is for the scientific community and will not help geospatial data to be commercialized. No one cares about your geospatial crop model or that you can identify energy infrastructure or that there's some activity around that copper mine. Well, at…
> Satellite data is extremely idiosyncratic. It's coarse (~10m at best), infrequent (every few days at best), and oh you have to deal with the fact that the planet is covered in 50% clouds at any moment. Are the coarseness and cloud aspects going to become less of a factor now that there are commercial high-resolution synthetic aperture radar imagery providers? I'm just a hobbyist, but the imagery I've seen is sharp…
Super interesting. Hadn’t heard of SAR before. Quickly reading about it, it seems like it works like lidar, what’s the difference between the two techniques? Is SAR like “lidar for space”?
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#54Earlier quoted context omitted.
We want much larger models, not because they're "cool," but because they exhibit capabilities that tiny models don't exhibit, including the ability to perform new tasks for which they were not trained, without requiring finetuning.
I question the assumption that fine-tuning should always be avoided. If a model is going to be used many times for a specific use case, it is far cheaper and uses far less energy to fine tune a small model once and run it on cheap low-power hardware than it is to continuously run a huge, do-everything model on expensive, high-power hardware. Enormous models are great for exploration and for general purpose applicatio…
We're talking about different things. You're talking about finetuning models to tasks known in advance. I'm talking about the ability to generalize to new tasks: https://arxiv.org/pdf/2206.07682. Please don't argue against a straw-man.
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#55I wish the press release had a bit more detail about what this model actually does and whether it's actually useful for the suggested use cases. However, make no mistake: this is for the scientific community and will not help geospatial data to be commercialized. No one cares about your geospatial crop model or that you can identify energy infrastructure or that there's some activity around that copper mine. Well, at…
what happened with your company?
he ran into the ground without a vision and excess spending on bar tabs and the startup life
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#56Earlier quoted context omitted.
> Satellite data is extremely idiosyncratic. It's coarse (~10m at best), infrequent (every few days at best), and oh you have to deal with the fact that the planet is covered in 50% clouds at any moment. Are the coarseness and cloud aspects going to become less of a factor now that there are commercial high-resolution synthetic aperture radar imagery providers? I'm just a hobbyist, but the imagery I've seen is sharp…
Super interesting. Hadn’t heard of SAR before. Quickly reading about it, it seems like it works like lidar, what’s the difference between the two techniques? Is SAR like “lidar for space”?
I think one difference is that with SAR the sensor needs to be moving.
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#57Earlier quoted context omitted.
> Satellite data is extremely idiosyncratic. It's coarse (~10m at best), infrequent (every few days at best), and oh you have to deal with the fact that the planet is covered in 50% clouds at any moment. Are the coarseness and cloud aspects going to become less of a factor now that there are commercial high-resolution synthetic aperture radar imagery providers? I'm just a hobbyist, but the imagery I've seen is sharp…
Super interesting. Hadn’t heard of SAR before. Quickly reading about it, it seems like it works like lidar, what’s the difference between the two techniques? Is SAR like “lidar for space”?
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Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#58Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#59This is cool -- I built something very close to this and I think it's really useful for researchers to have access to pre-trained models. Training something like this isn't that challenging given the relatively limited scale (100M parameters), but most grad students working in GIS won't have the resources or time to do it.
I think partnering with Huggingface was a good move, because it means the interface is easy to use. This difficulty in actually using pre-trained research models was one of the design goals of Moonshine[1] and I have no doubt that if it was IBM alone it wouldn't be nearly as easy to use.
Will be excited to hear if this works for people! Always cool to see your idea validated even if nobody really uses your tool :)
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#60I wish the press release had a bit more detail about what this model actually does and whether it's actually useful for the suggested use cases. However, make no mistake: this is for the scientific community and will not help geospatial data to be commercialized. No one cares about your geospatial crop model or that you can identify energy infrastructure or that there's some activity around that copper mine. Well, at…
PlanetScope is 3.7m and captures the full land area of the earth daily (minus cloud cover, of course): https://www.planet.com/products/planet-imagery/
Disclaimer: I work for Planet.
I also disagree with the assertion "no one will actually pay you." Read pages 26-28 of the quarterly report for more information.