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Plan another training run for Clay v1 #283
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Possibly relevant? I think the authors make a good case for focusing efforts on improving vision representations in multi modal llms to make truly flexible models in terms of accepted inputs and tasks they can address. and improving evaluation benchmarks like COCO to test more than just MaP https://arxiv.org/pdf/2406.16860 |
https://x.com/osanseviero/status/1807679660328620099 ^ Possible funding source for model distillation work. |
Ok @brunosan could you help determine a priority list here? The other thing I'd love to see is if we can add MODIS data, as long as the architecture won't need to change |
Update: MODIS has been just added. #311 |
Curious why CC-By is a blocker? this article indicates that the model can be used, even commercially, with attribution. https://satellogic.com/2024/05/01/satellogic-open-source-release-a-large-dataset-of-high-resolution-imagery-for-ai-model-training/ For any high res dataset sourced from a commercial provider, I expect they will at least want this kind of attribution. Having a model that understands submeter resolutions in addition to coarser resolution public imagery would be very valuable. |
This is for foundational training. If we train with data that requires attribution, we understand it means that the attributions carries over to the trained model, and all users of Clay need also to attribute it, which would bring higher friction. E.g. If Planet incorporates Clay on the pipeline, they might need to attribute Satellogic when using Clay. This of course does not prevent us, or anyone, to make a finetuned version of Clay with Satellogic, or Maxar or Planet data. That version would carry the licenses of the data used. fwiw, Clay is trained with NAIP and LINZ, which are both well under 1 meter. (32% of the 70 million chips) PS: AFAIK it is not legally settled if the license of each training data carries over to the trained model. In LLMs the practice seems not to, but we choose to take the safer position and only use fully open data. |
Update: We are conducting another model run for CLAY with the following updates:
We are running several experiments with these changes, and based on the results, the successful adjustments will be included in the new model run. Keep track of the changes in dev branch. |
Ideas to add are
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