[HN Gopher] IBM and NASA open-source largest geospatial AI found...
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       IBM and NASA open-source largest geospatial AI foundation model on
       Hugging Face
        
       Author : anigbrowl
       Score  : 117 points
       Date   : 2023-08-05 19:05 UTC (3 hours ago)
        
 (HTM) web link (newsroom.ibm.com)
 (TXT) w3m dump (newsroom.ibm.com)
        
       | pkdpic wrote:
       | In case anyone's wondering what the model does (like I was).
       | 
       | > With additional fine tuning, the base model can be redeployed
       | for tasks like tracking deforestation, predicting crop yields, or
       | detecting and monitoring greenhouse gasses. IBM and NASA
       | researchers are also working with Clark University to adapt the
       | model for applications such as time-series segmentation and
       | similarity research.
        
       | version_five wrote:
       | Discussed two days ago, 296 points and 78 comments:
       | https://news.ycombinator.com/item?id=36985197
        
       | Y_Y wrote:
       | [flagged]
        
       | hardware2win wrote:
       | Whats the deal about hf?
        
         | phero_cnstrcts wrote:
         | Dunno, but I'm not sure I like the name.
        
           | version_five wrote:
           | I don't like it, on one hand it's really sappy in a non-
           | endearing way, on the other,
           | https://avp.fandom.com/wiki/Facehugger (which incidentally is
           | probably some foreshadowing of the time when the VCs start
           | trying to get their returns)
           | 
           | It's mildly embarrassing to have to refer to it in a
           | professional context.
        
           | kbutler wrote:
           | AI model-sharing platform, named after the emoji:
           | https://blog.emojipedia.org/emojiology-hugging-face/
           | 
           | (I don't know that I've ever attempted to paste an emoji into
           | HN before, and I'm rather glad to learn it strips them out,
           | though they're fine in other contexts.)
        
       | RosanaAnaDana wrote:
       | This is such a weird headline and dataset. It's not a very large
       | model, esp for geospatial. And the data set is microscopic, not
       | even 1k image tiles.
       | 
       | A typical geospatial UNET would be trained on any where from 10x
       | to 100x this much data.
       | 
       | This is more like a toy dataset I would give an intern to play
       | on. But to be clear, one would need much much much more data do
       | do something interesting on. Likewise, there are a lot of data
       | filtering and data processing considerations that come into play
       | with satellites like clouds, ascension or descenion, averaging to
       | try and get fewer clouds. Satellite and all remote sensing ML is
       | tricky stuff.
        
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       (page generated 2023-08-05 23:00 UTC)