Be - before you get on the next part l let me just point out that s there 's  there 's a  a pretty nice   relationship between what you 're talking about doing and what you 're talking about doing there. Right ?
Yeah.
So ,  it seems to me that , you know , if you take away the  the   the difference of this  primary features ,  and , say , you use  as we had talked about maybe doing  you use P - RASTA - PLP or something for the  the primary features ,  um , then this feature discovery ,  uh , uh , thing  is just what he 's talking about doing , too , except that he 's talking about doing them in order to discover  intermediate categories that correspond  to these  uh , uh , what these sub - features are  are  are  are showing you. And , um ,  the other difference is that , um ,  he 's doing this in a  in a multi - band setting , which means that he 's constraining himself  to look across time in some f relatively limited , uh , uh , spectral extent. Right ? And whereas in  in this case you 're saying " let 's just do it unconstrained ". So they 're  they 're really pretty related and maybe they 'll be  at some point where we 'll see the  the connections a little better and  connect them.
Hmm.