do 200,000 - to kind of get a good similarity measure you can do something smaller than that the trade-off there is between sort of like the number of data points you're using and serve the actual number of like kind of vectors you're trying to find similarities over this is why people so so okay so I think there are two parts to this firstly like people I think there's some outs of people like using transfer learning simply because they've seen other people do it and kind of you train it and then you can do this process and it sort of