training methods so as I mentioned like there's a lot of things that could be going on current techniques are brittle they're memorizing and so generalizing they're exploiting spurious correlations you know also stop learning once you want to get to you know memorizing your training set you just wall turns off because the gradient ties ISM training lost goes to zero so it just kind of feels incorrect so there's like a lot of different routes we could go down to make progress we can do better models and architectures we could do more data