CRASS is the first project of apergo.ai. It’s aim is to create the decisive step to make causal and counterfactual reasoning of neural networks testable and have clear standards on how to judge counterfactual reasoning in AI in general.
Moreover, CRASS got accepted to be part of Google’s and OpenAI’s BIG-Bench which in turn is part of the broader effort to develop PaLM (a 560B parameter model). Visit the blog post and see Google’s inclusion of a CRASS in the dataset: