> domain-specific models will always outperform generalist ones That's only true assuming you habe enough data to train a domain-specific model / expertise to

> domain-specific models will always outperform generalist ones That's only true assuming you habe enough data to train a domain-specific model / expertise to train it and test it correctly. I've encountered cases where an image recognition task could be accomplished well with a very general model like CLIP, but people still fine-tuned another model on their own small data set because that's considered better. A domain specific model might be more likely to fail on weird outliers not present in the small domain specific training data. > could spell disaster for OpenAI Nah I don't think so. They are not all in on one specific model architecture. If the current architecture is found to have serious unfixable flaws then they'll just change architecture.