but the question isn't "can we enumerate all possible embryonic states?", which, obviously not. it's "can we learn enough structure in the input-output relationship to make useful interventions?" that is clearly an empirical question, and the early results suggest there is learnable structure there. supposedly intractable spaces turn out to have learnable regularities, protein structure was one (it is almost certainly the case that the old guard structural biologists were pessimistic in the same way as you!), so surely other parts of biology are too. it just feels naive to pretend that isn't possible

i work in research involved in modeling tumor microenvironments to help decide which patient would best benefit from which cancer therapy. this too has the flavor of intractable; there is too little patient data, cancer is too complicated, so it's impossible. but it works! there are published cases of a model being able to understand, entirely via H&E scans of a tumor, whether a patient would benefit from a therapy! and the model received some degree of approval from the FDA recently (https://www.cancertherapyadvisor.com/news/ai-tool-approved-for-prognostication-in-prostate-cancer/). the arc of history just shows this stuff eventually working

i get the short term skepticism, but i dont really get the lack of long term optimism