TLDR? "The Bitter Lesson of AI-driven drug discovery is that methods that primarily focus on raising the quantity of hypotheses available to be pursued are bound to not be transformative for drug discovery"
BinaryIgor•5mo ago
And this nugget:
"Unfortunately, working on hypothesis generation remains extremely attractive to AI in drug discovery researchers: (1) day-to-day generating more and more ideas subjectively feels like progress is being made - after all, you’ve created an enormous and ever-growing database of almost-medicines - and (2) science has trained researchers to value invention over doing the hard work to validate ideas, leading to a world in which everyone wants to be the idea-person and comparatively almost no-one wants to be doing the hard and unrewarding work to take these ideas all the way. And so, AI-driven drug discovery researchers still largely pursue hypothesis-generation machines and consequently, as a field, we unfortunately continue to make the same mistakes."
attogram•5mo ago
BinaryIgor•5mo ago
"Unfortunately, working on hypothesis generation remains extremely attractive to AI in drug discovery researchers: (1) day-to-day generating more and more ideas subjectively feels like progress is being made - after all, you’ve created an enormous and ever-growing database of almost-medicines - and (2) science has trained researchers to value invention over doing the hard work to validate ideas, leading to a world in which everyone wants to be the idea-person and comparatively almost no-one wants to be doing the hard and unrewarding work to take these ideas all the way. And so, AI-driven drug discovery researchers still largely pursue hypothesis-generation machines and consequently, as a field, we unfortunately continue to make the same mistakes."