BioAI faces 'fuzzy API' challenge in drug discovery
TL;DR. AI in biology struggles with complex, interconnected biological feedback loops that lack the clear APIs of traditional software development. - Drug discovery involves probabilistic hypotheses and numerous interdependent variables, not clean input-output interfaces. - Unlike software, biology's 'APIs' are ambiguous, making it hard to validate targets or drug candidates in isolation. - This complexity requires AI models capable of handling multifaceted, uncertain data beyond simple linear dependencies.
- Biology lacks clean, composable APIs seen in software, complicating AI applications.
- Drug discovery output is probabilistic and depends on many interacting factors.
- Fuzzy APIs in biology make AI model training and validation inherently difficult.
- Success depends on AI handling complex biological uncertainties beyond simple interfaces.
Sources
- AI for Bio has a Fuzzy API problem — ankitg.me