Source: The Next Web
The gap between computational throughput and actual therapeutic outcomes is widening. Novartis and other pharma players can now screen millions of molecular candidates daily, but this velocity hasn't translated into cures for diseases where it matters most—Alzheimer's, Huntington's. The constraint isn't finding candidate molecules. AI excels at optimization within known chemical spaces. The hardest problems require fundamental biological insights that no amount of screening can generate. Health chatbots illustrate the same dynamic: they improve at pattern-matching language while becoming less reliable at medical advice. The architectural advantage that enables speed in pattern recognition undermines reliability where stakes are high.