According to Chris Olah, the scientific principles of biology, particularly in terms of evolution, are highly relevant to understanding deep learning and model interpretability. Olah draws a direct analogy, stating that biology relates to evolution as interpretability does to gradient descent in machine learning (source: Chris Olah on Twitter, May 13, 2025). For crypto traders, this insight suggests that advances in interpretability could lead to more transparent AI-driven trading strategies, potentially impacting the predictability and reliability of automated crypto market analysis tools. As deep learning interpretability improves, traders may gain better visibility into AI decision-making, influencing risk assessment and trading confidence.