The article further explores the metaphor by examining the historical context of AI, where early approaches relied heavily on recursive algorithms and hierarchical data structures (Yin), but were eventually outperformed by iterative, linear algebra-based methods (Yang) like neural networks. The authors suggest a synthesis of both approaches, advocating for a functional language with a strong positive side and a limited negative side. They also discuss the language Lucid, traditionally seen as a functional language, but argue it is more iterative (Yang) due to its emphasis on streams and indexing. The article concludes by suggesting that Lucid could benefit from incorporating a small amount of functional features (Yin), similar to how PyFL was enhanced by adding iteration.
Key takeaways:
- The paper discusses the balance between recursion (Yin) and iteration (Yang) in programming, highlighting the strengths and weaknesses of each approach.
- PyFL, an experimental functional language, is extended with a declarative while construct to introduce controlled iteration, aiming to balance recursion and iteration.
- The article argues that while functional languages like Haskell are successful, they often miss the practicality of iteration, as seen in the success of iterative approaches in AI and machine learning.
- Lucid, traditionally considered a functional language, is re-evaluated as an iterative language due to its emphasis on streams and indexing, suggesting it could benefit from incorporating limited higher-order functions.