Planes of Thought and Future of Machine Programming

We discuss deterministic intent folding (DIF) and how it can help improve machine learning systems, beyond neural networks and in conjunction with large language models (LLMs). We further discuss different mechanisms of reasoning: concrete, abstract, and meta. We correlate these ideas as a fusion across the principle forms of logic. We start with an examination of Yann LeCun's world model approach and why that approach may have value for Dr. LeCun, but may not be the most appropriate for machine programming (MP). We detail this by scrutinizing the overlap of DIF reasoning with regard to first order, second order, third order, and higher order logics.