Just Like Humans Do (JLHD) :: Additional Modalities needed for Advanced AI to Accurately Understand and Reason on Real-World Physics and Environments

Abstract Current advanced Artificial Intelligence (AI), including Artificial General Intelligence (AGI) approaches like the Neural-Matrix Synaptic Resonance Network (NM-SRN AGI) and contemporary Large Language Models (LLMs), has made extraordinary strides. However, a significant frontier remains: the deep, intuitive understanding and reasoning capabilities regarding real-world physics and dynamic environments that humans exhibit. This paper introduces the "Just Like Humans Do (JLHD)" multi-modalities, a proposed enhancement framework designed to be integrated into advanced AI, specifically targeting an NM-SRN AGI v8.0 Model. The JLHD framework posits that three additional, deeply interwoven modalities are crucial: 1) Deepened Embodiment Dimensions providing a rich self-model for the AI; 2) A highly contextualized World View of the AI's environment; 3) Precise, SLTF-defined OBJECT PROPERTIES for all entities within the AI's Known Local Environment (KLE), detailing verifiable physical attributes like weight, dimensions, material, and density; and 4) A Simple/Complex Physics Engine (SCPE) that uniquely leverages "DRAW CODE" RUNS (DCRs). This DCR mechanism allows the AI to generate segments of executable code (e.g., Python) to model and reason about physics, kinematics (including anatomical - PKPC), and fluid dynamics as an "extended thought process," rather than relying solely on pattern matching or static simulations. The framework also allows for optional integration with Emotional MimicWare to provide affective context. The anticipated outcome is an AI possessing "Animus LEVEL" world data, enabling accurate physical reasoning, enhanced operational safety, and significantly broadened applicability in complex domains such as robotics, nanotechnology, Asteroid Defence Systems (ADSYS), and beyond. The JLHD modalities are designed to align seamlessly with the core tenets of Definitive AI and 3rd Meta Thinking, ensuring that this enhanced physical understanding is built upon verifiable data and deterministic reasoning processes, paving the way for even more capable and trustworthy AGI.