This image visualizes the core philosophy that “In the AI era, vector-based thinking is needed rather than simplified definitions.”
Paradigm Shift in the Upper Flow:
- Definitions: Traditional linear and fixed textual definitions
- Vector: Transformation into multidimensional and flexible vector space
- Context: Structure where clustering and contextual relationships emerge through vectorization
Modern Approach in the Lower Flow:
- Big Data: Complex and diverse forms of data
- Machine Learning: Processing through pattern recognition and learning
- Classification: Sophisticated vector-based classification
- Clustered: Clustering based on semantic similarity
- Labeling: Dynamic labeling considering context
Core Insight: In the AI era, we must move beyond simplistic definitional thinking like “an apple is a red fruit” and understand an apple as a multidimensional vector encompassing color, taste, texture, nutritional content, cultural meaning, and more. This vector-based thinking enables richer contextual understanding and flexible reasoning, allowing us to solve complex real-world problems more effectively.
Beyond simple classification or definition, this presents a new cognitive paradigm that emphasizes relationships and context. The image advocates for a fundamental shift from rigid categorical thinking to a nuanced, multidimensional understanding that better reflects how modern AI systems process and interpret information.
With Claude
Lechuck Park 