This image contrasts traditional programming, where developers must explicitly code rules and logic (shown with a flowchart and a thoughtful programmer), with AI, where neural networks automatically learn patterns from large amounts of data (depicted with a network diagram and a smiling programmer). It illustrates the paradigm shift from manually defining rules to machines learning patterns autonomously from data.
The image titled “New Coding” illustrates the historical evolution of programming languages and the emerging paradigm of AI-assisted coding.
On the left side, it shows the progression of programming languages:
“Bytecode” (represented by binary numbers: 0110, 1001, 1010)
“Assembly” (shown with a gear and conveyor belt icon)
“C/C++” (displayed with the C++ logo)
“Python” (illustrated with the Python logo)
Below these languages is text reading “Workload for understanding computers” with a blue gradient arrow, indicating how these programming approaches have strengthened our understanding of computers through their evolution.
The bottom section labeled “Using AI with LLM” shows a human profile communicating with an AI chip/processor, suggesting that AI can now code through natural language based on this historical programming experience and data.
On the right side, a large purple arrow points toward the future concepts:
“New Coding As you think”
“With AI” (in purple text)
The overall message of the diagram is that programming has evolved from low-level languages to high-level ones, and now we’re entering a new era where AI enables coding directly through human thought, speech, and logical reasoning – representing a fundamental shift in how we create software.
From Claude with some prompting This image titled “IF THEN” by AI illustrates the evolution from traditional programming to modern AI approaches:
Upper section – “Programming”: This represents the traditional method. Here, programmers collect data, analyze it, and explicitly write “if-then” rules. This process is labeled “Making Rules”.
Lower section – “AI”: This shows the modern AI approach. It uses “Huge Data” to automatically learn patterns through machine learning algorithms.
Large-scale data → Machine Learning → AI model generation
Key differences:
Traditional method: Programmers explicitly define rules
AI method: Automatically learns patterns from data to create AI models that include basic “if-then” logic
The image effectively diagrams the shift in programming paradigms. It demonstrates how AI can process and learn from massive datasets to automatically generate logic that was previously manually defined by programmers.
This visualization succinctly captures how AI has transformed the approach to problem-solving in computer science, moving from explicit rule-based programming to data-driven, pattern-recognizing models.
From DALL-E with some prompting The image depicts the evolution of decision-making processes from manual to automated, facilitated by AI and Digital Transformation (DT). Initially, decisions were made by humans based on specific conditions (IF condition THEN action). This manual approach did not involve computing. With DT, the process becomes automated through computing, making it faster and more efficient. The transition to AI and Machine Learning (ML) marks a further evolution where decisions are not just automated but are also data-driven, increasing accuracy and the ability to adapt to complex situations. The visual suggests a shift from human-based decision-making to a more sophisticated, automated, and intelligent system of processing and action-taking, indicative of modern advancements in technology.
Lechuck Park 