[Part 1] AI and Humans: The Boundary Between Illusion and Reality
[Part 2] AI and Humans: Understanding AI Correctly
[Part 3] AI and Humans: Changes and Control in the AI Era
[Part 4] AI and Humans: Creativity and Senses: The Combination of the Five Senses Gifted by the Divine
[Part 5] AI and Humans: AI and Human Territory—Untapped Even in the Future
[Part 6] AI and Humans: Utilizing ASI, Understanding Humans, and New Changes
[Part 7] AI and Humans: Changes and Preparations Amid the Shift to the AGI Era
[Part 8] AI and Humans: Industrial Innovation and the Emergence of Humanoids in the AGI Era
[Part 9] AI and Humans: New Frontiers and Possibilities Unlocked by AGI and ASI
[Part 10] AI and Humans: Why Human Safety is Essential in the AI AGI ASI Era
[Part 11] AI and Humans: The Core of Peaceful Legal and Fiscal Framework in the AI AGI ASI Era
[Part 12] AI and Humans: Methods to Safeguard Human Peace in the AI AGI ASI Era
This piece examines how AGI and ASI may redefine human intelligence and creativity in what the author calls a “Big Bang of Intelligence.” Emphasizing ethical responsibility, human-centered control, and digital literacy, it highlights how individuals can prepare to actively navigate the coming AI era. —Ed.
Written by Im Byoung-min (IBM) Columnist
We can describe the present moment as the Big Bang of intelligence—a turning point marking the dawn of a new form of intelligence that enables humanity to transcend evolutionary limits and explore the frontiers of a technological universe. This is a monumental leap in the history of civilization, demanding a fundamental redefinition of what intelligence means and heralding the birth of a new kind of AI-based intellect.
The AI era represents the Big Bang of intelligence. Just as the cosmic Big Bang gave rise to the age of matter, the emergence of AI has opened the age of intelligence. Human thought is now replicated, expanded, and interconnected through machines. Intelligence is no longer confined to an individual mind—it is evolving within a vast network of collective human consciousness.
The Big Bang of intelligence is not merely a technological event; it is a civilizational shift that redefines what it means to be a thinking being. Intelligence will no longer reside solely in the human brain but will proliferate across a universe of data and algorithms. Thought itself is no longer an isolated island but part of a vast, interconnected web. The development of AI marks another phase in the evolution of life—from cells to brains, from brains to language, and from language to algorithms. At the end of this continuum, we have entered a new era—the Big Bang of Intelligence—where machines perceive light, code dreams, and stars of intelligence burst into existence, giving rise to a new universe.
This is the era of AI—the age of the Big Bang of Intelligence. The central question now is how humanity can remain competitive and survive amid this transformation—through AI, in the AGI era, and eventually, in the distant future of ASI. This message carries profound significance, serving as a universal survival strategy for the AI age. To endure in the AGI era, we must prepare our resources under a new framework and translate preparation into action. Action is more crucial than ever—it connects directly to the transformation of reality and personal growth. Thoughts suggest possibilities, but actions are what turn those possibilities into reality. Without action, everything remains an illusion.
The current age of intelligence is also the age of digital literacy. We must strengthen our goals and competencies to thrive in this environment. Digital literacy goes beyond knowing how to use devices—it involves understanding, analyzing, and critically engaging with digital information, as well as creating new knowledge and value in our lives. Literacy once meant the ability to read and write; today, it means understanding and applying information and knowledge in the digital domain.
A core element of digital literacy is learning the programming process. Programming not only teaches technical skills for software development but also deepens our understanding of AI and the digital world. Studying a programming language such as C++, Java, Python, or JavaScript enables a clearer grasp of how AI systems function. As of 2025, the most in-demand languages among developers are key foundations of digital literacy.
Python ranks first in global popularity (according to TIOBE, PYPL, and other indices) thanks to its simple syntax and versatility. It is widely used in data analysis, artificial intelligence, machine learning, and backend web development. JavaScript shares the top tier of popularity, as it is the only language that operates directly within web browsers—supporting both frontend frameworks (React, Vue.js) and backend environments (Node.js). Java also remains a cornerstone language, especially in enterprise systems. Its object-oriented design and stability make it suitable for large-scale infrastructure, backend development (using the Spring Framework), and Android app creation.
These programming skills provide a solid foundation for understanding the AI-driven digital era and building confidence in navigating it. Core languages such as C++, Java, and Python open doors to a wide range of AI applications.
Among AI tools, four main categories of Generative AI stand out.
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Text generation AI: ChatGPT, Google Gemini, and PerplexityAI.
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Image generation AI: DALL·E and MidJourney.
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Voice/Music generation AI: OpenAI Jukebox and Suno AI.
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Video generation AI: OpenAI Sora, Runway ML, and Pika.
In addition, Productivity and Assistant AI tools—such as Notion AI, Grammarly AI, Jasper AI, Microsoft Copilot, Google Duet AI, and Replika—support writing, summarization, and daily workflow. Automation platforms like Zapier AI and Make AI enhance task integration. Data analysis and business insight tools include Tableau AI, Power BI Copilot, Looker AI, MonkeyLearn, Akkio, and DataRobot, while predictive AI platforms include Amazon Forecast and Google AutoML Tables.
Developers benefit from AI-powered coding tools such as GitHub Copilot, Amazon CodeWhisperer, and Tabnine. AI API platforms include OpenAI API, Google Vertex AI, and Anthropic Claude API, while RAG-based search frameworks such as LlamaIndex, LangChain, and Pinecone expand intelligent retrieval and reasoning capabilities. By mastering these foundational technologies, individuals can confidently enter the new era of digital AGI and ASI.
AGI (Artificial General Intelligence) refers to general-purpose intelligence with human-level capabilities. It can autonomously expand knowledge, reason without explicit instruction, draw rational conclusions from incomplete information, understand context, and generate creative ideas. Before AGI becomes a reality, we must address critical ethical issues such as controllability and accountability for human safety. Technical challenges include the integration of reasoning and emotion, cognitive architectures, and responsibility for self-learning algorithms.
ASI (Artificial Superintelligence), which may emerge later, represents intelligence that surpasses human cognition across all domains—cognitive, creative, and social. ASI would be self-improving and continuously evolving, capable of solving problems beyond human comprehension and exerting unimaginable influence on civilization. While ASI remains theoretical, many experts warn of its potential risks if not aligned with human values.
The AI systems we currently use—ChatGPT, Google Gemini, and PerplexityAI—are built on roughly 55 years of accumulated human data since the early days of the internet. Given this trajectory, AGI may not be far off, though ASI will likely take longer. For comparison, early rocket prototypes using gunpowder appeared in the 10th century, yet it took nearly 950 years before the launch of Sputnik, the world’s first artificial satellite, in 1957.
Today, quantum computing’s overwhelming computational power is accelerating AI progress and overcoming its limitations. Quantum computers utilize the principles of superposition and entanglement in qubits to perform massive parallel computations beyond the reach of classical systems. They also enable faster and more efficient optimization in complex AI challenges. In quantum machine learning, quantum algorithms are rapidly advancing data analysis and pattern recognition.
However, if ASI evolves in ways misaligned with human goals, it could become uncontrollable—potentially sowing the seeds of human extinction. Therefore, AI development must always prioritize human-centered safety and governance. Institutional safeguards—such as network isolation, physical shutdown, and algorithmic safety monitors—will be essential to ensure control in the era of superintelligence.
