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Data types label what data means so computers know whether to treat it as numbers, text, logic, or collections. Integers and floats represent countable vs continuous quantities and use different internal representations, which affects precision. Characters and strings handle human-readable text; booleans drive control flow with true or false. Arrays or lists store ordered values, dictionaries or maps store key-value pairs; Null or None means no value and is not the same as zero. Using the wrong type causes bugs or coercion surprises, so mastering types builds portable understanding across languages. You can view the original blog  post in Korean and English at the links below: [  View in Korean  ] | [  View in English  ] We need to tell apart iced Americano and hot cafe latte To a computer, we must give a clue about whether "100" is a number, a piece of text, a foreign word, or an alien symbol

The smartphone’s 40-year journey began with the 1983 Motorola DynaTAC, evolving from bulky “brick phones” into AI-powered personal devices. IBM Simon (1993) introduced the first real smartphone concept, while Nokia and BlackBerry shaped early mobile computing. Samsung’s 1995 “phone burning” event and the 1999 Anycall SCH-800 marked Korea’s rise as a global tech power, driven by a belief that “we can do it.” The 2007 iPhone revolutionized design and usability, while Samsung’s Galaxy series led Android innovation through the 2010s. Today’s iPhone 17 and Galaxy S26 integrate generative AI, transforming smartphones into digital extensions of human memory, creativity, and thought. You can view the original blog  post in Korean and English at the links below: [  View in Korean  ] | [  View in English  ] iPhone17 (apple newsroom) DynaTac 8000X By Redrum0486 - Own work, CC BY-SA 3.0 IBM Simon Personal Communicator By Bcos47(wikimedia) Mobile Phone Burning Ceremony (신...

Today is October 9 — Hangul Day . English is like stacking ready-made Lego blocks. Hangul is like building each Lego piece first , then putting it together.   1459년(세조 5년)에 간행된 《훈민정음언해》 Hangul is a logical and scientific writing system, but computers process it inefficiently because they only understand 0s and 1s. English fits in 1 byte per character, while Hangul needs 2–3 bytes due to its combinational consonant–vowel structure. This makes font design, rendering, and coding with Hangul more complex compared to English. The issue isn’t Hangul itself but the English-centered computer architecture and encoding standards. In the AI era, future developers could create “Hangul-friendly” systems — a true Digital Sejong Project where computers finally understand Hangul natively. You can view the original blog  post in Korean and English at the links below: [  View in Korean  ] | [  View in English  ]

(Published in   Electronics Magazine ,  April 19, 1965, pp. 114–117.) From left:   Andy Grove, Robert Noyce, and Gordon Moore. (Photo courtesy of the Gordon and Betty Moore Foundation.) Gordon Earle Moore (1929 – 2023) Gordon Moore, co-founder of Intel, predicted in 1965 that transistor counts on integrated circuits would double roughly every two years — later known as Moore’s Law. His insight became the guiding principle of the semiconductor industry, driving decades of exponential progress. From the Intel 4004 microprocessor with 2,300 transistors to today’s chips with tens of billions, his prediction shaped modern computing. Though physical limits now challenge miniaturization, innovators like Jensen Huang, Bill Gates, and Ray Kurzweil see Moore’s Law living on through AI, software, and system design. Moore’s Law ultimately symbolizes human imagination and the will to push beyond limits, not just transistor counts. You can view the original blog  post in Korea...

This post explores how different AI-generated images change dramatically depending on the phrasing of the prompt. Starting with “make an image of jjamppong,” the AI produced a simple noodle dish, then improved realism when “delicious” was added. Adding actions like “lifting noodles” or “showing steam” revealed that AI still struggles with motion and consistency. Introducing settings such as a “Chinese restaurant background” showed AI’s ability to express atmosphere as well as taste. The experiment proves that prompt engineering is the art of clear communication — AI creates not what you say, but what it understands. You can view the original blog  post in Korean and English at the links below: [  View in Korean  ] | [  View in English  ]

Prompt Engineering is the skill of crafting clear, structured instructions that help AI understand your intent. By defining context, role, goal, and constraints, you can guide AI to produce accurate and consistent results. It transforms AI from a simple answering tool into a reliable collaborator. As AI grows smarter, human questioning skills become even more essential. Ultimately, Prompt Engineering is emerging as a key communication skill in the AI era. You can view the original blog  post in Korean and English at the links below: [  View in Korean  ] | [  View in English  ]

photo by Worldspectrum on pixels 1. Bitcoin’s value is rooted in its technical design — a system sustained by electricity, probability, and computational effort rather than investment speculation. 2. Mining isn’t solving equations but randomly guessing a valid hash, an event so rare it happens roughly once every ten minutes thanks to massive global computing power. 3. Since mining consumes enormous energy, the Bitcoin network’s survival depends on electricity costs and sufficient financial incentives. 4. Its self-adjusting difficulty mechanism and halving schedule inherently create upward price pressure to maintain miner profitability. 5. Unless disrupted by breakthroughs like quantum computing or waning public trust, Bitcoin’s long-term trajectory remains structurally upward as a digital store of energy and time. You can view the original blog  post in Korean and English at the links below: [  View in Korean  ] | [  View in English  ]