Tag: human

Quantum is human-like

Posted on by lechuck park

With a Claude’s Help
This image illustrates a comparison between key quantum physics characteristics and human society, titled “Quantum likes humans.”

It presents three main quantum properties:

  1. Superposition
  • Quantum: 0 and 1 exist at the same time, with many (0|1) q-bits existing simultaneously
  • Human society parallel: Many people exist in mankind at the same time
  1. Entanglement
  • Quantum: All (0|1) q-bits are connected, even from a distance
  • Human society parallel: All people are connected
  1. Interference
  • Quantum: Can adjust overall probability through one q-bit
  • Human society parallel: One could influence the group (humans)

The image is structured with:

  • Left column: Quantum-related icons/symbols
  • Middle: Blue boxes with quantum physics concepts and their descriptions in gray boxes
  • Right: Green boxes showing human society analogies with simple stick figure illustrations

Each concept is visualized to make complex quantum principles more relatable by drawing parallels with human social dynamics.

This visualization effectively simplifies complex quantum mechanics concepts by relating them to familiar human social behaviors and relationships, making the concepts more accessible to a general audience.

The Era of True Artificial Intelligence: Bridging Human and Machine Learning  

Posted on by lechuck park

AI has now reached a level that can truly be called Artificial Intelligence. This is especially evident in the era of Machine Learning (ML). Humans learn through experiences—essentially data—and make judgments and take actions based on them. These actions are not always perfect or correct, but through continuous learning and experience, they strive for better outcomes, which inherently reflects a probabilistic and statistical perspective.

Similarly, ML learns from massive datasets to identify rules and minimize errors. However, it cannot achieve 100% perfection because it cannot learn all possible data, which is essentially infinite. Despite this, recent advancements in infrastructure and access to vast amounts of data have enabled AI to reach accuracy levels of 90% to 99.99%, appearing almost perfect.

Nevertheless, there still remains the elusive 0.00…1% of uncertainty, stemming from the fundamental limitation of incomplete data learning. Ultimately, AI is not so different from humans in how it learns and makes probabilistic decisions. For this reason, we can truly call it Artificial Intelligence.

WHY I LOVE A COMPUTER.

Posted on by lechuck park

Democracy and the constitution are like the fundamental principle of “1+1=10” in computer calculations. If these fundamentals are not respected, the results derived from immense computing power will ultimately be nothing more than illusions.

“1+1=10” 이어야 한다. 이 믿음이 사람들, 사회에서도 이루어지길 바란다.
물론 컴퓨터로 담아내지 못한, 또 담아낼 수도 없는 무언가 있다는 것은 잘알고 있다.
하지만, 알고 있는 것, 지켜야 하는 것, 지향해야 하는 것.. 그것은 확실히 지켜져야 한다.

정치라는 것의 아무런 관심도 없었고, 잘못된 정보로 인한 부끄러웠던 나의 과거가 존재한다. 하지만 1+1=10 이 아닌 현상을 너무 극명하게 느끼게 되면서.. 그 정치라는 것에 대해 관심을 가지게 되었다. 그리고 바랬다…누구에게나 공정한 “1+1=10” 세상이 되면 좋겠다고..
그리고 내가 그나마 알고 있는 컴퓨터 기술로 그 방향에 도움이 되면 좋겠다는 생각을 하게 된것 같다.

비트코인을 첨 알고 매력을 느꼈고. 지금은 WEB3 에 관심을 가질수 밖에 없는 이유이기도 하고.. 물론 사람의 욕심은 끝이 없고 무한할 것이다. 하지만 욕심은 문제가 아니다. 문제는 적어도 우리가 지켜온 “1+1=10” 이라는 지금까지 만들어온 기본인 Democracy 와 Constitution 은 지켜야 할 것 아닌가.. 그래야 발전을 꿈꾸고 그 위에서 사람의 욕심을 채워가야 하지 않을까 싶다.

number nice but limit

Posted on by lechuck park

This concept emphasizes the balance between numerical analysis and human intuition. Numbers are efficient tools for decision-making but have limitations, as they cannot solve everything. It highlights the importance of adhering to principles and goals when using data. Areas beyond numerical solutions allow for creativity and human values to drive progress, advocating for an integrated approach to decision-making.

Understanding and Predicting

Posted on by lechuck park

From Claude with some prompting
This image illustrates the human process of approaching truth through understanding and prediction. The key components are:

  1. Understanding: Represented by a lightbulb and a human icon, signifying the acquisition of basic knowledge.
  2. Predicting: Symbolized by a magnifying glass with a question mark, indicating the stage where understanding is used to make predictions.
  3. Truth: Depicted by a group of people and a “TRUTH” label, representing the ultimate goal.

These elements are connected sequentially, with prediction aiming to get “near to the Truth.”

The process is built on two foundational concepts:

  • Fundamental
  • Extension

These concepts interact through “New & Verification,” with the fundamental aspect encompassing “More Micro, More Macro, More Detail.”

Key Insights:

  1. Continuous Approach to Truth: Humans are constantly moving towards truth through understanding and prediction. This is a dynamic process, not a static one.
  2. Knowledge Expansion and Refinement: We expand our knowledge by exploring fundamental concepts more microscopically, macroscopically, and in greater detail. This represents growth in both depth and breadth of human knowledge.
  3. Limitations of Human Perception: The phrase “Just by Human observation & Words” at the bottom of the image highlights a fundamental limitation. We can only understand and express the world through our observations and language, not through direct access to matter itself.
  4. Role and Limitations of Numbers: While mathematical expressions can help overcome some linguistic limitations, they too face boundaries when confronting the infinite complexity of the microscopic and macroscopic worlds.
  5. Infinite Nature of Knowledge: As we learn more, we discover there is even more to learn. This paradox suggests an endless journey of discovery and understanding.
  6. Dynamic Process: The pursuit of knowledge is ongoing and ever-evolving, constantly expanding and becoming more refined.

In conclusion, this image portrays the continuous human quest for knowledge and truth, acknowledging our perceptual and expressive limitations while emphasizing our persistent efforts to expand and deepen our understanding of the world around us.

Everything is

Posted on by lechuck park

From Claude with some prompting
This diagram titled “Everything is” illustrates the process of human perception and understanding:

  1. “Input” represents all information received through human senses, depicted by a group of people icons and various symbols.
  2. This input connects to “EVERYTHING”, suggesting that we perceive the world through our senses.
  3. The note “Only Meaning Very very small” indicates that the initial meaning of information at the input stage is limited.
  4. The “More & More” box represents the expansion of human understanding through two methods:
    • “Logics”: Human thought processes
    • “Auto Logics”: AI or automated thinking processes
  5. “More Micro” and “More Macro” arrows show that this expanded thinking develops into more microscopic and macroscopic perspectives.

In essence, this diagram portrays how humans receive information through their senses and process it using both human logical thinking and automated thinking (like AI). This continuous process expands our understanding of the world, allowing us to comprehend “EVERYTHING” from increasingly detailed (micro) and broad (macro) viewpoints. The diagram illustrates our journey towards a deeper and wider understanding of everything around us.

AI vs Human

Posted on by lechuck park

From Claude with some prompting
Sure, here’s an explanation of the image in English, with a detailed description of the graph’s contents:

This image contrasts the capabilities of rule-based human logic and data-driven AI. The graph shows two curves:

  1. The blue curve represents rule-based human logic, which is stated to be “Always 100%” accurate. However, the curve flattens out, indicating that as data volume increases, human logic reaches its limits and analysis stagnates.
  2. The purple curve represents data-driven AI output, which starts at 0% accuracy but increases “dramatically based on more data” as computing power increases. The curve asymptotically approaches but never quite reaches 100%, with values like 99.99%, 99.999% mentioned.

The key points made are:

  • Rule-based human logic is 100% accurate but limited in its ability to process excessive data volumes.
  • Data-driven AI has lower initial accuracy but can approach near-perfect accuracy (99.99%+) by analyzing vast amounts of data powered by immense computing capabilities.
  • As more data and computing power become available, the effectiveness of data-driven AI surpasses the limits of human logic analysis.

So the image suggests that while human logic is perfect within its constraints, the future lies with data-driven AI systems that can harness massive data and computing resources to deliver extremely high accuracy, potentially exceeding human capabilities.