Tag: 100%

Data Life

Posted on by lechuck park

From ChatGPT with some prompting
reflecting the roles of human research and AI/machine learning in the data process:

Diagram Explanation :

  1. World:
    • Data is collected from the real world. This could be information from the web, sensor data, or other sources.
  2. Raw Data:
    • The collected data is in its raw, unprocessed form. It is prepared for analysis and processing.
  3. Analysis:
    • The data is analyzed to extract important information and patterns. During this process, rules are created.
  4. Rules Creation:
    • This step is driven by human research.
    • The human research process aims for logical and 100% accurate rules.
    • These rules are critical for processing and analyzing data with complete accuracy. For example, creating clear criteria for classifying or making decisions based on the data.
  5. New Data Generation:
    • New data is generated during the analysis process, which can be used for further analysis or to update existing rules.
  6. Machine Learning:
    • In this phase, AI models (rules) are trained using the data.
    • AI/machine learning goes beyond human-defined rules by utilizing vast amounts of data through computing power to achieve over 99% accuracy in predictions.
    • This process relies heavily on computational resources and energy, using probabilistic models to derive results from the data.
    • For instance, AI can identify whether an image contains a cat or a dog with over 99% accuracy based on the data it has learned from.

Overall Flow Summary :

  • Human research establishes logical rules that are 100% accurate, and these rules are essential for precise data processing and analysis.
  • AI/machine learning complements these rules by leveraging massive amounts of data and computing power to find high-probability results. This is done through probabilistic models that continuously improve and refine predictions over time.
  • Together, these two approaches enhance the effectiveness and accuracy of data processing and prediction.

This diagram effectively illustrates how human logical research and AI-driven data learning work together in the data processing lifecycle.

Anyway, The probability

Posted on by lechuck park

From Claude with some prompting
Traditional View: AI’s probability-based decisions are seen in contrast to human’s logical, “100% certain” decisions, and this difference could be perceived as problematic.

New Insight: In reality, the concept of human’s “100% certainty” itself might be an illusion. Human judgments are also based on limited data and experiences, making them inherently probabilistic in nature.

Finding Common Ground: Both humans and AI make decisions based on incomplete information. Even human’s logical certainty ultimately stems from restricted data, making it fundamentally probability-based.

Paradigm Shift: This perspective suggests that AI’s probabilistic approach isn’t a flaw but rather a more accurate modeling of human decision-making processes. What we believe to be “100% certainty” is actually a high-probability estimation based on limited information.

Implications: This prompts a reevaluation of the perceived gap between AI and human decision-making styles. AI’s probabilistic approach might not be inferior to human logic; instead, it may more accurately reflect our cognitive processes.

This viewpoint encourages us to see AI’s probabilistic tendencies not as a problem, but as a tool providing deeper insights into human thought processes. It invites us to reconsider how AI and humans collaborate, opening new possibilities to complementarily leverage the strengths of both sides.

The image and your interpretation together challenge the notion that human reasoning is purely logical and certain. Instead, they suggest that both human and AI decisions are fundamentally based on probabilities derived from limited data. This realization can foster a more harmonious and effective partnership between humans and AI, recognizing that our decision-making processes may be more similar than previously thought.