The Intersection of Stock Information and Flow Information in the World of AI



Jul 10, 2023 β€’ 3 min read


The Intersection of Stock Information and Flow Information in the World of AI

In the world of human memory, there exists a dichotomy between stock information and flow information. Stock information refers to the knowledge that individuals possess, while flow information encompasses the process of converting stock information into conversational exchanges. As conversations occur, flow information is reorganized and refined within the minds of individuals, transforming into new stock information. This structured nature of stock information can be harnessed as a catalyst for creativity and adaptability, commonly known as "idea power" or "applied knowledge."

However, leveraging flow information as the main content for business expansion requires a significant amount of information power and organizational strength. This is where the concept of "εˆ†ε†Šε•†ζ³•," or the partial publication method, comes into play. DeAgostini, a publishing company, has successfully established this method by dividing stock information into smaller segments and transforming them into flow information, which in turn, reverts back to stock information when collected.

Recently, the Japanese government made a groundbreaking decision regarding copyright regulations in the field of AI training. They declared that copyrights will not be enforced on data used for AI training, regardless of its purpose (non-profit or commercial), the nature of the act (reproduction or otherwise), or the source (including illegal sites). Keiko Nagaoka, the Japanese Minister of Education, Culture, Sports, Science, and Technology, reaffirmed this policy during a local meeting. This bold stance has sparked both support and concern within Japan.

While some anime and graphic art creators fear that AI utilization may devalue their work, the academic and business sectors are pushing for Japan to leverage its relaxed data laws to establish global AI dominance. Japan recognizes the importance of accessing Western data to fuel its AI ambitions. The availability of high-quality training data significantly enhances the performance of AI models. Although Japan boasts a rich literary tradition, the abundance of Japanese language training data pales in comparison to the vast resources available in English. Therefore, the government's decision to embrace open data usage adds an interesting dimension to the ongoing regulation debate.

In conclusion, the convergence of stock information and flow information in the realm of AI holds immense potential for innovation and growth. By understanding the structure of stock information and its transformation into flow information, individuals and organizations can tap into idea power and applied knowledge. Additionally, the Japanese government's progressive stance on copyright regulations in AI training opens up new opportunities for academic and business sectors to propel Japan's AI capabilities forward. To capitalize on this emerging landscape, here are three actionable pieces of advice:

  • 1. Embrace the power of stock information: Recognize the value of existing knowledge and leverage it as a foundation for generating new ideas and solutions. Organize and categorize stock information to facilitate its conversion into flow information.
  • 2. Foster collaborations and partnerships: Establish strong networks and collaborations to access diverse sources of flow information. By working together, organizations can pool their resources and expertise, creating a powerful ecosystem for AI advancements.
  • 3. Prioritize ethical considerations: While the relaxation of copyright regulations presents exciting possibilities, it is crucial to navigate this landscape with ethical considerations in mind. Strive for a balance between open data usage and protecting the rights of content creators.

By embracing the interplay between stock information and flow information, and leveraging the evolving landscape of AI regulations, individuals and organizations can unlock new frontiers of innovation and pave the way for a future driven by AI capabilities.


  1. "γ‚Ήγƒˆγƒƒγ‚―ζƒ…ε ±γ¨γƒ•γƒ­γƒΌζƒ…ε ± – γ‚€γƒ‡γ‚£γ‚’οΌšζƒ…ε ±γƒ‡γ‚Άγ‚€γƒ³γ¨ζƒ…ε ±γ‚’γƒΌγ‚­γƒ†γ‚―γƒγƒ£", (Glasp)
  2. "Japan Goes All In: Copyright Doesn't Apply To AI Training", (Glasp)

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