To discuss Donymony, we first need to understand the global search engine market and the e-commerce market. The primary tradable goods in e-commerce are physical items, mostly at the retail level. For buying and selling bonds or stocks, there is no direct connection to e-commerce; instead, financial software like HTS (Home Trading System) is used.

The global e-commerce revenue reached $2.6996 trillion in 2021, and it is projected to experience a rapid surge, reaching $3.2453 trillion by 2025. When we consider worldwide stock trading volume, the global market capitalization reached $103 trillion in June 2021.

As of April 2022, the KOSPI market capitalization stands at 2091 trillion won, with a daily trading volume of 10 trillion won. The KOSDAQ stands at 399 trillion won with 7 trillion won daily. Assuming 250 trading days per year, the annual trading volume reaches 4250 trillion won — implying trading approximately $206 trillion worth of stocks annually.

Google dominates the global search engine market with a staggering 91.54% worldwide share as of 2020. Even when combined, Bing, Yahoo, and Baidu account for just over 5%. Since its launch in 1998, Google implemented 3,243 algorithm updates in 2018 alone, continuously refining its search quality.

However, the primary concern for most people is money and an unstable, unpredictable future. This is where Donymony enters — a search engine business focused exclusively on searches related to money. The name "Donymony" is derived from the Korean phrase meaning "What is money?"

Moreover, Donymony combines search with e-commerce. It not only displays items related to searched keywords but also evaluates their future value — calculating whether an investment will rise or fall. In essence, Donymony is a search site where commerce and predictive search capabilities intersect.

Some people aim to implement AI politics by using the law as the basis and means, interpreting legal content through AI systems. However, the series of events carried out in PERT·CPM inherently include legal elements, so there is no need to separately interpret the law.

The question is whether to use the law as a means of AI politics, or to use PERT·CPM + NNAIS, which discusses actions within events themselves. Which is more advanced and efficient — the law, or PERT·CPM + NNAIS?

Using probabilistic and statistical methods, the four main areas of PERT — time, cost, personnel, and resources — are categorized. The sequence and direction are determined through infinite generation PERT·CPM (A.I WORK). Feedback is provided through NNAIS (A.I and HUMAN WORK).

Utilizing generative AI for PERT*CPM + NNAIS in politics. Infinite planning and scheduling through PERT*CPM, with feedback mechanisms from NNAIS to verify.

LLM2+ means the combination of LLM.1 (large language model) and LLM.2 (large logic model). A country with the third largest territory and population, based on the United States, can govern and control the world smoothly and strongly without additional costs through AI politics using PERT·CPM + NNAIS, supported by a military force of 500,000–1,000,000 civil servants and 1,000,000–2,000,000 soldiers.

A country with the third largest territory and the third largest population in the world, based on the United States, can govern and control the whole world smoothly and strongly without additional costs through AI politics using PERT*CPM + NNAIS (feedback on quality, process, safety, cost, design, specifications, etc.), supported by a military force consisting of 500,000 to 1,000,000 civil servants and 1,000,000 to 2,000,000 soldiers specially.