🔸SKILL

Brief description of technology development direction

Mango-X is divided into a total of 6 types and is being developed, ultimately leading to Mango-X.

Product

Using a global-based language that takes into account high security, high processing speed, and UI,UX, it is developed by combining Mango-X's unique technology with a focus on matching the Mango-X ecosystem and having high interoperability between AI functions and products.

Services

Mango-X's Services are developed for the purpose of being friendly and highly compatible with the product, and especially during the development stage, they are built and developed with a focus on the service's own processing speed and data processing that does not conflict with other services.

Blockchain

Mango-X's service compatibility and function development that matches BSC's excellent compatibility and technical capabilities must be carried out independently and together. In particular, the Mango-X ecosystem is created as a transparent and equitable development for Web3 Dapp by designing the Binance-based MSC-X (Mango-X Smart Contract) suitable for the service ecosystem.

Bridge

Mango-X's Bridge aims to develop or use a Bridge that has methods and functions suited to each model efficiently. As the role of the bridge area, it will operate the role of an efficient bridge area in each area suitable for all model environments

AI

GPT-based or Mango-X's own AI Black Box continuously applies efficient technologies such as Deep Learning and Machine Learning to Mango-C's information and other information, such as user information and activities of Mango-X's ecosystem, and refined and classified information. The AI ​​Black Box, which is equipped with Deep Learning and Machine Learning, is advancing the AI ​​model and provides services to users with AI that is based on GPT suitable for the Mango-X ecosystem or advanced to Mango-X's own MPSTD-X (Proper service tracking detection) technology. assisting aims to Additionally, Mango-X's AI aims to perform the functions of RTLR (Real-time Learning and Reveling). Additionally, it can be further developed to provide medical services that check the user's current condition.

Mango-C

Mango-C is the core of Mango-X's big data service. In all data pre-processing processes, L1D (Layers 1 Date) management of Low Date, which is collection and input data, L2D (Layers 2 Date) through use and analysis within the ecosystem, data processing and optimization assumptions through AI and other processes. It is classified into classified ALD (AI Layers 2 Date), which is optimally classified through MPSTD-X and classified into data through data utilization commercialization, and is ultimately classified into MALD-X (Mango-X AI Layers Date).

🟠The current and future contents of this white paper are not definitive and may change depending on the development process (uncompleted development stage).

🟠If the content of the white paper is changed, it will take effect 30 days after the content of the changed white paper is announced after prior notice that the white paper may be changed.