Next Gem Ai aspires to be at the forefront of this revolution by introducing a new era in crypto data research and analysis: We are building a set of software and tools monitored by the best curated LLM artificial intelligence to access all Web3 project data directly on their pre-launch & launch stage and providing our community efficient ways to invest in the most promising crypto projects, on any existing blockchain.
Here's an overview of the token utility for $GEMAI token:
Premium Access:
Purpose: $GEMAI tokens are required to acquire premium access to select AI premium features, including the custom NextGem LLM.
Mechanism: Users need to spend $GEMAI tokens to unlock time-bound premium access to specific AI tools and services.
Token Burning Mechanism:
Purpose: Token burning is implemented as a deflationary measure.
Mechanism: Users burn a certain amount of $GEMAI tokens to gain access to premium services, reducing the overall token supply.
Deflationary Design:
Purpose: Encourage sustainable platform growth and align the token's value with the project's expansion.
Mechanism: The token supply is designed to decrease over time through burning, contributing to a deflationary model.
Transition to Locking Model:
Purpose: Address sustainability concerns by transitioning from a burning mechanism to a locking model.
Mechanism: At a certain stage where burning is no longer feasible, users must lock $GEMAI tokens for a specific period to access premium services, contributing to a new dynamic within the ecosystem.
Balancing User Benefits and Operational Efficiency:
Purpose: Ensure a balance between user engagement and operational efficiency.
Mechanism: The tokenomics are structured to provide superior value to users while promoting sustainable platform growth.
The $GEMAI token is positioned as a key element in incentivising community engagement, ensuring efficient operation of AI tools, and fostering a deflationary model that aligns with the project's growth.
All existing stored data from all crypto projects that we retrieve on the Internet is computed in the Next Gem MongoDB database, sent and processed by the most powerful AI models available on the market today; here is a non-exhaustive list of them: GPT4, GEMINI AI, MISTRAL AI, GROK AI.
We categorize projects using these models based on defined criteria, and rules trained and reviewed both by the
AI themselves and experts in the crypto investing industry. Each model evaluates the overall reliability of a project
and assigns a score to each one, utilizing a comprehensive data set. They are continually updated with all available
information we can gather from the project’s website, documentation, papers, and more.
Our LLM back-end processes are developed in C# language or Node.JS (Typescript). We interact with the APIs of each
AI company, sending them the extra data extracted from the scrapper (see section below): they are executed in a safe
environment in cloud instances. Some extra instructions are provided to give them specific tasks, knowing what they
have to do precisely: known as assistants, we use a relatively low LLM temperature to avoid creative outputs and ensure
the models do as taught & instructed.
The software process related to the AIs interaction waits for new projects to be sent to their execution state through
internal HTTP requests for specific requests demands or select the fresh one on our MongoDB database directly by
filtering projects not analyzed yet by each model we implement.
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