AIS Node Phases

Alpha Node Nodes are focused on data acquisition, which is the first step of building a robust and diverse AI language model. Nodes use crawler bots to collect text data from various sources, such as websites, social media platforms, forums, blogs, etc. Nodes also label the data according to categories, such as topics, sentiments, intents, entities, etc. This helps to create a rich and structured dataset that can be used for AI learning in the next phase. Beta Node

Nodes use distributed computing to process the acquired data into AI learning using state-of-the-art natural language processing techniques, such as transformers, attention mechanisms, self-attention, etc. Nodes also use reinforcement learning to optimize the AI language model based on feedback and rewards from the users and the system. This helps to improve the accuracy and performance of the AI language model in various tasks and scenarios.

Full Node

Nodes have all the capabilities of the previous nodes, and can access the processed and stored data to make inferences, which is the process of generating new text based on input and context. Nodes can understand new data with the ability to identify and categorize it according to different criteria, such as relevance, quality, sentiment, etc. AI NPCs provide service not only in AI Society Metaverse but can be suited to different metaverses, GameFi, and dApps.