⭕Problems with Web2.0 LLM

The Web2.0 environment has presented a range of limitations and challenges, particularly in the realm of language learning models (LLMs). Here are some key issues associated with Web2.0 LLMs:

1. Monopolization of Knowledge Bases:

In the Web2.0 paradigm, large corporations tend to dominate and monopolize the knowledge bases that drive LLMs. This monopolization stifles innovation and competition, resulting in a lack of variety and choice for users. Furthermore, it creates significant barriers to entry for new companies, preventing them from bringing fresh ideas and improvements to the field.

2. Sacrificing Privacy for Interaction and Training:

Web2.0 LLMs often require users to give up a significant amount of their personal data and privacy for the sake of interaction and training. Users' interactions, conversations, and learning data are often collected, analyzed, and stored, raising serious privacy concerns. Despite these sacrifices, users often do not see a direct benefit or return from the data they provide.

3. Lack of Rewards for Training and Interaction:

In the current Web2.0 LLM landscape, users do not receive any rewards or incentives for their time and effort spent interacting and training with AI models. Despite the valuable data users generate and provide through their engagement, they are not compensated, making the process a one-way street favoring corporations.

In contrast, the AI Economy Community LLM in W3space is designed to address these issues by ensuring that knowledge is democratized, user privacy is respected, and that users are rewarded for their contributions. By leveraging the advantages of Web3.0, W3space aims to revolutionize the way AI avatars are used and developed.