The project ingests a prompt that is presumed to be relevant to two pieces of embedded text or more. By way of example, I embedded a book by Nietzche and Jane Austen’s Pride & Prejudice as well as the prompt. Nearest neighbour search between the prompt embedding and each of the two embedded pieces of text was performed to generate a new vector embedding representing the three way relationship to be used to fine tune other LLM’s or the original model.

The new embedding is then stored as metadata on an NFT that by virtue of the being an ERC-6551 NFT has its own wallet. Having its own wallet means the NFT, which holds the embedding vectors representing the relationship between three pieces of text, is now able to autonomously transact itself in a hypothetical marketplace of AI text embeddings.

As they are stored as metadata on NFT’s, the embeddings may also be transacted by humans as valuable items for the refinement of personal LLM’s, thus combining a decentralized blockchain protocol, the ERC-6551 and LLM’s, within the context of an autonomous or voluntary marketplace.

In other words, it’s designed purpose is to improve LLM’s as cognitive tools for both humans and AI agents through an NFT marketplace of relationship bearing vector embeddings stored as metadata on token bound NFTs.