GradientCoin: A Peer-to-Peer Decentralized Large Language Models
Yeqi Gao Zhao Song Junze Yin
Since 2008, after the proposal of a Bitcoin electronic cash system, Bitcoin
has fundamentally changed the economic system over the last decade. Since 2022,
large language models (LLMs) such as GPT have outperformed humans in many
real-life tasks. However, these large language models have several practical
issues. For example, the model is centralized and controlled by a specific
unit. One weakness is that if that unit decides to shut down the model, it
cannot be used anymore. The second weakness is the lack of guaranteed
discrepancy behind this model, as certain dishonest units may design their own
models and feed them unhealthy training data.
  In this work, we propose a purely theoretical design of a decentralized LLM
that operates similarly to a Bitcoin cash system. However, implementing such a
system might encounter various practical difficulties. Furthermore, this new
system is unlikely to perform better than the standard Bitcoin system in
economics. Therefore, the motivation for designing such a system is limited. It
is likely that only two types of people would be interested in setting up a
practical system for it:
  $\bullet$ Those who prefer to use a decentralized ChatGPT-like software.
  $\bullet$ Those who believe that the purpose of carbon-based life is to
create silicon-based life, such as Optimus Prime in Transformers.
  The reason the second type of people may be interested is that it is possible
that one day an AI system like this will awaken and become the next level of
intelligence on this planet.