AI and LLM are proliferating and there are more and more advanced models with shocking capabilities.
We would like everbody to be able to use these models, but not everybody has the hardware.
Could we integrate AI with our existing blockchain ecosystems to possibly open up AI for more users?
## Motivation
Some models take an immense amount of resources to train.
However, _running_ the models also costs significant computational resources.
For example, even on a beefier machine with 8 GB of VRAM, LLaMa and Stable Diffusion seem to run at 1 token/sec for even the smallest model versions available.
What if we had an AIaaS (AI as a Service) system in a distributed, blockchain-based manner?
Users submit their prompts and the type of model they would like to run them on with some tokens as a reward and people with access to strong hardware can execute the models for them to win the reward.
The problem is of course, how does one know that the results they got from somebody else are indeed the results of running the models?
Also, when this communication takes place on the blockchain, both the prompt and the output will be public.
We propose using Zero Knowledge Proofs to show that the output of the model is indeed the result of running the model on the prompt and not
some random output. It also makes the gas lower, since the computation is not done on-chain. In the future, we could also use this to make the prompt and the output private.
2. Other users with strong hardware can fulfill these requests.
But instead of sending transactions with just the output, they also send a Zero Knowledge Proof that the output is indeed the result of running the model on the prompt.
The network would use a native token to reward the users who fulfill the requests, and the users who submit the requests would also have to pay in
this token. This way, the network can be self-sustaining.
