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Teach AI

Teach AI

The application helps to curate high-quality datasets by providing a framework to incentivize RLHF, with the LLM being fully verifiable and hosted on-chain.
Hackathon ProjectAI/ML

Team

Denver Baumgartner
denverb#0
Kirill Igumenshchev
kirilligum#0
Julio Cruz
juliomcruz#0

Languages, Libraries & Stacks

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About Teach AI

The application allows the the user to submit instructions and queries to an AI chat interface, the smart contract acts as a middle-man between the user and hosted (centralized unsecured or Cartesi) LLM. The user can rate two responses to their prompt, creating an incentivized system to curate high-quality RLHF data. The user pays a query fee for the initial prompt and receives a rebate for providing feedback on the responses. All data is tracked on-chain, indexed by The Graph, and with the ability to offer state checks of the model through Cartesi. As the model is tuned, datasets used for tuning can be uploaded to IPFS, and verified by The Graph, and checkpoints from Cartesi can be recorded in the smart contract, providing a fully transparent lineage of LLM evolution.

How it's Made

The application was developed using the Scaffold ETH and WAGMI libraries for blockchain functionality. Additionally, we employed The Graph and Cartesi libraries. For the front-end technology, we utilized React JS along with Biconomy and Worldcoin. The application allows the user to recharge their account using fiat.

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Anyone is free to submit information about their project. Do your own research and use your best judgment when using or interacting with any of the projects listed in this directory. Being listed in this directory is not an endorsement from the Cartesi Foundation or any other related entity.

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