kaal:claim:4855607-001

Web3 community governance built on Weighted Directed Acyclic Graphs, validation pools with reputation staking, and a federated communications protocol provides an evolutionary approach to optimizing AI models rather than a static compliance layer over them.

Source quote, verbatim

The integration of web3 community governance, using Weighted Directed Acyclic Graphs (WDAGs) and validation pools with reputation staking in combination with a federated communications protocol, offers an evolutionary approach to AI model optimization.

From

Wulf A. Kaal, How AI Models are Optimized Through Web3 Governance (2024), Abstract, p. 1
https://ssrn.com/abstract=4855607 · source PDF

Cite as

Wulf A. Kaal, How AI Models are Optimized Through Web3 Governance (2024). SSRN: https://ssrn.com/abstract=4855607

Holds when

applies to the six AI model families the author examines: deep learning, federated learning, transformer, GNN, RL, and RLHF

Classification

designsupport: arguedgovernance-designai-and-agentsreputation

Related claims

extended_by kaal:claim:4957318-031 Validation pools are the consensus mechanism of the proposed system: author stakes are pooled to evaluate spec...

Verify

The quote above is an exact substring of the source PDF, whose sha256 is eb0b3e62374b45a8fa888c6bde9725e606bcb46cf4b5e74a6e851d9f25099113. Extraction method: pdf-text-layer.
Attestation record: colloquium/attestations/635665da90cf506f...json
Verify the binding yourself: curl -s https://wulfkaal.github.io/claims/4855607-001.md | sha256sum