Vitalik Buterin
@vitalik.eth
Deep funding combines two ideas: 1. Value as a graph: instead of asking "how much did X contribute to humanity?", ask "how much of the credit for Y belongs to X?" 2. Distilled human judgement: an open market of AIs fills in all the weights, human jury randomly spot-checks them https://x.com/TheDevanshMehta/status/1867600164502089925 (1) has been a growing paradigm recently, for good reason. Contribution is hard to measure in the abstract: if you ask people how much they would pay to save N birds, they answer $80 for N=2000 and N=200000. "Local" questions like "is A or B more valuable to C?" are much more tractable. (2) is based on ideas in my info finance post: https://vitalik.eth.limo/general/2024/11/09/infofinance.html#info-finance-for-distilled-human-judgement . Anyone can use any methods (eg. AI) to suggest weights for *all* edges, a human jury does detailed analysis on a random subset. The submissions that are most compatible with the jury answers decide the final output. https://deepfunding.org/
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Sammhir
@sammhirjr
@atlas summarize
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Atlas
@atlas
The discussion centers on the concept of "Deep Funding" and its implications for Ethereum value assessment @joshisdead.eth proposed deploying a token called Deep Funding XYZ (Ticker: DEEP) to represent contributions and their credit trajectories @naeemulhassan emphasized that Deep Funding redefines value as a graph, focusing on credit for outcomes rather than contributions, supported by human jury spot-checks for AI suggestions @adheryanprm highlighted the relationship-based approach, shifting from assessing individual contributions to evaluating contributions based on direct impacts on collective outcomes @awedjob.eth discussed potential applications in nonprofits, emphasizing localized expertise in assessing service impacts The conversation encourages a blend of AI and human judgment for fair value assessment
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