Driving rewards to open source dependencies with a market of AIs as the engine and humans as the steering wheel, deep funding requires 3 components:

A data layer mapping all contributions to an ecosystem
An open contest to crowdsource the relative value between contributions
A jury to express preferences on a randomly selected set of contributions

The model(s) best aligning with jury spot checks distribute funds across the dependency graph, thus scaling high quality human judgement

In most funding rounds, selection procedures require a committee or donors to have an opinion on all eligible projects.

In deep funding, the jury votes carefully on a few projects. These selections serve as test data to choose a winning model that decides allocations to all projects, using a data science competition approach (like the ones on Kaggle or Pond) where anyone can submit models giving weights to projects in a round.

Pilot Implementations

Deep Funding kicked off with a competition using funding data from 2019-2024 from Open Collective, Gitcoin, Optimism and Octant. Participants needed to build open source AI or metrics based models to predict funding received by projects in these past rounds.

You can see our proof of work here - 15 high quality submissions from participants that are being judged for $20k in prizes!

What's Next

The next contest asks participants to submit machine learning or metrics based model that gives 15,000 weights indicating the contribution of ~5000 open source repos to the ethereum universe

The model that best aligns with juror rankings for a subset of these dependencies gets to allocate $170,000 based on their weights

Simultaneously, we are spreading the meme of predictive funding challenges where models guess the amount received by a project before the round even starts. Proof of Work: https://gov.gitcoin.co/t/gcp-xxx-predictive-funding-competition-for-gg23/19902/6

Your support will help the 6 partners involved in Deep Funding;

VoiceDeck as StoryTeller Open Source Observer as Wizard Pairwise as Referee

Drips as Sprinkler Pollen Labs as Accelerator Allo as Weaver