This comparison outlines how AI Internet-Meritocracy (AIIM) differs from traditional grant funding. Unlike conventional systems that rely on peer review committees and formal credentials, AIIM distributes funding algorithmically based on merit signals. The table below highlights structural differences in eligibility, funding logic, and support for science marketing.
| AIIM | Gitcoin | Giveth | Manifund | |
| Funded | science and free software | mainly, Ethereum | public and private goods | a picked-up set of public goods |
| Pays in | several cryptocurrencies | several cryptocurrencies | several cryptocurrencies | FIAT money |
| Distribution | AI | mainly, quadratic funding | mostly direct, some quadratic funding | direct and regranting |
| Grant writing | without | required | required | required |
| Small projects support | yes | bad | bad | bad |
| Fairness of distribution between projects | maximal | low | average | low |
| Wait for payout | ~week | months | immediately | weeks |
👉 Help fund the next public test of AIIM.
Help Test a New Way to Fund Science
AI Internet-Meritocracy (AIIM) is an operational beta designed to allocate available donations to researchers and open-source developers using AI-assisted evaluation of documented contributions. Payment transactions are already recorded on-chain.
The next major evidence milestone is a proposed five-month public adversarial test of the allocation model, with $1,000 distributed to eligible funding recipients. Donations help pay for the development, infrastructure, reviewer and participant recruitment, outreach, and operating work needed to reach and evaluate that milestone.
You do not need to assume AIIM is already proven to support the project. Your donation helps turn the proposal into evidence: what works, what fails, and what should change.
Support the next testing milestone → Read the test proposal →
Independent review
Researchers and technical reviewers: independent criticism is welcome, including negative conclusions. Review AIIM’s assumptions, governance, failure modes, and testing plan →
Research status: AIIM remains experimental. AI-generated evaluations can contain factual errors or biases, and decentralized governance and non-custodial components remain under development. That uncertainty is why public testing, auditability, and external criticism are central to the project.