Custom scenario builder
For questions the curated examples do not cover.
Editable scenarios for asking what AI revenue, copied libraries, data deals, and training-data mixes might cost, fund, or imply.
Each scenario opens progressively, starting with the summary result and revealing the shared assumptions and exact formula on request.
For questions the curated examples do not cover.
How much would it cost to pay for a brand new LLM-scale pre-training dataset (say, ) assuming moderate freelance writing wages (say, )?
What would it cost to compensate an entire copied library (say, ) at a settlement-style rate per work (say, )?
If we distribute the payments from recent data deal (say, ) to some group of people (say, ), how much will each person get?
How many expert-eval questions could one data deal (say, ) fund at current expert rates (say, )?
If feeling comfortable with medical AI meant asking some share of the world's physicians (say, ) out of a global pool of roughly to each spend about on audits, review, and oversight, what annual labor budget would that imply at current physician wages (say, )?
How much would it cost to fund a domain-specific eval effort using a panel of physicians (say, ) for some review time each (say, ) at current physician wages (say, )?
How much would it cost to pay for an eval dataset (say, ) assuming a per-question expert benchmark (say, )?
How many absolute tokens would a books, code, or social share (say, ) represent at frontier scale (say, )?
If we distribute AI revenue (say, ) to some group of people (say, ), how much will each person get?
This site is still evolving. It is built to make AI training-data and distribution debates easier to inspect with shared inputs and simple, editable math.
The resources page keeps our essays and external references in one place, and the GitHub repository is where ongoing updates live.