When a model speaks for a population
Language models answering as real people, scored once on survey answers nobody had read: a frontier model met 0 of 6, prompted voices overstated births threefold, and carrying the last shares forward beat a small model. Lives fitted to records came closer, a model's estimate counted as a prior meant fewer people to ask, and subgroup splits landed inside the survey's own noise in the United States and in 30 of 31 African countries.
Twenty years ahead: forecasting how long people live, on years nobody had read
Living Worlds' life expectancy forecasts, frozen twenty years back and scored once on years no run had seen: met for women and for men on the latest national figures, not met against 2024 national figures or across 155 countries, with honest intervals for women and a stacked UN model that did not help.
Synthetic populations: where simulated people hold up, and where they fail
Census-built populations, agents grounded in interviews and language models speaking for whole groups have all advanced in 2025-26. The evidence now shows clearly which of them match real people, and the dividing line is what each simulated person is built from.
Families from lived records: children and siblings, counted before the answers were read
A population lived month by month in the United States from 1950 matched how many children Americans have had and how many brothers and sisters they report, closer than a frontier model answering from what it has read. The father's side, first counted through partnerships, missed, and became the next test.
A billion lives on one GPU, and what only shows at scale
Living Worlds runs more than a billion life-months a second on one desktop GPU and on one desktop processor, with every birth, death, partnership and separation identical across engines; a million-life world that anyone can replay; and an effect of who is born that appears only when lives have to find each other.