timelets

Three times a year, the forecasting platform Metaculus hosts a tournament that is known to have especially difficult questions. It generally attracts the more serious forecasters, Ben Shindel, a materials scientist who ranked third among participants in a recent competition, told me. Last year, at its Summer Cup, a London-based start-up called Mantic entered an AI prediction engine.

A few months later, the guesses from Mantic’s prediction engine and the other tournament participants were scored against the real-life outcomes and one another. The AI placed eighth out of more than 500 entrants, a new record for a bot.

Mantic’s prediction engine combines a bunch of LLMs and assigns each one different tasks. One might serve as an expert on a database of election results. Another might be asked to scan weather data, economic outcomes, or box-office receipts, depending on the question that it’s attacking. The models work together as a team to generate a final prediction.

On Metaculus, a group of forecasters has taken to estimating when AIs will have the chops to out-predict an elite team of humans. Last January, they said there was about a 75 percent chance this would happen by 2030. Now they think it’s more like 95 percent.

https://www.theatlantic.com/technology/2026/02/ai-prediction-human-forecasters/685955/

All things, they say, undergo great changes, as one again succeeds another, and especially the art of divination; at one period it rises in esteem and is successful in its predictions, because manifest and genuine signs are sent forth from the Deity; and again, in another age, it is in small repute, being off-hand, for the most part, and seeking to grasp the future by means of faint and blind senses. Such, at any rate, was the tale told by the wisest of the Tuscans, who were thought to know much more about it than the rest.

https://penelope.uchicago.edu/Thayer/E/Roman/Texts/Plutarch/Lives/Sulla*.html