The central challenge of modern machine learning lies in dealing with high-dimensional, complex, and noisy data. Classical approaches reduce this complexity by imposing linear or metric assumptions—for example, kernel methods, embeddings, or dimensionality reduction...

Introduction Ce texte constitue l’introduction d’un projet de livre en cours, dont les chapitres seront publiés progressivement.Plus d’informations : thepredictivepresent.com. Par Dan Herbatschek Par une matinée ordinaire, le futur se présente déjà sous forme de suggestions discrètes. Un...

On an ordinary morning, the future arrives in small, polite suggestions. A phone wakes before we do. It offers the weather as a confidence interval, traffic as a probability, the day’s meetings as blocks on...

Before clocks, before calendars, before numbers, there was the sky. Imagine a hunter in the Paleolithic dusk, crouched at the edge of a forest. The shadows are lengthening, the air cooling, and in his...