No Free Lunch: The Impossibility of a Universal Learner
There is no algorithm that is best at everything. Averaged over all possible problems, every learner performs exactly alike, and...
Year: 2026
The Curse of Dimensionality
Add dimensions and intuition betrays you. Volumes explode, neighbors flee, and the comfortable geometry of ordinary space gives way to...
The Manifold Hypothesis: Why Data Lives on a Lower Dimension
High-dimensional data is rarely as vast as it looks. Images, sounds, and language occupy only a thin sliver of all...
Regularization as a Statement of Belief
To regularize a model is to lean on it, gently, in a chosen direction. The technique looks like arithmetic but...
The Bias-Variance Tension at the Heart of Fitting
Every model that fits data faces a pull in two directions. Too rigid, and it misses the signal; too flexible,...
Inductive Bias: The Prior That Makes Learning Possible
No learner learns from data alone. Before the first example arrives, a system must already prefer some explanations over others,...
Generalization and the Difference Between Learning and Memorizing
To learn is to go beyond what one has seen. A system that merely records its examples has memorized; a...
The Measure of Aging and the Prospect of Its Reversal
Aging has long been treated as destiny; it is increasingly treated as a variable. If the passage of biological time...
Complexity, Tipping Points, and the Fragility of Large Systems
Large systems fail not gradually but suddenly. Whether in climate, ecology, or economy, the same lesson recurs: a system may...
The Genome as Language, and the Limits of the Metaphor
To call the genome a text is irresistible and misleading in equal measure. The metaphor of code, letters, and grammar...
