btrmt. | Betterment

You’ve heard of quantum entanglement, probably. Two particles linked in some strange way, regardless of the distance between them. But I’d never heard that this could happen through time too:

The data revealed the existence of quantum correlations between ‘temporally nonlocal’ photons 1 and 4. That is, entanglement can occur across two quantum systems that never coexisted.

Honestly, I understand very little of this. It doesn’t make me very confident about the Instagram videos I’ve idly scrolled through. But it does highlight just how limited the human perspective is. See also The colour of the inhuman world.

Sometimes it’s not parsimony, but complexity that we’re looking for:

The preference for simple explanations, known as the parsimony principle, has long guided the development of scientific theories, hypotheses, and models. Yet recent years have seen a number of successes in employing highly complex models for scientific inquiry (e.g., for 3D protein folding or climate forecasting). In this paper, we reexamine the parsimony principle in light of these scientific and technological advancements. We review recent developments, including the surprising benefits of modeling with more parameters than data, the increasing appreciation of the context-sensitivity of data and misspecification of scientific models, and the development of new modeling tools. By integrating these insights, we reassess the utility of parsimony as a proxy for desirable model traits, such as predictive accuracy, interpretability, effectiveness in guiding new research, and resource efficiency. We conclude that more complex models are sometimes essential for scientific progress, and discuss the ways in which parsimony and complexity can play complementary roles in scientific modeling practice.