change

Everything flows and nothing abides; everything gives way and nothing stays fixed. – Heraclitus

Things change.

Without change, there would be no difference between states. Without difference, nothing meaningfully exists. Time itself is just another word for difference - each moment is distinct from the last.

When things change, some persist and others don’t.

A rock endures through many states; a soap bubble vanishes. This persistence creates what Bennett calls the “cosmic ought” - the universe inherently selects for self-preserving structures. This foundational normativity cascades upward through all levels of organization.

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The “Paradox” of change

Living systems face a paradox: If they try to remain the same, they will disappear / die when the environment changes / their parts become mutated. But if you do change / evolve / adapt, the old is in some sense gone.
Biology commits to persistence not by remaining unchanged, but by constant adaptation and change to novel circumstances

Dalle vs Baby: Moving vs. Static World

A baby couldn’t learn from being shown 600 million static, utterly disconnected images in a dark room (and remember most of them!). Our statistical models way surpass the brain in that respect.
For us, information stays the same, but gets transmogrified over time, so we only need to learn the transmogrification. We mostly need to learn change.

→ Learning in a moving, dynamic environment is much easier, as it imposes constraints on the world (world model).
Cats, for example, can track moving objects much better than static objects.

In moving vs static, the semantics of features change:
Static: Scene is composed of features / objects, which are in a static relationship, based on which you need to interpret the scene (ambiguous, hard, …). The features are classifiers of the scene.
Dynamic: Features become change operators, tracking the transformation of a scene. They tell you how your world-model needs to change. To process that, you need controllers at different hierarchical, spatial and temporal levels, which can turn on/off/change at the level of the scene. → Features become self-organizing, self-stabilizing entities, that shift themselves around to communicate with other features in the organism, until they negotiate a valid interpretation of reality.

A similar thing happens also in the spatial domain (i.e. in biological development as opposed to neuroscience, which usually deals with the temporal domain): The delta of voltage gradients modifies the controllers for cells (gene expressions etc.).

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If you want something to change, you have to do it yourself.