Intelligence typically manifests at the edge of chaos – a dynamical state more characteristic of prefrontal networks than cerebellar microcircuits.

3. Emergence Mechanism Perspective:
From a statistical physics/emergence standpoint, the cerebellum exhibits insufficient symmetry breaking relative to the neocortex. Consequently, its representational capacity does not scale proportionally with neuronal count.

2. Information Processing Efficiency:
The density of information exchange between cerebellum and cerebral cortex is substantially lower than that between thalamus and cortex. The cerebellum primarily serves convergent integration functions and does not generate complex cognitive capabilities.

Thus, the cerebellum is not the core neuroarchitecture supporting higher cognition

In contrast, cerebellar architecture has been evolutionarily conserved for hundreds of millions of years across vertebrates.While nearly all higher animals possess a cerebellum, advanced cognition manifests predominantly in mammals – particularly primates.

1. Evolutionary Hierarchy:
Compared to the cerebellum, the cerebral/prefrontal cortex emerged later in both evolution and development. The prefrontal cortex (PFC) is a mammalian innovation, and its impairment often doesn't compromise survival. . .

Many researchers consequently regard embodied intelligence as the essential path to understanding cognition and intelligence. However, I find this perspective problematic for the following reasons

Proponents of embodied intelligence particularly endorse this view: Given that most human brain neurons are cerebellar (primarily involved in motor functions), artificial intelligence should "grow" physical sensors.

From over five professors specializing in brain-inspired computing/embodied intelligence, I have heard this statement: "The majority of neurons in the brain reside in the cerebellum, so neuroscience should more accurately be termed 'cerebellar science'."

May I add one more question：would this open to fourth year undergraduate？

Thanks for your excellent job！I wonder whether PySR use a GP based sketch or a transformer based sketch.

excellent！like a white bridge across the river！

if you mean extracting watershed features for observations and train a model based on that, I guess I am?

Thanks for sharing！I would also recommend vmls written by Boyd