It probably can, but how will those algorithms be created? And the representation of both input and output. If it’s text, the most efficient way is to construct a formal system. Or a statistical model if ambiguous and incorrect result are ok in the grand scheme of things.

The issue is always inout consumption, and output correctness. In a CPU, we take great care with data representation and protocol definition, then we do formal verification on the algorithms, and we can be pretty sure that the output are correct. So the issue is that the internal model (for a given task) of LLMs are not consistent enough and the referential window (keeping track of each item in the system) is always too small.

Neural networks can be evolved to do all sorts of algorithms. For example, controlling an inverted pendulum so that it stays balanced.

> In a CPU, we take great care with data representation and protocol definition, then we do formal verification on the algorithms, and we can be pretty sure that the output are correct.

Sure, intelligent design makes for a better design in many ways.

That doesn't mean that an evolved design doesn't work at all, right?