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Slower paths means loops here for humans where the output of a neuron gets feed back into itself. The fastest path = a feed forward neural network without loops.

LLM’s operate strictly feed forward neural networks.

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Your assumption is wrong. Unlike artificial neurons, real neurons process massively and concurrently, let’s say 10-20 thousand inputs at once in less than 1 millisecond. In Kahnemans theory system 2 always involves the anterior cingulate cortex and arises when there are multiple conflicting streams of information. That’s the defining characteristic. Both system 1 and system two process in the same way, including looping back to previous areas. So really, no, stopping an LLM early vs letting it run has nothing to do with Kahnemans theory. In general LLMs are so far removed from what we consider natural cognition that it’s very hard to apply neuroscience concepts to LLMs simply because they share no real world similarity. At best, you’re simulating something in a very inefficient way.

We’re talking about biological processes which have physical limitations on how frequently a neuron can fire as well as a signaling system that based on how rapidly neurons fire. Loops anywhere in the system enforce a minimum 5ms latency and more realistically several times that. A typical neuron is firing closer to 0.1 to 2 times a second. Add to that the physical transmission speed and rapid response doesn’t allow for loops.

There’s a reason reflexes for the feet are handled by the spine that’s got nothing to do with total processing power.

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