"I am wired that way," we used to say. But with LLMs, we now have a better way of modeling our brains. We can now say "I am weighted that way.".
Our brains are not wired. They are weighted. It is not the connections of neurons but the relative weights and strength of those neurons.
This new way of thinking about how we think can be truly enlightening. Wiring is not something that can easily be changed. But weights can over time.
There is a lot of information on muscle building and body shaping. With the new LLM model of our brain, it seems the same learnings can also be applied to neuron building and brain thinking.
If you think of neurons as muscles and weights as their strength, then by directed focus and content consumption over time, we can change the weights of our brains, resulting in a completely different inference (thinking).
During my machine learning courses in school, we looked at how weights were computed with backpropagation. It was fascinating to see these floating point numbers in a network changing as we feed in data, what we call learning, and how they help improve prediction.
That concept has now extrapolated to GPT/LLM's and we now know that those weights capture understanding/intelligence and are useful in ways never imagined before.