It's a lot more complicated than that.

You have instincts, right? Innate fears? This is definitely something passed down through genetics. The Hawk/Goose Effect isn't just limited to baby chickens. Certainly some mental encoding passes down through genetics as how much the brain controls, down to your breathing and heartbeat.

But instinct is basic. It's something humans are even able to override. It's a first order approximation. Inaccurate to do meaningfully complex things, but sufficient to keep you alive. Maybe we don't want to call the instinct a world model (it certainly is naïve) but can't be discounted either.

In human development, yeah, the lion's share of it happens post birth. Human babies don't even show typical signs of consciousness, even really till the age of 2. There's many different categories of "awareness" and these certainly grow over time. But the big thing that makes humans so intelligent is that we continue to grow and learn through our whole lifetimes. And we can pass that information along without genetics and have very advanced tools to do this.

It is a combination of nature and nurture. But do note that this happens differently in different animals. It's wonderfully complex. LLMs are quite incredible but so too are many other non-thinking machines. I don't think we should throw them out, but we never needed to make the jump to intelligence. Certainly not so quickly. I mean what did Carl Sagan say?

One of the biggest mysteries of humans Vs LLMs is that LLMs need an absurd amount of data during pre training, then a little bit of data during fine tuning to make them behave more human. Meanwhile humans don't need any data at all, but have the blind spot that they can only know and learn about what they have observed. This raises two questions. What is the loss function of the supervised learning algorithm equivalent? Supposedly neurons do predictive coding. They predict what their neighbours are doing. That includes input only neurons like touch, pain, vision, sound, taste, etc. The observations never contain actions. E.g. you can look at another human, but that will never teach you how to walk because your legs are different from other people's legs.

How do humans avoid starving to death? How do they avoid leaving no children? How do they avoid eating food that will kill them?

These things require a complicated chain of actions. You need to find food, a partner and you need to spit out poison.

This means you need a reinforcement learning analogue, but what is going to be the reward function equivalent? The reward function can't be created by the brain, because it would be circular. It would be like giving yourself a high, without even needing drugs. Hence, the reward signal must remain inside the body but outside the brain, where the brain can't hack it.

The first and most important reward is to perform reproduction. If food and partners are abundant, the ones that don't reproduce simply die out. This means that reward functions that don't reward reproduction disappear.

Reproduction is costly in terms of energy. Do it too many times and you need to recover and eat. Hunger evolved as a result of the brain needing to know about the energy state of the body. It overrides reproductive instincts.

Now let's say you have a poisonous plant that gives you diarrhea, but you are hungry. What stops you from eating it? Pain evolves as a response to a damaged body. Harmful activities signal themselves in the form of pain to the brain. Pain overrides hunger. However, what if the plant is so deadly that it will kill you? The pain sensors wouldn't be fast enough. You need to sense the poison before it enters your body. So the tongue evolves taste and cyanide starts tasting bitter.

Notice something? The feelings only exist internally inside the human body, but they are all coupled with continued survival in one way or another. There is no such thing for robots or LLMs. They won't accidentally evolve a complex reward function like that.