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.

  > Meanwhile humans don't need any data at all

1) Certainly the data I discussed exists. No creature comes out a blank slate. I'll be bold enough to say that this is true even for viruses, even if we don't consider them alive. Automata doesn't mean void of data and I'm not sure why you'd ascribe this to life or humans.

2) humans are processing data from birth (technically before too but that's not necessary for this conversation and I think we all know that's a great way to have an argument and not address our current conversation). This is clearly some active/online/continual/ reinforcement/wherever-word-you-want-to-use learning.

It's weird to suggest an either or situation. All evidence points to "both". Looking at different animals even see both but also with different distributions.

I think it's easy to over simplify the problem and the average conversation tends to do this. It's clearly a complex with many variables at play. We can't approximate with any reasonable accuracy by ignoring or holding them constant. They're coupled.

  > 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

Just because there are externally driven or influenced goals doesn't mean internal ones can't exist. Our emotions can be driven both externally and internally.

  > Notice something?