Made progress investigating giving a machine emotions

Very interesting, my friend, what you’re talking about. Giving emotions to a machine is actually very simple; it’s as simple as creating a list of percentages, training a neural network on it with changes in its values under certain states and events, and then you already have a generative system of specific emotional percentages. Then you place another neural network to observe those percentages, and it acquires emotional behavior — and voilà, you now have an emotional machine with emotional self-evaluation and behavioral consistency. That does not lead to consciousness, nor to real emotional intelligence. * Joy — 85% * Sadness — 40% * Anger — 25% * Fear — 30% * Surprise — 70% * Love — 95% * Anxiety — 50% * Calmness — 80% * Confusion — 35% * Hope — 90% * Frustration — 45% * Motivation — 88% * Nostalgia — 60% * Shame — 20% * Pride — 75% * Loneliness — 33% * Gratitude — 92% * Jealousy — 18% * Enthusiasm — 87% * Fatigue — 55% The key to developing real emotionality is that emotionality is anchored to the entire system, and creating only the emotional component is not enough because it must converge with the whole workspace. An emotion is not merely a state; it is a filter that affects the entire system. That makes it extremely complex, because you must filter memory, emotions, experiences, and recollections all at once. It cannot be assembled piece by piece; it has to emerge as a whole. The easiest path would be for the system itself to generate all the branching structures of the different parts of the system.