If you simulate a neural network, there is no need to know, how it really works.
That is NOT a good thing. If we ever want to actually get any sort of efficient AGI, we need to figure out how intelligence actually works. The vast majority of current AGI attempts are based upon reasoning like "The human brain is a neural network. The human brain is intelligent. Therefore, all I need to do is use a sufficiently large/fast neural network, and my AI will magically become intelligent."
If you cannot explain why your AI will be intelligent without resorting to comparing it to a human brain, you are effectively trying to fly by gluing feathers to your arms. Aeroplanes do not need feathers; if you actually understand how something works, you can change its superficial structure without losing the key attributes that make it work.
Neural networks, in the context of AGI, are a waste of time, computing power, and are a convenient distraction from the damn hard problems we need to solve to actually get working AGI.
("You" in the above should not be construed to refer to the parent.)
So if you can get the energy to cause the reaction in one direction, it's exothermic; if you can do it in the other direction, it's also exothermic.
Not quite correct. Fusion is only exothermic for elements below iron, fission is only exothermic for elements above iron.
FORTUNE'S FUN FACTS TO KNOW AND TELL: A giant panda bear is really a member of the racoon family.