... provided by my trained Facebook feed and by my Feedly. These ones forced me to think in the last few days, so I decided to try to link them here:
The evolution of hierarchy -- a simple system of ranking -- in biological networks may arise because of the costs associated with network connections:
... the software doesn't have such limits, it is not even limited by three-dimensional space - particular artificial neurons can be linked in virtually any way - opens space to artificial neural networks more complex than biological ones.
Consciousness evolution (excerpt from the link below):
... The Attention Schema Theory (AST), developed over the past five years, may be able to answer those questions. The theory suggests that consciousness arises as a solution to one of the most fundamental problems facing any nervous system: Too much information constantly flows in to be fully processed. The brain evolved increasingly sophisticated mechanisms for deeply processing a few select signals at the expense of others, and in the AST, consciousness is the ultimate result of that evolutionary sequence.
If the theory is right—and that has yet to be determined—then consciousness evolved gradually over the past half billion years and is present in a range of vertebrate species.
Evolved from not selective processing of external sensory inputs - the same response to almost everything - to selective signal enhancement - and after that to a centralized controller for attention that could coordinate among all senses.
In many animals, that central controller is a brain area called the tectum. It coordinates something called overt attention – aiming the satellite dishes of the eyes, ears, and nose toward anything important.
To control the head and the eyes efficiently, it constructs something called an internal model. An internal model is a simulation that keeps track of whatever is being controlled and allows for predictions and planning.
With the evolution of reptiles around 350 to 300 million years ago, a new brain structure began to emerge – the wulst. The cortex is like an upgraded tectum.
The most important difference between the cortex and the tectum may be the kind of attention they control. The tectum is the master of overt attention—pointing the sensory apparatus toward anything important. The cortex ups the ante with something called covert attention. You don’t need to look directly at something to covertly attend to it. Even if you’ve turned your back on an object, your cortex can still focus its processing resources on it.
Unlike the tectum, which models concrete objects like the eyes and the head, the cortex must model something much more abstract. According to the AST, it does so by constructing an attention schema—a constantly updated set of information that describes what covert attention is doing moment-by-moment and what its consequences are.
Then self-models become models of others. Once the basic mechanism was in place, according to the theory, it was further adapted to model the attentional states of others, to allow for social prediction. Not only could the brain attribute consciousness to itself, it began to attribute consciousness to others.
We understand other people by projecting ourselves onto them. But we also understand ourselves by considering the way other people might see us.
We attribute consciousness to characters in a story, puppets, and dolls, storms, rivers, empty spaces, ghosts and gods. Justin Barrett called it the Hyperactive Agency Detection Device, or HADD.
"If the wind rustles the grass and you misinterpret it as a lion, no harm done. But if you fail to detect an actual lion, you’re taken out of the gene pool."
Evolution turned up the amplitude on our tendency to model others and now we’re supremely attuned to each other’s mind states. It gives us our adaptive edge. The inevitable side effect is the detection of false positives or ghosts.
And so the evolutionary story brings us up to date, to human consciousness—something we ascribe to ourselves, to others, and to a rich spirit world of ghosts and gods in the empty spaces around us.
Source:
How do intelligent minds learn?
The two-system set-up is nature’s solution to efficient learning. ... and why we need to sleep?
... and how this model can be used in machine learning?
"All models are wrong, but some are useful." ... for survival
And now we don't need to settle for models at all.
