why do scientists struggle to replicate the working of human brains into artifical neural networks? Please tell
It is part of ai
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The Artificial Intelligence misinformation epidemic centred around brains working like neural nets seems to be coming to a head with researchers pivoting to new forms of discovery – focusing on neural coding that could unlock the possibility of brain-computer interface. Of late, there have been many multiple projects and a lot of ongoing research into replicating the human-like thought, mostly by hardware and software simulations of human brain structures. But the question here is — can one simulate the human brain? Are Artificial Neural Networks a good model of the human brain and most importantly — neural networks which are good devices for computation and can neural nets really imitate the human mind?
AI Brain vs Human Brain
To start with, neuroscientists explain the two big problems facing brain simulation — firstly, the human brain is extremely complex, with around 100 billion neurons and 1,000 trillion synaptic interconnections. And it is not digital; instead the brain relies on electrochemical signaling with inter-related timing and analogue components, the sort of molecular and biological machinery that neuroscientists are only beginning to unravel. Which means, despite repeated attempts, simulation of the human mind is complex—and goes exponentially beyond the current technological reach.
On the other hand, neural networks roughly approximate the structure of the human brain. A neural network architecture is arranged into layers, wherein each layer consists of many simple processing units — nodes — further connected to several nodes in the layers above and below. The data is fed into the lowest layer which is then relayed to the next layer. Unlike humans, artificial neural networks are fed with massive amount of data to learn.
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