Holloway says, they can and do; when artificial intelligence programmers stopped trying to copy the human neuron, they made much better progress. Humans can do things that AI cannot do, as we saw earlier, but those abilities are not due to the superior learning ability of a human neuron:
Brain neurons operate on what is called the “all or nothing” principle. When enough charge is built up by the neuron’s synapses, it neuron fires. But until then, the neuron does absolutely nothing. The neuron can thus be seen as an on–off switch. It is either firing, or it is not. There is no in-between stage. This makes learning difficult.
To understand why the “all or nothing” principle makes learning difficult, think about playing the “hot or cold” search game where you are searching a room for a treasure. A helpful bystander says “Hotter!” as you get closer to the treasure and “Colder!” as you get farther from it. This signal is very effective in helping you locate the treasure.
But what if we tweak the game. Now, the bystander tells you only whether you have found the treasure or not. If you find the treasure, the bystander says “Yes.” If you did not find the treasure, the bystander says “No.” This new version will take quite a bit longer to play because the bystander is really not providing any information that speeds up the game.
Eric Holloway, “Can computer neural networks learn better than human neurons?” at Mind Matters News
Takehome: Humans can do things that AI cannot do, as we saw earlier, but those abilities are not due to the superior learning ability of a human neuron.
You may also wish to read: Artificial neural networks can show that the mind isn’t the brain Because artificial neural networks are a better version of the brain, whatever neural networks cannot do, the brain cannot do. The human mind can do tasks that an artificial neural network (ANN) cannot. Because the brain works like an ANN, the mind cannot just be what the brain does. (Eric Holloway)