^TagArtificial neural networks (ANNs)

Chocolate and vanilla bourbon ice creams

^{Type
post

Author
Eric Holloway
Date
August 29, 2022

Categorized
Artificial Intelligence, Machine Learning, Philosophy of Mind

Tagged
Artificial neural networks (ANNs), Featured, Information and decision-making, Mind-Brain Distinction}

How We Know the Mind Is About Information, Not Matter or Energy

_{The computer program’s world is one of binary 0 or 1 decisions but the physical world is one of many different shades of more or less} _{Eric Holloway

August 29, 2022

4

Artificial Intelligence, Machine Learning, Philosophy of Mind}

It’s really hard to picture the “mind,” isn’t it? You might think of wavy ghosts, or a spectral light. But nothing very definite. The brain, on the other hand, is very easy to visualize. Images and videos are just a Google away. That’s why it’s easy to assume that our brains are the entities that do our thinking for us. The brain is not only easy to image, it is physical. We can (in theory) touch it. Poke it. The brain even runs off electricity, just like your computer. But what makes a computer run Windows? It isn’t just the transistors on silicon wafers. It isn’t just the electricity coursing through the circuits. Windows itself is a ghostly being, like Read More ›

black metal spiral staircase in grayscale photography

^{Type
post

Author
Eric Holloway
Date
August 8, 2022

Categorized
Artificial Intelligence, Philosophy of Mind, Programming

Tagged
AND function, Artificial neural networks (ANNs), Artificial neural networks vs. neurons, Decision regions in neural networks, Decision surfaces in neural networks, Featured, Incremental learning in neural networks, Logic functions, Logic functions and neural networks, Mind vs. brain, Mind vs. neural networks, Multilayer perceptrons, Neural networks' limitations, Neurons, Neurons vs. artificial neural networks, Perceptrons, Python (program), Truth tables, XOR function}

How AI Neural Networks Show That the Mind Is Not the Brain

_{A series of simple diagrams shows that, while AI learns faster than the human brain, the human mind tackles problems that stump AI} _{Eric Holloway

August 8, 2022

11

Artificial Intelligence, Philosophy of Mind, Programming}

Recently, I’ve been arguing (here and here, for example) that we can use artificial neural networks (ANNs) to prove that the mind is not the brain. To recap, here is the logic of my argument: Premise A: neural networks can learn better than the brainPremise B: the human mind can learn better than a neural networkConclusion: the human mind can learn better than the brain, therefore it is not the brain This means if we can conclusively show the human mind can learn better than a neural network, then the mind is not the brain. For Premise A, I’ve argued that the differentiable neural network is a superior learning model compared to the brain neuron’s “all or nothing principle”. The Read More ›

^{Type
post

Author
Eric Holloway
Date
July 24, 2022

Categorized
Artificial Intelligence, Neuroscience, Philosophy of Mind, Programming

Tagged
Artificial neural networks (ANNs), Artificial neural networks vs. neurons, Featured, Hodgkin-Huxley model of a neuron, McCulloch–Pitts model of neurons, Mind vs. brain, Mind vs. neural networks, Neurons vs. artificial neural networks, Perceptrons and error backpropagation, Society of Mind (book 1987)}

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.} _{Eric Holloway

July 24, 2022

4

Artificial Intelligence, Neuroscience, Philosophy of Mind, Programming}

What is the human mind? AI pioneer Marvin Minsky (1927–2016) said in 1987 that essentially “Minds are what brains do.” That is, the mind is the result of electrical waves cycling through the brain, as neurons spike and synapses transmit signals. But is that true? Can we test this idea? We can indeed, using artificial neural networks. One of the most popular approaches to artificial intelligence is artificial neural networks. These networks, inspired by an early model of how neurons fire (the McCulloch–Pitts model), consist of nodes, where each node is similar to a neuron. A node receives signals and then sends them to its linked nodes based on an activation function. There are, of course, differences between neural networks Read More ›