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accdd

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- TL;DR Summary
- Do you think neural networks are the mathematical model of intelligence?

Why do almost all people not think that neural networks are the mathematical model of intelligence?

I briefly explain what I understand:

-A neuron is a mathematical object that takes numerical inputs from other nearby neurons, applies a nonlinear function (combining the input with numbers assigned to the neuron), and spits out an output. A neuron is not intelligent

-we take many neurons, arrange them in a network of neurons with at least one hidden layer (input->hidden layer->output) and get a model that can learn everything that can be done in a computer

-at first the values of the neurons are random, we compute the errors of this model with that of a pre-labeled dataset and change the values of the neurons accordingly, this is learning/training and can be difficult

(http://neuralnetworksanddeeplearning.com/)

Depending on the data submitted to the NN, one can make programs that even show concepts that until a few years ago were thought to be exclusively human, an example being creativity in generating images. (stable diffusion)

In addition, NNs trained on natural text language acquire new capabilities as the size of the NN increases, such as algebraic computation, translation, etc. (https://ai.googleblog.com/2022/04/pathways-language-model-palm-scaling-to.html)

What do you think?

I don't know if this topic has been addressed in other discussions

I briefly explain what I understand:

-A neuron is a mathematical object that takes numerical inputs from other nearby neurons, applies a nonlinear function (combining the input with numbers assigned to the neuron), and spits out an output. A neuron is not intelligent

-we take many neurons, arrange them in a network of neurons with at least one hidden layer (input->hidden layer->output) and get a model that can learn everything that can be done in a computer

-at first the values of the neurons are random, we compute the errors of this model with that of a pre-labeled dataset and change the values of the neurons accordingly, this is learning/training and can be difficult

(http://neuralnetworksanddeeplearning.com/)

Depending on the data submitted to the NN, one can make programs that even show concepts that until a few years ago were thought to be exclusively human, an example being creativity in generating images. (stable diffusion)

In addition, NNs trained on natural text language acquire new capabilities as the size of the NN increases, such as algebraic computation, translation, etc. (https://ai.googleblog.com/2022/04/pathways-language-model-palm-scaling-to.html)

What do you think?

I don't know if this topic has been addressed in other discussions

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