Addio Tomàs
siamo fatti della stessa materia di cui sono fatti i 5 stelle
Inspired by neural circuits, many scientists have contributed to the development of mathematical and computational models in an effort to create artificial neural networks (ANN). Similar to the biological circuits, ANNs consist of artificial neurons and artificial synapses. One of the easiest ANNs is called the perceptron (see the figure above), which is basically the mathematical model of an artificial neuron. The artificial neuron is connected to other artificial neurons through synapses, mimicking the biological brain. The artificial neuron receives different inputs from neighboring neurons. These inputs are weighted based on the value of their connecting artificial synapse. The perceptron ANN is designed so that the artificial neuron passes the signal (“1”) to the output when its total weighted input exceeds a certain threshold; otherwise, the output stays “0”. The perceptron can be trained to classify binary objects, which belong to either one class (labeled as “1”) or another (labeled as “0”). The perceptron can recognize rudimentary patterns by being able to classify objects to either class “1” or class “0”. For example, a perceptron can learn to classify animals either as cats or not cats. More complicated ANNs utilizing multiple layers of neurons can be used to recognize advanced patterns, such as images. The first layer of neurons can detect edges, the next layer can detect basic shapes, the third one deals with colors, and so forth, with the last layer combining all this information and recognizing more advanced features like a face or an object.
Currently, ANNs implemented in software are widely used for image and sound recognition and machine learning. However, the software implementation of ANNs is inherently slow because the underlying digital computer hardware is not appropriate for such tasks. Intensive research has been pursued in the past decade in trying to find an appropriate hardware implementation for ANNs. The current digital transistor is an approximate model for an artificial neuron. What is missing is an artificial synapse that has good analog properties.
https://theglobalscientist.com/2015/...e-human-brain/
Truth is a paradox and relativism his compass.
Ma poi secondo voi, non riescono a trovare la cure per fermare la perdita di neuroni nell'alzheimer e mo vogliono addirittura riportare in vita i morti?
Nè DAVANTI Nè DI DIETRO, MA DI LATO
lavorare sulla tecnologia per costruire una intelligenza artificiale che possa eguagliare quella umana e' come correre per raggiungere l'orizzonte.
sec me nemmeno fra tremila anni avremo un pc che decide di propria iniziativa di mentire e darsi malato perche' non ha voglia di lavorare. opinione personale.