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This site is watching trends in artificial intelligence and in datamining. If you are interesting in analyzing trends, in modelling reality and in predicting the future, then you may find here some interesting links.

One of the subjects of interest, is the human interface and interaction with neural networks. Traditionally, the term neural network was used to refer to a network or circuit of biological neurons. The modern usage of the term often refers to artificial neural networks, which are composed of artificial neurons or nodes. According to wikipedia, the term neural network has two distinct usages:

1. Biological neural networks are made up of real biological neurons that are connected or functionally related in the peripheral or the central nervous system. In the field of neuroscience, they are often identified as groups of biological neurons that perform a specific physiological function.

2. Artificial neural networks are made up of interconnecting artificial neurons (programming constructs that mimic the properties of biological neurons). Artificial neural networks may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system.

Neural networking as extended brainpower. In this blog, we will consider neural networks and artifical intelligence as a model and as a mean to extend the neural processing capabilities of the brain. Artificial intelligence and neural networks are capable of simulating and complementing the human brain and have already been applied successfully to speech recognition, image analysis, robotics, and analytics.