Neural Networks and Artificial Intelligence
Original Article: https://tinyurl.com/yarr4w5e
Artificial Intelligence has made massive strives in the areas of business intelligence, research, robotics, analytics, and even in effectively modeling how the human brain works with artificial neural networks. Different from more basic forms of artificial intelligence, neural networks involve the creation of a series of logical nodes with mathematical weights and connections to other logical nodes. A system of these nodes will receive input, and this input will eventually run through the system of nodes, each node with it’s own mathematical weight or criteria. Based on how the system is set up, a neural network will take that output and come to some eventual result that is hopefully actionable to either an analyst or some program that may be utilizing the neural network.
This artificial system is a direct mirror to how our brains supposedly operate, with these logical nodes representing individual neurons in a human brain. Artificial systems like these can be refined to extreme precision for classification, decision making, or mathematical calculation and many prominent firms already use complex neural networks. Organizations like YouTube, Google, Microsoft and Amazon already use neural networks to direct content, and advertisements on their platforms.
Feel free to answer one of these questions below:
Are the complexity of AI systems outrunning how fast human’s are able to understand them? What good is it having a complex system if you can’t discern how eventual decisions are being made?