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Neural Networks And Deep Learning

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Neural Networks And Deep Learning

We model most of AI’s deep learning neural networks on the portion of the brain responsible for logical cognition. This is what results in AI is being only able to focus on narrow tasks as we have not yet managed to locate and understand how to model the understanding of consciousness and high order thought. In conclusion, AI is more similar to us in regard to pure cognition as the black box of neural networks is directly obtained from the human model of basic reactionary thought, however, due to technological or philosophical conundrums we still cannot or have not been able to identify and model our consciousness and

“Artificial neural networks” and “deep learning” are often used interchangeably, which isn’t really correct. Not all neural networks are “deep”, meaning “with many hidden layers”, and not all deep learning architectures are neural networks. There are also deep belief networks, for example. An artificial neural network represents the structure of a human brain modeled on the computer. It consists of neurons and synapses organized into layers.ANN can have millions of neurons connected into one system, which makes it extremely successful at analyzing and even memorizing various information. Here is a video for those who want to dive deeper into the technical details of how artificial neural networks work.

Deep learning is probably one of the hottest tech topics right now. Large corporations and young startups alike are all gold-rushing this fancy field. If you think big data is important, then you should care about deep learning. In the 21st Century. If data is the crude oil, databases and data warehouses are the drilling rigs that digs and pumps the data on the internet, then think of deep learning as the oil refinery that finally turns crude oil into all the useful and insightful final products. There could be a lot of “fossil fuels” hidden underground, and there are a lot of drills and pumps in the market, but without the right refinery tools, you ain’t gonna get anything valuable. That’s why deep learning is important. It’s part of the data-driven big picture.