Amazing Things Neural Networks Can Do

From Google’s DeepDream that turns pictures
Simply put, neural networks are a form of quantitative analysis technology. Apps that use neural networks use artificial intelligence that analyses data by applying algorithms very similar to the ones used by our brain cells in the process of learning, for example, to identify different data patterns. The software then uses this new information to predict how data will behave in similar cases. Let’s look through a couple of them.
Neural networks are much more effective in solving complex tasks than traditional computing algorithms, which strictly follow the specific instructions given to the app by the programmer. Instead of using a predefined series of logic statements, neural networks use nodes and edges, which perform functions very similar to what our neurons and synapses do. The results of data processing then go through the system, which comes up with a number of outputs.
For instance, Yahoo uses neural networks to detect pornographic images on the internet. The network learnt to distinguish the two types and classify the images and other similarities with great accuracy. Yahoo has recently made the technology open-source, so you can try it out yourself.Google’s search engine trains search robots and improves SE proficiency, implementing this technology for recognition of artificially optimized websites. Analysis of millions of domains lets search spiders collect similarities and the neural network scan for artificial sites that share the same ‘footprint’ - an identical structure or components. Neural systems use the same self-learning technology to improve the comparison results, thereby ensuring only the very domains become Google’s TOP SERP for a user’s search request.
Besides detecting images, neural networks offer many benefits to businesses.
Here is a list of things they can learn to do:
Neural networks are excellent at solving real-world problems because they integrate disparate pieces of information into complex concepts. For example, neural networks have great ability when it comes to image recognition, because they go far beyond understanding individual pixels; they recognise geometric shapes and even pictures with multiple objects. The range of opportunities offered by neural networks is proven by the fact that the leading tech companies have already integrated them into their services:
Neural networks are the key to the future of artificial intelligence, which may come at any moment now, given their fast pace of evolution. We’ll soon hopefully find ourselves in the classic Hollywood scenario where human-like robots assist us in everyday life (as opposed to the one in which robots conquer the world). One thing to be sure of is that neural networks are already having a great effect on the world around us, implementing complicated analysis, working on detailed image recognition and creating multivariable forecasts.