TheNeurosphere: How neural networks work and how to use them
Neural networks: how they appeared, what they are for and what to expect from them – Theneurosphere comments
Neural networks are widely regarded as one of the most amazing programming paradigms ever created by humans. There is a misconception that the resource is used only in the field of AI development, therefore, it is the lot of scientists and programmers to work with it. In fact, neural networks are so firmly entered our lives that even the person who does not know anything about science encounters them almost daily. The scope of their application is surprisingly wide and covers all areas of modern life. All The Neurosphere neural networks are designed to help people solve their problems and make it easier to achieve goals
Here are some examples of using NN:
- Siri chatbot
- Google Image Search
- MSQRD, FaceN services in social networks
- car navigators
- computer vision in medical institutions
- protective programs in the financial sector, etc.
A short history of neural networks – from the simplest solutions to the development of Theneurosphere
Neural networks are a prototype of the human nervous system modeled by the program. The artificial neurons that make up the network are a simplified copy of the biological neuron model. The first mention of this resource appeared in 1943. An article written by mathematician and neurolinguist Walter Pitts and his co-author, founder of cybernetics, Warren McCulloch, explained the basic principles of the artificial neural network.
The next step in this direction was taken in 1958, when the American scientist Frank Rosenblatt presented the first neural network to the world. However, the speed of its work was so low that the resource did not receive wide distribution. The situation has changed for the better with the development of video cards.
In 1997, the computer beat the world champion Kasparov at chess, this caused an unprecedented excitement around neural networks. But the “explosive” development began only in 2010 with the development of ImageNet – a database of annotated images. In 2015, several companies, including Google and Microsoft, developed and presented algorithms for recognizing emotions and human faces. In the same year, Filipino scientists created a classifier capable of distinguishing animals by voices.
In 2016, experts from the Theneurosphere LLC from Belize presented the beta functionality of a decentralized computer-aided learning network. In 2017, a new branch line was opened in the Beijing underground where a magnetic cushion train runs.
Since 2018, robocars, known as self-driving cars, have been massively appearing in many countries around the world.
Smart homes, self-learning entertaining robotic dogs, medical programs that accurately identify infected cells in the body, robotic harvesters and tractors have already appeared. Not far off are unmanned buses, vertical air taxis, multifunctional robot consultants, houseboats that will clean up the oceans and seas. Mankind has reached a tipping point. People have all the tools they need to change the future of the planet.