The Evolution of Artificial Neural Networks: From 19's to the Modern AI

Introduction

Artificial neural networks, humans tried to develop computer systems that could learn and make decisions these systems are able to do tasks such as; recognizing patterns were developed as long as 1958. With years passing along with the appropriate advancements in technology, such networks have today transformed into complex problem solvers. In this blog, we will analyze the roots of ANNs, finally ending at an artificial intelligence breakthrough: deep learning.

Evolutionary Timeline of Neural Networks

In the 1950s perceptrons and the like made the foundations of neural networks. They were also very simple and nonspecialized because the technology of the time was not advanced enough but still these basic models created the embryo for a giant AI that was to come.

The Story of the Emergence of Deep Learning

The increase in capabilities of the neural network architectures was achieved from considerable advances made between 2011 to 2020 where GPUs and software tools like TensorFlow enabled vast amounts of data to be batched, increasing the speed of processing images, language and reasoning in AI.

Conclusion

It is correct to say that without the early networks AI would have never existed, however it is deep learning that has certainly taken the world by storm and with it the possibilities to apply AI have increased immensely, thus speeding up the process of any further developments in machine learning.

Reference

https://www.nvidia.com/en-us/deep-learning-ai/