Engineering learning is an important aspect of modern business and research. Using algorithms and neural networks, engineering learning can help computer systems improve performance. They use simple data to build models that help make decisions without programming.
The first example of neural networks occurred in 1943, when mathematician Walter Pitts and neurophysiologist Warren McCulloch wrote a paper on neurons and their functions. That’s when they decided to create a model with the help of circuits, and so the neural network was born.
Further research was done on the Turing test, a computer must convince a human that it is a human and not a computer. Decades later, Google’s DeepMind AI game, AlphaGo, beat world number one in the Go game, an ancient board game that is said to have more possible configurations of fragments than atoms existing in the universe.
There is no doubt that artificial intelligence and machine learning have evolved to unimaginable heights, ideally driven by the power of computing.
With the rise of computer chip creation in classical computing, you will see more pieces approaching the smallest molecular size. Therefore, engineering learning can no longer rely on the power of computing to create powerful models. The reason why engineering learning is now turning to blended learning.
Define learning to compose?
The idea behind blended learning is that one model cannot do everything. For example, when deep neural networks are used for one task, such as classifying images such as cats or dogs or identifying cancer, they perform very well. Unfortunately, it was noticed that the model can only perform one task at a time.
As technology in AI and applications becomes more complex, individual neural networks will only grow. Once that happens, it may explain more complications with more neurons. Therefore, the ability to grow can lead to a dead end.
Now, if you combine all these neural networks to perform some parts of the full task, in general, the model will perform even better when dealing with complex tasks, while maintaining reasonable computing space.
If these tasks are broken down (several neural networks), each of these networks can specialize in a specific domain. The relationship is almost like asking the Prime Minister to make decisions with or without the support of the Minister for Defense, Health, Labor or any other department.