Efficiently updatable neural network

A neural network is like a computer program that learns to do something, like recognizing pictures of animals. It works by taking in lots of examples of pictures with animals and figuring out what features to look for to tell them apart.

An efficiently updatable neural network means that we can make changes to it quickly and easily without having to start over from scratch. It's like being able to change the instructions of the program without having to rewrite the whole thing.

Imagine building a tower out of blocks. If you want to make changes to the tower, it's easier to take out a few blocks and rearrange them than to knock down the whole tower and start over. An efficiently updatable neural network is like building a tower of blocks that you can easily make changes to.

This is important because as we use neural networks to solve more complex problems, we may need to make changes or adjustments as we learn more about the problem. An efficiently updatable neural network makes it easier for us to do this and improve our results.