Limited memory is a type of artificial intelligence. It refers to an AI’s ability to store previous data and predictions, using that data to make better predictions. With limited memory, ML architecture becomes a little more complex. Every ML model requires limited memory to be created, but the model can get deployed as a reactive machine type, which is the most basic and simplest type of AI.
What are the significant kinds of ML models that achieve limited memory?
Reinforcement Learning:These models learn to make better predictions through many cycles of trial and error. This kind of model teaches computers how to play games like chess. Long Short-Term Memory (LSTM):For predicting the next elements in a sequence, the LSTM tags more recent information as more critical and items further in the past as less important. Evolutionary Generative Adversarial Networks (E-GAN):The E-GAN has memory such that it evolves at every evolution. The next model evolves with modifications and mutates towards the path its ancestor found in error.