Council Post: Machines Are Learning From Each Other, But It's A Good Thing

Machine learning (a subset of artificial intelligence) involves the advancement of computer algorithms that evolve and improve over time through learned experience. Because these machines learn through repetition, these models are built on training data or sample sets of data. This training develops in the machine the ability to act without relying on a specific program. The problem is that the data used to build these models can be expensive, and the training models are only effective if they're fed the right quantity and quality of data, neither of which is easy or cheap to obtain. Additionally, the cost of training models is expensive.