Strengths and Weaknesses of Machine Learning Approaches

Machine learning is a branch of artificial intelligence in which computational systems learn from their own experiences in order to make decisions. Rather than hardwiring in a system’s responses to inputs, it is designed to work out for itself how to complete certain tasks. The more example data the system is given the better the results will usually be. These systems are especially good at solving problems that would usually require a human brain such as recognising and classifying images, handwriting recognition, facial recognition, natural language processing (understanding spoken and written language including idioms and sentiment, sometimes language translation), self-drive cars, spam email and fraud detection, and medical diagnosis. Despite its representation in popular literature however, machine learning does not really mimic human thought. It is simply used to augment human intelligence and extend our capabilities, often speeding up complex but repetitive tasks or drawing conclusions from data...