NOVEMBER 20189MANUFACTURINGTECHNOLOGYINSIGHTSHot Topic: Deep LearningDeep learning is a sub-set of machine learning which involves trying to get the machine to think more like the human brain in particular around the area of "feature extraction"­or in the case above, what are the features of a cat and a dog that allows an ultimate way of telling the difference between the two.Imagine yourself now looking at pictures of cats and dogs. It's easy to tell them apart. But have you thought about how you can do this? It's not about number of legs, fur color, absence, or presence of fur, absence or presence of a tail. Even if you were shown part of the animal, you could probably tell the difference fairly accurately.The reason is that there are many data points which together ultimately differentiate between whether a picture of an animal may be best classified as a dog or a cat and those data points are so wide and various that it would be impossible for a programmer to "hard-code". Deep learning is a way of configuring a computer to identify which are the data points (or features) that need to be considered and in what way to make an accurate prediction between a dog or a cat. The word deep comes from the fact that learning happens in multiple layers, i.e. the network has depth. Each layer extracts a certain representation of the data with the ultimate goal of classifying whether an image is a cat or a dog. In our case of cats and dogs, for example, the first layer of a deep learning algorithm might extract pixel darkness, the second layer could extract the edges of the pixel darkness and the third layer would take edges and start joining them in shapes such as ears, legs and tails. Finally, the last layer would take the features from the previous layers (let's say ears, legs and tails for simplicity) and ultimately classify the outcome as a dog or a cat.Hot Topic: Neural NetworksNeural networks are often used to try to emulate the multi-layered thinking capacity of the human brain in deep learning situations­while combining it with huge computing power and speed to think "biologically" about problems.SummaryUnderstanding the building blocks of AI (or at least some of them) is a first step to building a picture of how AI impacts our present and drives our future. If you made it this far, I'm grateful for your reading and any comments you can give. Machine Learning allows computers to do things without being explicitly programmed to do so. How? By learning from patterns and experience just as a child does
< Page 8 | Page 10 >