Creating an AI requires lots of image data upon which to train. The Lucid AI platform brings together a range of tools necessary to prepare this data and to use it to train an AI. The broad steps of building your AI are outlined below.
- A list of labels needs to be created that indicate the ‘things’ you are wanting the AI to be able to recognize. This can be anything you can take photos of, such as plants and insect species associated with an existing Lucid key.
- Next, a set of images is needed representing examples of the subject denoted by each label, for example, a specific weed or insect species. These images are then annotated with the appropriate label and become the data the AI will train on. In simple terms the AI training produces a model of labelled patterns. These desired patterns are in turn used when comparing the pattern of the provided image for identification. How an AI works under the ‘hood’ is beyond the scope of this help. If you are interested in finding out more about the most common AI technology type see the Wikipedia article on convolutional neural networks.
