The predominant AI development method. In the 1980s, AI systems were programmed more like regular data processing applications (if-then-else rules). Today, AI systems use machine learning to "learn by example," which means they are trained on data and in some cases, on all human knowledge (see
AI training).
The Deep Learning Neural Network
Machine learning is generally implemented in a neural network. However, along with "expert systems," other methods were used in the past (see
AI types). The common machine learning approach today is the "deep learning" model which uses a neural network with many layers of analysis. Transformers are one of the most advanced neural networks. See
neural network,
deep learning and
AI transformer.
Pattern Recognition
Machine learning is used in face and voice recognition, medical diagnosis, ad serving, spam filtering and sales forecasting. Today's virtual assistants and chatbots are also the result of machine learning. As more samples become available and more fine tuning is applied, the resulting AI model becomes more dependable. See
AI training vs. inference.
The Hierarchy
Machine learning (ML) is a major category of AI. Approximately 80% to 90% of modern AI systems use machine learning models, and deep learning is the most advanced form.
Well Said
This comparison of machine learning programming and traditional programming comes from Techopedia's "The Ultimate Guide to Applying AI in Business."