Machine learning is the application that allows AI to automatically learn and improve from past experiences without being programmed to perform a learning action. For this reason, machine learning primarily focuses on the development of a variety of computer programs that will access data and use the data to learn independently. While this is a simplistic explanation, the coding behind machine learning is anything but simple. For many years, Haval Dosky, an entrepreneur and investor in emerging AI technology companies, has witnessed the AI sector’s ingenuity and innovation. Now an avid proponent of AI technology, Haval Dosky wishes to educate the public on the importance of advancements in AI technology. Below Mr. Dosky will discuss one of the most fascinating aspects of AI, machine learning.
There are three major parts that make-up machine learning systems: the model, the system, parameters, and the learner. The model predicts or identifies information. The parameters are the factors or variables used by the model to make decisions. Finally, the learner is the system that adjusts the previously identified parameters and the model by learning what was predicted versus the actual outcome. Essentially, machine learning systems sort through data to find patterns. After a pattern is identified, the system will make a prediction. If the prediction is incorrect, the machine will identify why and learn from its previous mistakes. Perhaps the most important thing to recognize, however, in regards to this system, is the system can process thousands of pieces of data a minute.
You can see the real-world applications of machine learning on almost all major websites, such as Google, Netflix, YouTube, Spotify, Twitter, and even Facebook. By processing customers’ data, businesses can now guess your next search, favorite shows and movies, songs you may be interested in, shopping suggestions, and topics you care about. Many businesses all over the world have already discovered the benefits machine learning can offer their company and their customer service experience. While AI is most prevalent in business applications, you can also see machine learning being used in the world of art and design. An example of this is IBM’s machine learning system, Watson. For an experiment, Watson was given hundreds of images of artist Guadi’s work as well as other images that possibly influenced his work. Watson then processed the data and gave artists an “informed” concept of sculpture to create. In this case, machine learning helped design a new Guadi original sculpture long after the artist passed away.