Bergur Thormundsson
Research expert covering technology in the Nordics, AI and smart cities
Get in touch with us nowHow is it different from Machine Learning?
Machine learning operates on more simplified data than deep learning, and uses structured data for its algorithms. Deep learning, however, eliminates much of the pre-processing involved with machine learning by being capable of ingesting unstructured data, such as texts, and extracting the necessary data. This also means that there is a difference in the skills required to code deep learning and machine learning. Coding capabilities for deep learning algorithms are some of the most sought-after by large organizations around the world.What is the current state of affairs?
There are a number of real-world, deep learning applications; however, they are often hidden behind the scenes, and the average user is unaware of the complexity of the automation at work. Deep learning is used in various fields, such as financial services, customer service, and healthcare. For example, financial services rely on a large amount of analytics to predict stock trading, monitor for fraud, and aid clients in building their investment portfolios. The most prevalent sign of deep learning in customer services is in the number of AI-enabled assistants or chatbots. These are more specialized than the average chatbot that cycles through manual responses. Deep learning chatbots seek to understand if there are multiple responses to ambiguous questions. Depending on the analysis of the chatbot, it will then provide a response or route to a human agent. Healthcare is another field where deep learning has seen significant growth. Digitizing hospital records and images allows for much swifter organization and categorization of affairs, speeding up and increasing the efficiency of hospital work.
