Case Study (Discussion)

Discussion

Deep learning is now an integral part of our daily lives, seamlessly integrated into products and services. However, users are often unaware of the intricate data processing happening in the background. Here are some examples of such applications:

Law enforcement

Sophisticated deep learning algorithms have the capability to scrutinize and comprehend transactional data, thereby detecting suspicious patterns that might signal fraudulent or criminal activity. By harnessing the power of speech recognition, computer vision, and other deep learning applications, investigative analysis can be expedited and enhanced through the extraction of valuable insights from sound and video recordings, images, and documents. This allows law enforcement personnel to efficiently analyze vast quantities of data with unparalleled precision and speed.

Financial services 

Financial institutions regularly use predictive analytics to drive algorithmic trading of stocks, assess business risks for loan approvals, detect fraud, and help manage credit and investment portfolios for clients.

Customer service

Many organizations incorporate deep learning technology into their customer service processes. Chatbots—used in a variety of applications, services, and customer service portals—are a straightforward form of AI. Traditional chatbots use natural language and even visual recognition, commonly found in call centre-like menus. However, more sophisticated chatbot solutions attempt to determine, through learning, if there are multiple responses to ambiguous questions. Based on the responses it receives, the chatbot then tries to answer these questions directly or route the conversation to a human user.

Virtual assistants like Apple's Siri, Amazon Alexa, or Google Assistant extend the idea of a chatbot by enabling speech recognition functionality. This creates a new method to engage users in a personalized way.

Healthcare

The healthcare industry has benefited greatly from deep learning capabilities ever since the digitization of hospital records and images. Image recognition applications can support medical imaging specialists and radiologists, helping them analyze and assess more images in less time (IBM, 2023).

Reference List:

IBM (2023)  What is deep learning?. Available at: https://www.ibm.com/topics/deep-learning (Accessed: 02 June 2023).