Artificial intelligence mimics the human brain and forms the basis for all computer learning. It is the future of all complex decision making. Computers are extremely efficient at calculating these combinations and permutations to arrive at the best decision.
Applications of AI can be seen in everyday scenarios, such as financial services fraud detection, retail purchase predictions, and online customer support interactions. To start off, the financial services industry uses artificial intelligence in several ways. Initial scoring of applications for credit uses AI to understand creditworthiness. More advanced AI engines are also employed to monitor and detect fraudulent payment card transactions in real time. Furthermore, besides financial services, call centers use virtual customer assistance to predict and respond to customer inquiries outside of human interaction. Voice recognition, along with simulated human dialog, is the first point of interaction in a customer service inquiry. Lastly, when a person initiates dialog on a webpage via chat, the person is often interacting with a computer running specialized AI. If the chatbot cannot interpret or address the question, a human intervenes to communicate directly with the person. These noninterpretive instances are fed into a machine-learning computation system to improve the AI application for future interactions.
In addition, AI is significant because it successfully tackles a profound set of technical challenges. Increasingly, human capabilities can be undertaken by software, at scale, and at low cost. General analytical tasks, including finding patterns in data, that have been performed by software for many years can also be performed more effectively using AI. Instead of automating manual tasks, AI performs frequent, high-volume, computerized tasks reliably and without fatigue. For this type of automation, human inquiry is still essential to set up the system and ask the right questions.
AI adapts through progressive learning algorithms to let the data do the programming. AI finds structure and regularities in data so that the algorithm acquires a skill. AI analyzes more and deeper data using neural networks that have many hidden layers. AI achieves incredible accuracy through deep neural networks – which was previously impossible. For example, interactions with Alexa, Google Search, and Google Photos are all based on deep learning and they keep getting more accurate the more we use them. In the medical field, AI techniques from deep learning, image classification to object recognition can now be used to find cancer on MRIs with the same accuracy as highly trained radiologists.
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