Data Analytics is the key focus for today’s business’ decision making. The need for data-informed decisions has driven the desire for robust systems that have predictive capabilities. The development and advancement of artificial intelligence (AI) systems serve as the present and future of decision making in various industries. One of the revered qualities of a powerful AI is machine learning. This is the ability of a computer system to identify and learn from data/user behavior trends autonomously.
Yet, always, we have been told that no matter how powerful or intelligent computer systems have become, their application in the business setting cannot guarantee success and is entirely dependent on the human.
What Is Machine Learning?
AI systems have algorithms that mine trends from data and inherently develop a decision-making process to be applied in a real-life business environment aimed at meeting the business objectives. However, machine learning and how the AI algorithms develop its decision-making capabilities depends on the extent to which the individual developers and users empower the system.
TechRepublic highlights three forms of machine learning to include:
- Supervised learning: The user or developer, herein referred to as the “trainer” presents AI system rules (K) that link an input (e.g. smoke and heat) with an output (e.g. alarm or turn on sprinklers)
- Unsupervised learning: The AI system is provided with various inputs and left alone to identify the best patterns and data sets.
- Reinforcement learning: the AI system is continually being fed with structured and unstructured data (e.g. a driverless car programmed continuously with input about a road).
Another offshoot of machine learning, referred as “deep learning” combines several algorithms that react and trigger events in each other to predict future outcomes from a stream of data sets.
Deep learning in AI systems is not dependent on humans (users/trainer) control.
Application of Machine Learning IBM’s Watson is a real-life application of machine learning, infamous for “obliterating” humans on live TV show Jeopardy. Google’s DeepMind is another AI system that used machine learning to win against a world champion of the board game Go (more complex than chess). Amazon’s Echo uses Amazons Alexa to provide the services of a personal assistant to cater for different user needs in the Internet-of-Things. Amazon’s Echo and Alexa use several algorithms for machine learning and deep learning, including natural language understanding (NLU), voice and speech recognition, image and visual among other algorithms. It is amongst the most powerful consumer level AI devices. This gives the user the power to control interconnected devices by engaging and interacting with the AI.
The same algorithms and AI functionalities are applied in the business setting to provide an automated help desk solution and virtual assistants. Chatbots are used as virtual assistants in large scale business functions. Pizza Hut uses Facebook Messenger and Twitter for automatic electronic order taking, and Uber, the taxi-hailing app allows users to engage with the AI to monitor ride status, distance, and compute fare among other uses.
Businesses that have huge needs for one-on-one engagements with clients cannot afford the human resource to handle all these inquiries and orders efficiently, hence the need for AI. Nonetheless, people are required to ensure that personalization is not left to the bots.
Utilizing AI systems is both efficient and profitable for business. Automation of some services gives you room to make improvements on the company’s core product and lets you focus on growing your business. Our managed IT services provide strategies and tools to implement automation using AI and machine learning in your business.
To learn more about utilization of AI in your business, give us a call today at 1-888-245-9926.