In this article, we discuss the types of AI and the Ways and how important in our life. Artificial Intelligence (AI) technology is reshaping the way enterprises extract insights from data.
Artificial Intelligence (AI) technology is reshaping the way enterprises extract insights from data. The Gartner’s most recent hype cycle report on Types of AI points out that AI is the most favourable CIO technology initiative for the next five years as a source of business transformation.
PwC predicts that by 2030,
AI can potentially contribute around $15.7 trillion to the global economy.
Many organizations believe that AI is not just a business enabler, but that it is having fundamental impacts on the function itself. AI is automating some long-standing functions to deliver upon their demand for innovative approaches and greater involvement from the IT departments.
Long story short, AI is a big deal. Various flavors of cognitive capabilities make AI a success. It becomes critical for enterprises and business leaders to understand the types of AI and the impact that it will have on the IT operations and market.
Five types of Artificial Intelligence 1. Machine LearningIn the current scenario, machine learning (ML) is the most relevant and popular subset of AI. The Executive’s Guide to the real-world AI, a recent report by Harvard Business Review Analytic Services, stated that ML has been around for years and has matured into a technology.
ML allows computing devices to self-learn from data and implement those findings without any human intervention. Often when a solution/result is hidden in a huge data set, ML is really very helpful. ML is outstanding at data processing and pattern recognition as it takes a fraction of the time that a manual process would take.
Use Cases
Just to list a few of the ML use cases in the real world, ML is used in fraud detection, portfolio management, and risk analysis for financial services. It is also used for targeted marketing campaigns, GPS-based fleet tracking solutions and travel predictions.
2. Deep LearningAny computer program that does something smart is powered by AI, which is an umbrella term that holds ML as a subset. Here, Deep learning is a subset of ML that works towards mimicking the human mind really closely.
CompTIA explains that deep learning allows computer programs to process the problems in multiple layers, simulating the human brain analytical capabilities. The deep learning technologies extract the meaning out of information to build context. While, to increase the chances of getting the correct conclusion, deep learning empowers computer applications to understand the various components of the inputs such as text or visual images.
One explanation by deep AI says that this technology learns from processing the labelled data that is provided during the training. To process the labelled data, deep learning uses neural networks (yeh, that’s what they call them). The output of this processing is used to learn the attributes of the input that were required to come to the correct output. As soon as the sufficient number of inputs have been processed as examples, the so-called neural network can start processing new data.
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