How Accurate Can Supercomputers Predict the Future?

November 21, 2016

Analytics play a major role in today’s business world, but they are also pivotal to the development of artificial intelligence systems. One of the expected qualities of AI is machine learning, the ability for a system to identify and learn from trends. Yet, this extremely practical aspect of artificially intelligent systems may have its uses in a business setting.

What Is Machine Learning?
The concept is that an AI program can use machine learning to examine a large amount of data of a particular kind, and then apply that data in a real-world setting to meet a goal. The way that the algorithm moves forward depends on what it’s allowed to do. The program could be left to its own devices, or it could be told to examine specific information that’s provided to it. The following are methods of machine learning, as explained by TechRepublic:

  • Supervised learning: The “trainer” will present the computer with certain rules that connect an input (an object’s feature, like “smooth,” for example) with an output (the object itself, like a marble).
  • Unsupervised learning: The computer is given inputs and is left alone to discover patterns.
  • Reinforcement learning: A computer system receives input continuously (in the case of a driverless car receiving input about the road, for example) and constantly is improving.

In some instances, another offshoot called “deep learning” can be used. Deep learning is defined as algorithms layered together that are designed to process data and reach predictions. The main difference between machine learning and deep learning is the fact that deep learning doesn’t require the assistance of humans.

How It’s Being Used
Some common uses of machine learning can be seen in IBM’s Watson, which is infamous for being a Jeopardy powerhouse. Google’s DeepMind was capable of using machine learning to beat the world champion of Go, a board game that’s similar, yet far more complex, than chess. Microsoft and Amazon also offer machine learning platforms that are designed to help organizations build programs themselves.

In a business setting, machine learning can be used to help build an automated help desk solution, where a “chatbot” virtual assistant can answer commonly-asked questions. For example, Pizza Hut allows customers to place orders through Facebook Messenger and Twitter, utilizing intelligent technology that can personalize offers and make it easy for customers to quickly reorder their favorite menu items. Popular ride-hailing app Uber utilizes chatbots to let users request rides and get status updates.

This is particularly useful for businesses that don’t have the time to handle each individual inquiry. However, we understand that not every client you have wants to deal with an automated chatbot, and would rather deal with a person.

In order to help your business devote more time to its operations, CTN Solutions offers automated managed IT services that are designed to handle your technology solutions in a hands-off fashion. This allows you to focus on your business, while we keep your technology in proper working order.

To learn more, give us a call at (610) 828- 5500.

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