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The Basics of Artificial Intelligence Featured

The Basics of Artificial Intelligence "Bibleverse in a biblejournalling bible"

Artificial intelligence (AI) has evolved into one of the most advanced technologies that can be used in different industries for different things. A decade ago, when enthusiasts first talked about the potential of this technology, many laughed it off as just another fantasy and dreams that would never succeed. As we speak today, countries are trying their best to be the leaders in this area. It is the hottest buzzword in business circles and among governments as it is quickly proving to be a critical lynchpin of the digital transformation and automation that many players are seeking to take advantage of to reduce the cost of doing business and increase effectiveness.

Artificial intelligence and machine learning (ML) are now used in a wide range of solutions and applications. Their potential has seen them being implemented in manufacturing, governance, medicine, and content management to boost productivity and enhance effectiveness. With this trend, AI will be disrupting and reshaping industries significantly in the coming years.

What is artificial intelligence?

This is one of the questions that you are likely to ask yourself. The definition of AI has changed over time. However, the main idea is that AI is the building of machines that can think like humans. Humans are known to be unique in how they interpret things around them and use the information they gather to make decisions. The technology is built using humans as blueprints.

How does AI work?

At its basic level, AI systems use historical data to make future predictions. Through matching of data, these systems can generate an outcome that can be used to make decisions about specific topics of interest. AI is also able to simulate and learn the surroundings through sensors and give proper output.

Common Types of AI

Although there is confusion between AI, deep learning, and ML, ML, and Deep Learning are subsets of AI. The common types of machine learning that are in place include:

  • Machine learning (ML)

Machine learning is the application of artificial intelligence, which gives systems the ability to learn and improve automatically without human input. ML aims at creating programs that can access data and use it to learn by themselves.

  • Deep learning

Deep learning is actually the subset of ML, that is a subset of AI whose aim is to mimic the human neural network. It allows machines to learn by trying to mimic humans. The neural networks learn by processing labeled data, that is fed to them during training. This data is used to train systems and see the output produced after a given output. Once the systems have “learned” fully from supplied data and return an accurate result, it can be deployed to play an intended role.

  • Natural language processing (NLP)

NLP is a branch of AI that enables computers to interpret, understand, and manipulate human’s natural language. It has various subsets, including natural language understanding (NLU) and natural language generation (NLG). While NLU entails the ability of machines to read and comprehend, NLG, on the other hand, is a branch that strives to enable the transformation of data into human words.

  • Computer vision

Computer vision is a branch of AI that allows machines to identify and classify objects that they see. It also allows systems to react to what they have seen. Just like humans, computer vision allows machines to see and interpret objects around them and react accordingly. On top of it, they can measure things such as temperature and quality of air, some of that cannot be done by humans. With the advancement of deep learning, computer vision can learn many things, such as images, and translate them appropriately.

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Scott Koegler

Scott Koegler is Executive Editor for PMG360. He is a technology writer and editor with 20+ years experience delivering high value content to readers and publishers. 

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