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What is AI (artificial intelligence)

Artificial intelligence is the simulation of human intelligence processes by machines, especially in computer systems. Specific applications of AI include specialized expert systems, natural language processing, speech recognition, and machine vision.

How does AI (Artificial Intelligence) operate?

As the buildup of AI has skyrocketed, traders have been scrambling to promote how their products and services use AI. Often what people refer to as AI is simply one component of Artificial Intelligence, such as machine learning. AI requires a foundation of specialized technical hardware and software for creating and training machine learning algorithms. No one programming language is synonymous with Artificial Intelligence, but only a handful including R and Java, Python is popular.


In any case, AI systems work by consuming extensive amounts of tagged training data, analyzing the data for correlations and patterns, and using these patterns to make projections regarding future states. In this way, a chatbot that is fed specimens of text chats can learn to deliver realistic conversations with people, or an image recognition tool can learn to identify and represent entities in images by inspecting millions of examples.

Artificial Intelligence programming concentrates on only three cognitive skills: self-correction, reasoning, and learning.


Reasoning processes

This facet of AI programming concentrates on determining the right algorithm to achieve the desired outcome.

Self-correction processes

This aspect of AI programming is developed to continually fine-tune algorithms and ensure that they deliver the most precise results possible.

Learning processes

This element of AI programming focuses on achieving data and designing rules for how to convert the data into prosecutable information. The rules, which are named algorithms, provide computing machines with step-by-step instructions on how to complete a distinctive task.


Why is artificial intelligence important?

Artificial Intelligence is essential because it can help deliver enterprises insights into their operations that they may or may not have been aware of previously and because, even in some cases, AI can execute tasks more effortlessly and precisely than humans. Specifically, when it comes to repetitive, detail-oriented tasks like as example analyzing considerable numbers of legal documentation to ensure appropriate vocations are filled in correctly, Artificial Intelligence tools can often complete jobs quickly and with considerably fewer errors.


This has helped fuel an outburst in productivity and efficiency while altogether paving the path to entirely new and unique business opportunities for some of the larger enterprises out there. Preparatory to the recent wave of AI, it would have been difficult to imagine using computer software to connect riders to taxis, but today Uber has become one of the largest companies in the world by doing just that. It utilizes sophisticated machine learning algorithms to predict when people are likely to need rides in certain areas, which helps proactively get drivers on the road even before they are needed. Another example, Google has become one of the largest players in providing an extensive range of online services by using machine learning to understand and determine how people use their services and then improve them. In 2017, the company's CEO, Sundar Pichai, pronounced that Google would operate as an AI-first company.


Today's largest and most successful enterprises have used Artificial Intelligence to improve their operations and gain an advantage over their competitors.


What are the advantages and disadvantages of artificial intelligence?

Artificial neural networks and deep learning artificial intelligence technologies are quickly evolving, largely because AI can process large amounts of data at a faster pace and makes projections more accurately than humanly possible.


While huge amounts of data are being created daily burying a human researcher, on the other hand, AI applications that utilize machine learning can take that data and quickly turn it into prosecutable information. As of this writing, the primary disadvantage of using artificial intelligence is that it is quite expensive to process the large amounts of data that AI programming requires.




Good at detail-oriented jobs

Reduced time for data-heavy tasks

Delivers consistent results 

AI-powered virtual agents are always available.





Requires deep technical expertise

A limited supply of qualified workers to build AI tools

Only knows what it's been shown

Lack of ability to generalize from one task to another.


What are the 4 types of artificial intelligence?

Arend Hintze, an assistant professor of integrative biology and computer science and engineering at Michigan State University, explained in an article in 2016 that Artificial Intelligence can be categorized into four types, initiating with the task-specific intelligent systems in wide use today and progressing to sentient systems, which do not yet exist. The categories are as follows


Type 1 

Limited memory 

These AI systems can retain memory, so they can use what they have learned in their past experiences to help guide them to make more precise and accurate future decisions. Some of the decision-making functions in self-driving cars are designed in this particular way defense system.


Type 2 


In this classification, Artificial Intelligence cyber security systems have a sense of self, which gives them consciousness. Machines possessing self-awareness can even comprehend their current state. This type of Artificial Intelligence machine does not yet exist.


Type 3

Theory of mind 

Theory of mind is a psychological term. When applied to Artificial Intelligence, it means that the system would now possess the social intelligence to understand emotions. This type of AI will be able to infer human intentions and predict behavior, a necessary skill for Artificial Intelligence systems to become integral members of human teams and society.

Type 4 

Reactive machines

These AI systems have no memory and are task-specific. An example of this is Deep Blue, the IBM chess program that beat Garry Kasparov in the 1990s. Deep Blue can identify pieces on the chessboard and make predictions, but because it has no memory, it cannot use past experiences to inform future ones.

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