Artificial Intelligence Uses in everyday Life

Artificial Intelligence Uses

From cash registers at the grocery store to personal computers, artificial intelligence has come a long way. So has the way that humans have applied and interacted with it. Artificial Intelligence (AI) can be seen in several aspects of human life. Some familiar implementations of AI include video games, spam filtering, search engines, text analysis, and fraud detection. Artificial intelligence has become integral to the way our society functions and has great importance to many people. AI was used to protect the company’s valuable assets. Remarkably, artificial intelligence has even used to save human lives. Below are some of the Artificial Intelligence Uses in day-to-day life.

1) Making Recommendations to Your Users

With the amount of data now available through the internet, being able to accurately predict what type of information your users want has become mandatory to maintain an audience. This can be seen in sites like Amazon, Netflix, and YouTube where products, movies, and videos are recommended to visitors based on their previous actions.

Collaborative filtering is the name of a tool that allows for the combination of user input and data sources in order to predict what a user will need, like or be interested in.

Collaborative filtering is able to make automatic predictions by looking at the past interests of a large pool of users and looking for correlations. It then assumes that users who liked the same thing in the past will also like the same things in the near future. That way the system can use other users’ preferences to predict the preferences of future users.

2) Creating Killer Video Games

Video game developers have been a major driving force in artificial intelligence innovation. Video game artificial intelligence was conceived in 1951 by Christopher Strachey and Dietrich Prinz who wrote a chess and checkers game using a Ferranti Mark 1 machine at the University of Manchester.

The first video games used something called discreet logic intelligence, which provides the illusion of intelligence in the “virtual player.” Video games began utilizing neural networks in 1996 with Battlecruiser 3000 AD. Video game developers can target a variety of decisions to a specific neural network. By using neural networks, the video game AI infrastructure can adapt to user behavior.

The more complex video games utilize additional technologies referred to as ‘evaluation of player actions’ and ‘emergent behavior’. Modern-day video games have hundreds, perhaps thousands, of characters. New AI systems learn how the player interacts with the system and positions the characters accordingly. Artificial intelligence can utilize real-life military tactical planning and strategies, as seen in First-person shooter games such as Halo and Counterstrike.

Two new artificial intelligence technologies have emerged since 2008, including techniques dubbed “The Director” and “Milo.” The Director is a strategy that provides players a different experience each time they play the game. This means that no two gaming sessions would be exactly the same. The Director also uses a procedural narrative strategy in which the AI learns how the players interact with the game and gives them increasingly difficult challenges while following a narrative.

Unveiled at E3 2009, ‘Milo’ is an up-and-coming technology that will allow users to interact with voice recognition AI within video games. Milo allows users to have full (and logical) conversations with the system and offers the ability to pass “items” through the TV to the AI system. Milo is currently under development by Lionhead Studios.

Probably the most widely used form of Artificial Intelligence is in Intelligent Search. We benefit from it when we use the mighty Google search engine, while finding Amazon products, and when we get driving directions off Mapquest. Intelligent search is everywhere. There are so many different technologies that are employed in Intelligent search it’s hard to know where to begin.

One popular method uses and records the interaction of users to increasingly improve the intelligence of their search results. If a user clicks on a certain document or page it is given added weight in terms of its relevance. If website owners link to one document or page more often than others that too is taken into account. This of course is only scratching the surface.

Another way intelligence is used in the search is to find what a user is looking for as quickly as possible. The search algorithm A* (a star) is used to make sure that the amount of time, which is used for some information to travel on given paths, is decreased drastically. A function is known as F(x) or the distance + cost heuristic function is utilized by the A*algorithm.

If you’d like to add intelligent search to your application we recommend you check out Lucene. Lucene is a free open source and very innovative system that was created by Apache. It produces and optimizes intelligent searches. It’s very easy to use and you don’t have to make drastic changes in your system environment because it’s completely filed independently.

4) Document Filtering

Artificial intelligence is important and highly effective in its use of text and document classification. One common example is filtering out SPAM from your email inbox. This is accomplished by using a common classification algorithm like Naive Bayes classifier or employing an artificial neural network.”When using this kind of technology [Document Filtering] in your applications, it’s not uncommon to see success rates of up to 99.5%. “

When using this kind of technology in your applications, it’s not uncommon to see success rates of up to 99.5%. So how does this all work? In a nutshell, it takes sample data that you give to it and it learns from it.

By no means is document filtering restricted to its application in SPAM filtration. This kind of technology can be used in countless ways. If you have an interest in integrating this kind of technology in your program you might want to check out the free open-source library WEKA (Waikato Environment for Knowledge Analysis).

5) Using AI In Data Mining

Thanks to a large amount of information available on the internet today – the amount of which doubles every three years – data mining has become an important tool.”…the amount of [data] which doubles every three years….”

The object of data mining is to find and extract patterns from large data sets. Some common uses of data mining are marketing, scientific discovery, and even surveillance. A classic example is a company mining their database to find the customers that would be most likely to accept a certain offer. Data mining is a cost-effective way for large and small companies to get the necessary data when required.

6) Fraud Detection

Data mining, and many other forms of AI, are also extremely useful in fraud detection. This use of data mining for fraud detection takes the form of looking at any abnormalities, which might turn up in the records of the client. For example, Mr. XYZ uses his credit card to the tune of $500 per month. A large number of major and consecutive purchases against that card are going to be noted down and the information conveyed to Mr. XYZ as soon as possible.


A large number of AI developer systems and tools present in the market today have completely changed the manner in which Americans interact and communicate with each other. Artificial intelligence can be integrated into any sort of infrastructure, be it small or large. By now we hope it is evident that artificial intelligence is capable of increasing your business opportunities by making sure that your product reaches the target market. Artificial intelligence is a complex and detailed science so, if you want to know more about it, browse through various informational libraries online (brought to you by intelligent search!). These are only some of the Artificial Intelligence Uses.

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