Gaming

AI plays a big role in video games and is used primarily to determine the behavior of nonplayer characters in games and to define the way the computer opponent behaves. Popular video games such as Mario, chess, poker, and Road Rash use AI to create human experiences for gaming players.

Natural Language Processing

NLP refers to the AI method of communicating with an intelligent system by using a natural language used by humans, such as English. NLP is required when you want an intelligent system, such as a robot, to perform tasks based on your instructions and to retrieve useful information to assist you in making decisions. Inputs and outputs for NLP-based AI systems are written text and speech. One familiar example of an NLP-based AI system is Alexa.

Alexa was developed based on NLP, which involved procedures that converted speech into words, sounds, and ideas. When instructions in the form of sound are given by people, Amazon (the owner of Alexa), records the words, breaks the words into parts, and consults a database that contains various word pronunciations to determine which words correspond most closely to the combination of individual sounds. In addition, Alexa identifies keywords to make sense of the tasks and carries out corresponding functions per the instructions given. For instance, if Alexa notices words such as jeans or T-shirt, it opens a fashion app. Amazon’s servers then send the information back to your device and Alexa describes the relevant information being sent. Entire conversations take place very quickly, with high-level computation time—the time it takes the information to be sent from a device to Amazon servers and vice versa.

Expert Systems

In AI, an expert system is a computer system that helps human beings make decisions based on inputs entered into it. Such systems are designed to solve complex problems by using existing knowledge in the system and with the help of defining rules, rather than using lists of conventional procedural code.

Expert systems are highly responsive, reliable, and understandable. Expert systems are used in medicine, science, engineering, and so on. The knowledge stored in expert systems is based on knowledge shared by people. Organizations run campaigns to increase the knowledge in expert systems. Today, there are smart enterprise search engines that consider not only keywords used for searches, but also user browsing behavior, profile information, and search trends to extract useful search results from expert systems.

Vision Systems

AI-based vision systems are used to understand, interpret, detect, and comprehend visual input entered into computer systems. For example, developed countries send aircraft to unexplored areas to take photographs that can be used to figure out spatial information or to map these areas. Medical doctors use these systems to aid in their diagnosis of patients based on visual patient inputs. Police use computer software to run facial recognition software to identify suspects based on stored portraits created by forensic artists .

Intelligent Robots

Intelligent robots are able to comprehend human input, process it, make decisions and choose thebest one, then offer it as output to human beings. They have sensors that detect physical data from the real world, such as temperature, light, heat, movement, sound, cushion, and pressure. They are equipped with efficient processors, multiple sensors, and a huge amount of memory so they can exhibit intelligence. In addition, they are capable of learning from their mistakes and can be made to adapt to new environments. A well-known example of intelligent robots is Alibaba, a famous Chinese online e-commerce web site used for delivering orders. The robots operate in a warehouse. When a product request is generated through Alibaba, the most idle robot receives the request, goes to the shelf where the product is located, takes the product off the shelf, then unloads it onto a packing tray for delivery to the customer. Huge warehouses are managed by multiple intelligent robots that operate within a defined time frame.

IBM Watson for Chatbots

We conclude this discussion of AI applications by examining IBM Watson , which is a question-and-answer supercomputer that works based on natural human language and was built using AI. Apart from NLP, this question-and-answer system was built using information retrieval, knowledge representation, automated reasoning, and machine learning technologies.

The main difference between a question-and-answer mechanism and a document search is that a document search takes a keyword query and returns a list of documents, ranked in order of relevance to the query (often based on popularity and page ranking), whereas question-and-answer technology takes a question expressed in natural human language, comprehends it in much greater detail, and provides output with a precise answer to the question.

With IBM Watson, organizations have built chatbots to serve customers 24/7 that meet their expectations and build customer satisfaction. With the AI built in IBM Watson, it has helped global teams discover answers to complex questions with speed and accuracy so these teams can focus on innovative and interesting work. For organizations working on contracts, Watson provides great assistance with contract governance by analyzing and comparing contract elements rapidly—such as obligations, clauses, rights, and parties—and flags differences within seconds. This capability makes searches very easy, regardless of whether exact terms are used.

Siri

Siri is one of the most iconic examples of a personal assistant offered by Apple with its iPhone and iPad. Siri has a built-in friendly voice that interacts with users on a daily basis. Siri assists users in finding information, getting directions, exchanging messages, making voice calls, opening applications, and adding events to calendars. It uses machine learning technology to act intelligently. Furthermore, it is capable of understanding natural language questions and requests. It is currently one of the greatest examples of the machine learning abilities of gadgets.

Tesla

If you are a technology geek and dream of owning a car like the ones shown in Hollywood movies, a Tesla is what you need in your garage. This car is getting smarter day by day through over-the-air updates. Automobiles are moving toward AI. Tesla is one of the best automobiles the world has produced, and has features such as self-driving and predictive capabilities.

Cogito

One of the best examples of a behavioral AI system is Cogito, which was cofounded by Sandy Pentland and Joshua Feast. Cogito was developed based on machine learning and behavioral science to enhance customer collaboration for phone professionals. Cogito handles millions of calls on a daily basis. The AI solution within it analyzes the human voice and provides real-time guidance to enhance behavior.

Netflix

Today, you watch films either in a movie theater or on Netflix, which is known around the world as a one-stop shop for movies. Netflix—a content on-demand service—uses predictive technology to offer recommendations based on user reactions such as interests, choices, and behavior. AI built into Netflix identifies records related to user reactions to recommend movies based on shows that you’ve watched previously. The only drawback to this technology is that small movies go unnoticed and big films grow and become famous.

Pandora

Pandora is one of the most popular and high-demand technology solutions for music lovers. It is also known as the DNA of music. Based on 400 musical characteristics, a team of expert musicians individually analyzed songs that were then shared with end users. This system also recommends other music that would otherwise never get noticed except for the reactions of other users.

Nest

Nest is an AI solution that uses behavioral algorithms to save energy based on user schedules and behaviors. It was a successful and quite famous AI startup that was acquired by Google in 2014 for $3.2 billion. It uses a machine learning process that considers consumers’ body temperature, programs itself in a week, and regulates cooling or heating systems when consumers are not home. It uses a combination of both AI and Bluetooth low energy to provide the desired end results.

Boxever

Boxever is an AI solution that provides incredible experiences for travelers. It relies heavily on machine learning to enhance customer experiences and it makes travel recommendations to create memorable holidays.

Drones

Drones are based on a machine learning system that translates the environment into a three-dimensional model that uses sensors and video cameras. The sensors and camera are used to track the position of a drone, and a trajectory algorithm guides the drone on how and where to move. Drones are used for specific purposes, such as product delivery, news reporting, and discovery of unknown areas.

Echo

Echo was developed by Amazon. It is a revolutionary product that works like a search engine to help you find information on the Internet. It also schedules appointments, manages home lighting, answers questions based on information from the Internet, accesses and reads audio books aloud, and alerts users of traffic status and weather conditions. In addition, Echo notifies you of sports updates, business reviews, and job postings.