Artificial Intelligence (AI) technologies that enable computers and machines to perform intelligently are used widely in business. Some of the most important AI technologies include Speech recognition, Image recognition, Natural Language generation, chatbots, and sentiment analysis. Each of these has several hundred and thousands of components that are combined as a sophisticated application to deliver value to the business. These five AI technologies have drastically changed the way businesses generate, process, and analyze data.
- Image Recognition: The technology of image recognition identifies people, objects, places, and other images. Businesses use this technology in a wide variety of ways such as for automatic inspection of factory lines, to generate damage estimates, to identify objects within images, for controlling manufacturing processes, and to generate models of the real world. Image recognition technology has created huge growth opportunities for industries like e-commerce, automobile, and the gaming industry. It involves three major steps, which start with the collection of data where the computer interprets the image and identifies the data in it and it is further broken down into distinct images for further analysis. The next step is the building of a predictive model using a combination of hardware and software resources where the similar images are grouped together.
- Speech Recognition: In simple terms, this technology is the ability of machines for decoding human voice. Its application in business is increasing. The business application of this AI-driven technology is in the areas of monitoring call center activities, automating verbal translations for travelers, and video game interactions.
- Chatbots: It is a conversational AI feature that enables the application to interact with humans naturally. Eliza, the first chatbot was developed at the MIT Artificial Intelligence Laboratory during 1964-1966. These were limited in terms of the interactions they could make. Now the application of chatbots has increased dramatically in language processing technologies for interpreting and replying to queries.
- Natural Language Generation: Since the volume of data getting generated is escalating rapidly, the technology helps in searching, organizing, and summarizing the most appropriate insight for a given user. This software transforms structured data into natural language.
- Sentiment Analysis: Sentiment Analysis: Sentiment analysis is the finding and classifying of emotions. It may be positive, negative, and neutral within text data using text analysis techniques. It helps businesses to identify sentiments of customers toward products, brands, or services.