Exploring Artificial Intelligence Variants and Their Uses – RTInsights

The common thread across all AI technologies is the ability to impart human-like decision-making capabilities into applications and systems.

Artificial intelligence (AI) refers to thesimulation of human intelligence in systems programmed to think like humans andmimic their actions. AI includes a broad range of technologies, including cognitive computing, deep learning, expert systems, machine learning, natural language processing, and IBM Watson.

The common thread across these areas, and allof AI, for that matter, is the ability to impart human-like decision-makingcapabilities into applications and systems. Experts predict AI will be rapidlyadopted because they believe it will be a disruptive technology acrossmany industries.

There already are many examples of the impactAI has in a variety of fields, including:

AI is a very broad field with manysubcategories. Each is aimed at particular application areas and uses specifictechnologies for those application areas. They include

Cognitive computing is the use of computerizedmodels to simulate the human thought process in complex situations where theanswers may be ambiguous and uncertain. It mimics how humans learn, think, and adapt,enabling a wide range of real-time insights and actions.

For example, cognitive computing is being usedto aid human resources with hiring decisions, help doctors make diagnoses and treatment decisionsby using the data relating to a patients case to make suggestions withconfidence levels assigned to them, and improve call center customer experience.

Cognitive computing enables such applicationsusing several technologies, including:

Deep learning is a subset of machine learningin artificial intelligence (AI) that has networks capable of learningunsupervised from unstructured or unlabeled data. Deep learning systems notonly think, but keep learning and self-directing as new data flows in.

Deep learning can play a role in a range ofreal-time, interactive applications, including speech recognition, visual recognition, and machine translation.It accomplishes this using several techniques and technologies including:

An expert system that uses artificialintelligence techniques and databases of expert knowledge to offer advice ormake decisions. In particular, expert systems emulate the decision-makingability of a human expert. Expert systems are designed to solve complexproblems by reasoning through bodies of knowledge, represented mainly asif-then rules rather than through conventional procedural code.

A key attribute of expert systems is that theyautomate many tasks and work interactively with external information (e.g., atext message, an event log, a verbal question or answer, and more). Applicationareas for expert systems include use as:

Machine learning is an application ofartificial intelligence that provides systems the ability to automaticallylearn and improve from experience without being explicitly programmed. Machinelearning uses structured data that has a single, direct input for each fieldused. In general, machine learning makes use of clean data, that is easy towork with, and for which there are no nuances to it. (In contrast, deeplearning uses unstructured data.)

Machine learning is best when there aremassive volumes of structured data that would take years for a human operatorto process. It can efficiently classify information, predicting outcomes basedon previous behavior and performance, and organizing information together basedon key variables. General applications areas include:

Natural language processing (NLP) makes use oflinguistics and artificial intelligence to improve interactions betweencomputers and humans. In many applications, NLP is used to helpsolve a problem, answer a question, or direct a person to an appropriateresource based on the spoken word.

To achieve such results, NLP-bases systemsmake use of some core technologies and deliver essential capabilities,including:

IBM Watson is an artificial intelligence platform that helps businessespredict and shape future outcomes, automate complex processes, and optimizeemployee productivity. It is widely known from its first use case as a questionand answer computer system used in a series of matches against humans on the TVshow Jeopardy!

Today, IBM Watson technology delivers acompetitive advantage to businesses by using AI to unlock the value of data innew, profound ways, giving every member of a business the power of AI. IBMWatson consists of a suite of pre-built applications and tools to givebusinesses insights to predict and shape outcomes and infuse intelligence intoyour workflows. Implementations of IBM Watson include:

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Exploring Artificial Intelligence Variants and Their Uses - RTInsights