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Artificial Intelligence subfields

Artificial intelligence (AI) is representative of the Fourth Industrial Revolution and is described as the most important of various disruptive technologies which includes blockchain. AI is all around us. Worldwide revenue for AI software, hardware and services is claimed to grow over 16% annually from 2021 to 2025 to reach $327.5Bn, according to International Data Corp. The most valuable companies in the world (from tech to finance), without exception, invest in AI at their own scale.

There are three sorts of AI: artificial narrow intelligence (weak AI) whereby robots or comparable substitutes are able to perform singular tasks well (Siri, Alexa); artificial general intelligence whereby AI seeks to emulate human intelligence and capabilities; and artificial super-intelligence which is futuristic whereby AI mechanisms are superior to human intelligence.

source - The role of Artificial Intelligence in future technology

There are numerous subfields of AI including machine learning and its major subdivisions of deep learning and deep mind, robotics, facial recognition, artificial neural networks, and natural learning progression.

Machine learning is one of the subset of Artificial Intelligence to which Financial markets are turning more and more to in order to create more exacting, nimble models. These predictions help in utilising existing data to pinpoint trends, identify risks, conserve manpower and ensure better information for future planning.

Deep learning - algorithms are trained to search for predictive patterns within the data provided. What is the well-known model in deep learning and how is it applied in the implementation of a quantitative investment? Model such as neural networks are stimulated when they find similarities in, say, the pricing data of stocks.

Reinforcement learning - the machine readjusts itself on the go based on the success or failure of certain actions. Researchers also program penalties into algorithms to discourage certain behaviour by the AI, such as creating strategies that are too similar to those humans already employ.

In financial world, AI can't predict the future, however algorithms can learn patterns and make connections among the data that human can't see. AI is helping the financial industry to streamline and optimise processes ranging from credit decisions to quantitative trading and financial risk management.

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