The term artificial intelligence (AI) refers to computing systems that perform tasks normally considered within the realm of human decision making.Cognitive processes in learning these software-driven systems and intelligent agents incorporate advanced data analytics and big data applications. AI systems leverage this knowledge repository to make decisions and take actions that approximate cognitive functions, including learning and problem solving.Cognitive processes in learning

It’s important to recognize that AI is a constantly moving target. Things that were once considered within the domain of artificial intelligence – optical character recognition and computer chess, for example – are now considered routine computing.Cognitive processes in learning today, robotics, image recognition, natural language processing, real-time analytics tools and various connected systems within the internet of things (iot) all tap AI in order to deliver more advanced features and capabilities.Cognitive processes in learning

By then, the market for AI systems will top $4.8 billion dollars. Consulting firm accenture reports that AI could double annual economic growth rates by 2035 by “changing the nature of work and spawning a new relationship between man and machine.” not surprisingly, observers have both heralded and derided the technology as it filters into business and everyday life.Cognitive processes in learning

General AI. These systems typically learn from the world around them and apply data in a cross-domain way. For example, deepmind, now owned by google, used a neural network to learn how to play video games similar to how humans play them.Cognitive processes in learning natural language processing (NLP).This technology allows machines to read, understand, and interpret human language. NLP uses statistical methods and semantic programming to understand grammar and syntax, and, in some cases, the emotions of the writer or those interacting with a system like a chat bot.Cognitive processes in learning machine perception. Over the last few years, enormous advances in sensors — cameras, microphones, accelerometers, GPS, radar and more — have powered machine perception, which encompasses speech recognition and computer vision used for facial and object recognition.Cognitive processes in learning robotics. Robot devices are widely used in factories, hospitals and other settings. In recent years, drones have also taken flight. These systems — which rely on sophisticated mapping and complex programming—also use machine perception, to navigate through tasks.Cognitive processes in learning social intelligence. Autonomous vehicles, robots, and digital assistants such as siri and alexa require coordination and orchestration. As a result, these systems must have an understanding of human behavior along with a recognition of social norms.Cognitive processes in learning

Machine learning (ML). This branch of AI uses statistical methods and algorithms to discover patterns and “train” systems to make predictions or decisions without explicit programming.Cognitive processes in learning it may consist of supervised and semi-supervised ML (which includes classifications and labels) and unsupervised ML (using only data inputs and no human applied labels).Cognitive processes in learning deep learning. This approach relies on artificial neural networks (anns) to approximate the neural pathways of the human brain. Deep learning systems are particularly valuable for developing computer vision, speech recognition, machine translation, social network filtering, video games and medical diagnosis.Cognitive processes in learning bayesian networks. These systems rely on probabilistic graphical models that use random variables and conditional independence to better understand and act on the relationships between things, such as a drug and side effects or darkness and a light switch turning on.Cognitive processes in learning genetic algorithms. These search algorithms tap a heuristic approach modeled after natural selection. They use mutation models and crossover techniques to solve complex biological challenges and other problems.Cognitive processes in learning

A growing number of consumer-facing apps and tools support image recognition, voice and natural language processing and augmented reality (AR) features that allow consumers to preview a piece of furniture in a room or office or see what makeup looks like without heading to a physical store.Cognitive processes in learning retailers are also using AI for personalized marketing, managing supply chains, and cybersecurity.

Airlines, hotels, and rental car companies use AI to forecast demand and adapt pricing dynamically.Cognitive processes in learning airlines also rely on AI to optimize the use of aircraft for routes, factoring in weather conditions, passenger loads and other variables. They can also understand when aircraft require maintenance.Cognitive processes in learning hotels are using AI, including image recognition, for deploying robots and security monitoring. Autonomous vehicles and smart transportation grids also rely on AI.Cognitive processes in learning

As starting point, it's essential to know how and where AI can improve business processes and build a workforce that understands what artificial intelligence is, where it fits in and what opportunities it offers.Cognitive processes in learning this may require workers to have new knowledge and skills – and AI salaries are competitive – along with a rethinking of service providers, workflows and internal processes.Cognitive processes in learning