Artificial Intelligence, machine learning and NLP

Emerging trends are state-of-the-art technologies that gain popularity and set new trends. Many new technologies appear every day; some fade, others last and change the digital economy and society.

Artificial Intelligence (AI) tries to simulate human intelligence in machines so they behave intelligently: learning, decision-making and problem solving.

• Everyday examples: map apps that pick the fastest route from live traffic data; social sites that recognise and tag friends in photos; digital assistants such as Siri, Google Now, Cortana and Alexa.
• To work with little human help, an AI system builds a knowledge base, a store of facts, assumptions and rules, and makes decisions from it. It can also learn from past experiences or outcomes.

Machine Learning (ML) is a subsystem of AI in which computers learn from data using statistical techniques, without being explicitly programmed by a person.

• Its algorithms, called models, are first trained with training data and tested with testing data.
• After repeated training, once a model's results are accurate enough, it is used to predict for new, unknown data.

Natural Language Processing (NLP) handles interaction between people and computers in human languages such as Hindi and English.

• Examples: predictive typing (suggesting the next word), spell checking, searching or controlling devices by voice, text-to-speech and speech-to-text.
• Machine translation (from one language to another, fairly accurately) and automated customer service (software answering customers' queries and complaints) are fast-growing uses.

Example (new): a music app that notices you skip slow songs in the morning and starts suggesting faster ones is using machine learning; asking it aloud to 'play something cheerful' uses NLP to understand your words.