23 terms to help understand artificial intelligence

Neural networks, predictive parsing, chatbots, data analysis, machine learning, etc. The 8th Fondation Mines-Télécom booklet provides a glossary of 23 terms to clarify some of the terms used in artificial intelligence (AI).

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AI winters – Moments in the history of AI, in which doubts overshadowed previous enthusiasm.

API – (Application Programming Interface), a standardized set of methods by which a software program provides services for other software programs.

Artifact – Object made by a human.

Big Data – Massive data.

Further reading: What is big data?

Bots – Algorithmic robots.

Chatbots – Conversational bots.

Cognitivism – Paradigm of cognitive science focusing on symbols and rules.

Commodities – Basic everyday products.

Cognitive agent – Software that acts in an autonomous, intelligent manner.

Cognitive sciences – Set of scientific disciplines grouping together neurosciences, artificial intelligence, psychology, philosophy, linguistics, anthropology etc. An extremely vast cross-disciplinary field interested in human, animal and artificial thinking.

Connectionism – Paradigm of cognitive science based on neural networks.

Data analysis and data mining – Extraction of knowledge from data.

Decoder – An element in the signal processing chain responsible for recovering a signal after it has passed through a noisy channel.

Deep learning – Learning technique based on deep neural networks, meaning they are composed of many overlapping layers.

Expert systems – Systems that make decisions based on rules and facts.

Formal neural networks – Mathematical and computational representations of biological neurons and their connections.

FPGA – (Field-Programmable Gate Array), an integrated circuit which can be programmed after manufacturing.

GPU – (Graphics Processing Unit), a processor specialized in processing signals which is well-suited for neural networks calculations.

Predictive parsing – Techniques derived from statistics, data mining and game theory to devise hypotheses.

Machine learning – Techniques and algorithms which give computers the ability to learn.

Further reading: What is machine learning?

Semantic networks – Graphs modeling the representation of knowledge.

Value sensitive design – Approach to designing technology that accounts for human values.

Weak/strong AI – Weak AI may specialize in playing chess but is hopeless at cooking. Strong AI excels in all areas where humans are skilled

Further reading on this topic:

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