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).
Click here to download the booklet
on Artificial Intelligence (in French)
on Artificial Intelligence (in French)
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: