{"id":57492,"date":"2026-11-03T14:35:38","date_gmt":"2026-11-03T13:35:38","guid":{"rendered":"https:\/\/ritme.com\/lexique-ia-science-recherche\/"},"modified":"2026-11-03T14:35:42","modified_gmt":"2026-11-03T13:35:42","slug":"ai-glossary-science-research","status":"publish","type":"post","link":"https:\/\/ritme.com\/en\/ai-glossary-science-research\/","title":{"rendered":"AI Glossary: Essential Terms for Science and Research"},"content":{"rendered":"\n

Artificial intelligence is already being integrated into many scientific practices: scientific literature monitoring<\/mark><\/a>, quantitative and qualitative data analysis<\/mark><\/a>, scientific writing<\/mark><\/a>, programming<\/mark><\/a>, communication<\/mark><\/a>, image analysis<\/mark><\/a> , and the automation of certain tasks through specialized assistants<\/mark><\/a>. Yet the vocabulary used to discuss these technologies often remains unclear.<\/p>\n\n\n\n

For researchers and scientists, understanding these concepts is not merely a matter of technical vocabulary. It is a first step toward evaluating tools, identifying relevant use cases, and better understanding their methodological, ethical, and scientific limitations.<\/p>\n\n\n\n

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That is why we have compiled an AI glossary<\/strong> of the key concepts to know in science and research, organized into 5 sections<\/strong>:<\/p>\n\n\n\n

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The Different Forms of Artificial Intelligence:<\/a><\/strong><\/mark><\/p>\n\n\n\n

Artificial Intelligence<\/mark><\/a>  \u25aa<\/mark> <\/strong> Analytical AI<\/mark><\/a>  \u25aa<\/mark> <\/strong> Predictive AI<\/mark><\/a>  \u25aa<\/mark> <\/strong> Generative AI<\/mark><\/a>  \u25aa<\/mark> <\/strong> Multimodal AI<\/mark><\/a>  \u25aa<\/mark> <\/strong> Artificial General Intelligence<\/mark><\/a><\/p>\n<\/div>\n<\/div><\/section>\n\n\n\n

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The Fundamental Building Blocks of AI Systems:<\/a><\/mark><\/strong><\/p>\n\n\n\n

Machine Learning<\/mark><\/a>  \u25aa<\/mark> <\/strong> Deep Learning<\/mark><\/a>  \u25aa<\/mark> <\/strong> NLP<\/mark><\/a>  \u25aa<\/mark> <\/strong> LLM<\/mark><\/a>  \u25aa<\/mark> <\/strong> Token<\/mark><\/a><\/p>\n<\/div>\n<\/div><\/section>\n\n\n\n

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Interaction Tools:<\/a><\/strong><\/mark><\/p>\n\n\n\n

Chatbot<\/mark><\/a>  \u25aa<\/mark> <\/strong> AI Assistant<\/mark><\/a>  \u25aa<\/mark> <\/strong> AI Agent<\/mark><\/a><\/p>\n<\/div>\n<\/div><\/section>\n\n\n\n

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Techniques for Adapting and Connecting AI Systems:<\/a><\/mark><\/strong><\/p>\n\n\n\n

Prompt Engineering<\/mark><\/a>  \u25aa<\/mark> <\/strong> RAG<\/mark><\/a>  \u25aa<\/mark> <\/strong> Fine-Tuning<\/mark><\/a>  \u25aa<\/mark> <\/strong> MCP<\/mark><\/a><\/p>\n<\/div>\n<\/div><\/section>\n\n\n\n

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Key Risks to Be Aware Of:<\/a><\/strong><\/mark><\/p>\n\n\n\n

AI Hallucinations<\/mark><\/a>  \u25aa<\/mark> <\/strong> Algorithmic Bias<\/mark><\/a>  \u25aa<\/mark> <\/strong> Shadow AI<\/mark><\/a><\/p>\n<\/div>\n<\/div><\/section>\n<\/div>\n<\/div><\/section>\n<\/div>\n<\/div><\/section>\n\n\n\n

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Want to learn more about AI?<\/strong><\/p>\n\n\n\n

Discover our Focus IA<\/strong> section<\/p>\n<\/div>\n<\/div><\/section>\n\n\n\n

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Our articles are part of our EFFISCIANCE<\/mark><\/strong> AI support offering, dedicated to the use of AI for science<\/mark><\/strong>.<\/p>\n\n\n\n

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Discover all our articles<\/a><\/strong><\/mark><\/p>\n<\/div>\n<\/div><\/section>\n<\/div>\n<\/div><\/section>\n<\/div>\n<\/div><\/section>\n\n\n\n

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The Different Forms of Artificial Intelligence<\/strong><\/h2>\n<\/div>\n<\/div><\/section>\n\n\n\n

From data analysis to content generation, artificial intelligence covers a wide range of uses. Discover the main forms of AI, what they make possible in research, and the opportunities they open up for the scientific practices of tomorrow.<\/p>\n\n\n\n

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#<\/mark> Artificial Intelligence<\/h3>\n\n\n\n
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Artificial intelligence, or AI, refers to a set of methods and systems capable of performing tasks that typically draw on certain human cognitive abilities: classifying, predicting, recognizing patterns, analyzing text, generating content, or supporting decision-making. It is not a single technology, but a family of very different approaches, ranging from specialized statistical models to generative systems.<\/p>\n\n\n\n

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What can it be used for in research?<\/mark><\/strong>
In a scientific context, AI must always be assessed in light of its actual use:<\/p>\n\n\n\n