Opaque recurrence, and other AI terms that you should probably know

The rapid expansion of artificial intelligence has created its own vocabulary, increasingly complex for the general public. TechCrunch AI’s article compiles a list of the most important terms that appear in AI discussions, providing clear definitions and usage examples. Among the concepts explained are technical expressions such as “opaque recurrence,” which refers to internal feedback loops in models whose inner workings are not easily interpretable, and others like “prompt engineering,” “foundation model,” “hallucination,” or “few‑shot learning.” Each definition includes a brief description of its meaning, the context in which it is applied, and, when relevant, a reference to associated risks or limitations. The glossary also covers more colloquial jargon circulating in developer and user communities, helping readers understand debates around ethics, bias, and AI governance.

Knowing this lexicon is essential because it enables professionals and non‑specialists alike to follow developments and challenges in AI accurately. A better grasp of technical language helps critically evaluate new tools, engage in regulatory discussions, and make informed decisions about adoption.

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