Opaque recurrence, and other AI terms that you should probably know
The AI industry is generating a rapidly expanding vocabulary of specialized terms, from technical concepts like large language models and chain-of-thought reasoning to emerging techniques like opaque recurrence featured in OpenAI's latest model. A comprehensive glossary helps decode this evolving terminology that dominates industry meetings, investment discussions, and technology media.
Why It Matters
As artificial intelligence becomes increasingly central to business and technology decisions, understanding the technical language used by researchers and developers is essential for informed participation in AI discussions, whether for investors, builders, or general audiences trying to follow industry developments.
Key Facts
- New AI term: Opaque recurrence, a reasoning technique in OpenAI's Astra model
- Key figures in AGI definitions: OpenAI CEO Sam Altman and Google DeepMind researchers
- AI vocabulary scope: Includes terms like LLMs, RAG, RLHF, and emerging phrases
- Glossary approach: Plain-English definitions of frequently encountered AI terminology
- Document status: Regularly updated as the field evolves
The rapid advancement of artificial intelligence has created a knowledge gap that extends beyond technologists. Industry professionals, investors, and informed observers increasingly encounter specialized vocabulary at meetings and media discussions, yet many terms remain poorly understood even among educated audiences. To address this gap, a comprehensive glossary provides straightforward explanations of frequently used AI concepts without requiring deep technical expertise.
Among the glossary's key offerings are definitions of foundational terms like AGI (artificial general intelligence), which remains deliberately undefined even by leading organizations. OpenAI characterizes AGI as systems capable of performing most economically valuable work better than humans, while Google DeepMind describes it as AI matching human capability across most cognitive tasks. This conceptual ambiguity underscores how contested fundamental AI terminology remains.
Practical applications receive equal coverage, including AI agents—autonomous systems designed to complete multistep tasks like booking reservations or managing code—and coding agents that can independently write, test, and debug software. These capabilities rest on technical foundations like compute (the hardware infrastructure enabling AI operations), deep learning (multi-layered neural networks inspired by human brain structures), and chain-of-thought reasoning (breaking complex problems into intermediate steps for improved accuracy).
The glossary particularly highlights emerging concepts, such as opaque recurrence, which represents the newest terminology gaining attention from AI safety researchers. This treatment acknowledges that AI vocabulary continues evolving as new techniques emerge, making comprehensive documentation essential for maintaining shared understanding across diverse audiences engaged with AI development and deployment.
The living-document approach reflects the field's dynamic nature, with regular updates ensuring the glossary remains relevant as the industry introduces new terms and refines existing concepts, providing a stable reference point amid rapid technological change.
Keep Reading
First Xiaomi, then the world: why Arm might give phone gaming a huge graphics boost
Eric Wu’s newest company, out of stealth since May, is going after construction’s labor crunch
OpenAI Chief Scientist Warns AI Labs May Need to Slow Down
