Definition
Reasoning model
A model built to work through hard problems step by step before answering, trading extra time for better accuracy.
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Related terms in AI Fundamentals
ProbabilisticProduces outputs based on likelihood, which can vary and can be wrong. This is how LLMs work.Prompt injectionAn attack that hides malicious instructions in input, like a web page or email, to trick an LLM into ignoring its rules or taking unintended actions.RAG (Retrieval-Augmented Generation)A technique where a model first looks up relevant information from documents or databases, then uses it to write a more accurate, up-to-date answer.RationalistsAn online community focused on reasoning and AI risk.Red teamingAdversarial testing that attacks your own systems to find vulnerabilities before someone else does.Reinforcement learningTraining an AI through trial and error: it takes actions, gets rewards or penalties, and learns which choices lead to better results.Responsible AIThe principles and practices for developing and deploying AI ethically and safely, including fairness, transparency, and accountability.RWKVAn attention-free, linear architecture Eugene co-created, now under the Linux Foundation, designed to lower inference cost.