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A neural network trained on a wide corpus of text to predict the next token given a context. After pretraining, the model can generate fluent text, answer questions, summarize, and follow instructions, often with billions of parameters. Capability scales with model size and training compute, though returns diminish.
LLMs are the substrate under most current AI products. Almost every Applied AI job description mentions them by name, and AI security roles increasingly center on how to ship them safely.
The cybersecurity glossary covers a parallel term for this concept on the cyber side of the convergence.
Read about LLM Security in cybersecurity →A neural network trained on a wide corpus of text to predict the next token given a context. After pretraining, the model can generate fluent text, answer questions, summarize, and follow instructions, often with billions of parameters. Capability scales with model size and training compute, though returns diminish.
LLMs are the substrate under most current AI products. Almost every Applied AI job description mentions them by name, and AI security roles increasingly center on how to ship them safely.
Definitions are original explanations written for career development purposes. For authoritative technical definitions, refer to NIST, ISO, or the relevant standards body.
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