Definition
Hyperparameter
A setting chosen before training begins, like learning rate or model size, that shapes how a model learns.
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Related terms in AI Fundamentals
Hallucination-Free AIAn AI system constrained to answer only from a specified data set, with no access to the broader internet or general training data. Eliminates invented or inaccurate responses by removing the source of uncertainty — the model can only cite what actually exists in the collection.Human-centered AIAn approach to building AI that puts people's needs, values, and wellbeing first throughout design and deployment.Humane AIAI designed to strengthen human connection and meaning rather than maximize engagement.Hybrid AIDeliberately splitting workloads across frontier models, self-hosted open source models, and fully sealed environments.InferenceWhen a trained model is put to work on new inputs, making predictions or generating answers. It is what happens each time you use an AI product.Inference CostsThe computational expense generated when an AI model processes user queries. High inference costs signal heavy, active user engagement.Inference Engine (AI Context)In the context of Loman.ai, a system that draws contextual inferences from every customer interaction and stores them as a persistent diner profile. Rather than simply transcribing what the caller says, the inference engine captures implicit signals: background noise suggesting children or a social context, dietary patterns suggested by order history, regular timing patterns, and other behavioral cues. These inferences are used to personalize future interactions (surfacing likely orders, suggesting relevant upsells) and will eventually enable personalized outreach. The term distinguishes this layer of contextual reasoning from simple speech transcription or menu lookup - it is the layer that makes the AI agent feel like it knows the customer rather than merely recognizing their phone number.Intelligence boundaryTarun's term for the undefined line between the data you hand a model and the understanding that model derives from it.