Definition
Inference
When 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.
How founders on the podcast use it
Running a trained model in production to generate outputs, as opposed to training it.
Tokenomics Will Wreck Your Margins: The AI Model Routing Workflow That Cuts SpendRunning a trained model to get an output. The recurring cost in production.
40,000 Models, One API Key, and a $25M Bet on Open SourceHear it on the podcast2 episodes
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Related terms in AI Fundamentals
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.HyperparameterA setting chosen before training begins, like learning rate or model size, that shapes how a model learns.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.Intelligence layerThe analysis and decision-support layer built on top of the knowledge layer.