Definition
BYO-LLM (Bring Your Own LLM)
An architecture pattern where enterprise customers plug their own AI vendor API key into a product so data flows through their existing legal agreements rather than a vendor's.
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Related terms in AI Fundamentals
Bayesian networkA model that maps how variables influence each other using probabilities, useful for reasoning about causes and likely outcomes.Bias (in AI)When an AI system produces results that systematically favor or disadvantage certain groups, often because of skewed training data.Bio-AI hybridSpotitEarly's term for a platform where a biological sensor sits at the front of the pipeline and machine learning handles interpretation and verification.Brand Knowledge GraphEmberos's proprietary mapping of how a brand's entities, products, narratives, and digital assets relate to each other across the internet, enabling predictive visibility modeling.CAI (Collective AI)Collective Health's AI suite built with Google Cloud, spanning a member concierge, an agent copilot, and an enrollment tool.Calibrated ProbabilityA probability estimate that accurately reflects the true likelihood of an outcome over many predictions: if you say something has a 70% chance, it should materialize roughly 70% of the time. Calibration is a distinct measure from raw accuracy - a model can win most of its bets while being badly miscalibrated (e.g., stating 95% confidence on events that only happen 60% of the time). LightningRod measured its forecasting model on Polymarket using calibration as a primary metric, not just profit or win rate. Ben Turtle uses Polymarket bets as a forcing function for calibration training: putting money down on a prediction and seeing the outcome is the fastest way to build an accurate internal probability estimator.Capability BoundaryThe outer limit of what a person or team can produce at a given level of staffing and skill. AI extends this boundary — enabling smaller teams to produce work previously requiring larger ones. Section operates with 32 people doing the work of 45. For founders, this changes the build vs. hire calculation: always audit your AI-extended capability before adding headcount.Capability overhangThe gap between what frontier models can already do and what they're actually being used for.