Definition
Neural network
A model loosely inspired by the brain, made of layers of connected artificial neurons that pass signals and learn by adjusting their connections.
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Related terms in AI Fundamentals
Model routingSending different tasks to different underlying models based on which performs best on that task type. CEOfriend routes across Gemini, ChatGPT, Claude, and Grok.Modular GuardrailsBrand-safety constraints applied at the personality layer.MultimodalAble to process more than text, including images and audio. Dobbin reads layouts and critiques them against stated principles.Multimodal AIAI that can work with several types of data at once, such as text, images, audio, and video.NLP (Natural Language Processing)The branch of AI focused on getting computers to understand, interpret, and generate human language.No Free Lunch (AI)The principle that cloud AI platforms offering free or subsidized access to powerful models typically extract value through terms-of-service rights to user data — for training, analysis, or resale. Every convenient upload to a free or low-cost AI tool is an implicit transaction with your data as the currency.Non-deterministic outputAI that can return different answers to the same input. A dealbreaker for fields like finance and accounting that need identical, repeatable results every time.Non-Deterministic SoftwareSoftware whose outputs cannot be precisely predicted from a given set of inputs. Unlike deterministic programs (if X then always Y), AI systems produce probabilistic outputs that may vary given identical inputs — because they generate based on statistical patterns rather than explicit rules. The core challenge for AI deployment in high-stakes, safety-critical, and regulated applications: you can estimate what an AI agent will do, but you can't lock it in the way traditional software guarantees outputs. More advanced models become less deterministic over time, not more.