Definition
Probabilistic
Produces outputs based on likelihood, which can vary and can be wrong. This is how LLMs work.
From the episode “Turn Spreadsheets Into Apps Without a Single Prompt: AI Workflows for Founders With Gainable”Hear it on the podcast1 episode
Learn the language of AI-native founders
Every week: the new terms, tools, and workflows founders are using, straight from the podcast.
Related terms in AI Fundamentals
Physics-informed machine learningML that is constrained to respect physical laws rather than free to guess at any output. Encube's engine embeds physics constraints to keep results valid by definition.Precision NudgingLirio's trademarked approach: behavioral interventions personalized to an individual's specific barriers, delivered with optimized content, channel, timing, and frequency.Predictive SurfacingThe AI capability to surface relevant information, context, or the next action before the user knows to ask for it. The difference between a reactive tool (responds to queries) and a proactive system (anticipates needs). The hallmark of genuinely AI native product design.Predictive SystemsTools that anticipate user needs based on data patterns.Prompt injectionAn attack that hides malicious instructions in input, like a web page or email, to trick an LLM into ignoring its rules or taking unintended actions.RAG (Retrieval-Augmented Generation)A technique where a model first looks up relevant information from documents or databases, then uses it to write a more accurate, up-to-date answer.RationalistsAn online community focused on reasoning and AI risk.Reasoning modelA model built to work through hard problems step by step before answering, trading extra time for better accuracy.