Definition
Specialized model
A smaller AI model trained for one narrow task, usually faster and cheaper than a general LLM.
From the episode “How Gelu Sulugiuc Built AI Workflows That Beat Bloomberg by 47 Seconds”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
Shadow AIUnauthorized AI tools employees use without IT or security oversight — one of the fastest-growing compliance risks in 2026.SingularityThe hypothetical future point where AI capability surpasses human intelligence and becomes self-improving. Sameet references it as the long-term horizon his platform is designed to remain relevant through.Sovereign AIRunning models inside an environment an organization or government fully controls, rather than calling someone else's API.Spatial intelligenceThe ability to understand and reason about the 3D physical world: where things are, how they move, and how they interact.Structural patternA recognizable shape in speech, such as a list or a comparison.SuperfectaBrett Hurt's term for the convergence of AI, quantum computing, robotics, and brain computer interfaces.SuperintelligenceAI that exceeds human intelligence across most domains.Supervised Fine-Tuning (SFT)The standard technique for specializing a pretrained large language model on a specific task or domain: show the model labeled examples of correct input-output pairs, and train it to reproduce that behavior. SFT requires curated training data, and the quality of that data is the primary bottleneck - not the compute or the base model. Ben Turtle built LightningRod to eliminate this bottleneck for teams that lack the scale, budget, or time to pay human labeling companies like Scale AI or Labelbox to create SFT-ready datasets.