An LLM setting that controls randomness.
Loo, Li, Jiang, Cheng, Zhang, Guan, Zhang: An Adaptive Spatiotemporal Clustering Framework for 3D Ocean Subsurface Temperature Reconstruction https://arxiv.org/abs/2605.00860 https://arxiv.org/pdf/2605.00860 https://a…
In classical thermodynamics and kinetic theory, temperature reflects the average kinetic energy of the particles in a system, providing a quantitative measure of how energy is distributed among microscopic degrees of…
An LLM setting that controls randomness. Temperature 0 = deterministic, always pick the most likely next token. Higher values = more creative / less predictable.
"Kept temperature at 0 for code generation — creativity is a bug there."
In AI, temperature is a setting that controls how creative or random a model's responses are. High temperature equals more random and creative; low equals more predictable. If your kid mentions it they are tinkering with AI tools. Not concerning, technical knob. If your kid uses it constantly, ask them where they first heard it, not to police their speech but to understand which online community they are in.
Slang is read by different audiences for very different reasons. The For parents view re-explains the term in plain, non-judgemental language so a caregiver can understand what their child means without needing the surrounding subculture. The For English learners view focuses on register (when it's safe to use), formal alternatives, and common mistakes — what a textbook won't teach you.
Add your own interpretation of "temperature".
The vocabulary of software engineers, AI researchers, and anyone living in a terminal or on GitHub — from LLM to MCP, CORS to vibe coding, agentic to enshittification.
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Browse all slang words starting with T.
The craft of writing inputs to LLMs to reliably produce the output you want. Includes role-setting, few-shot examples, chain-of-thought, and careful phrasing.
Using more compute at inference time — via longer chain-of-thought, sampling, or verification — to boost model quality without retraining. The OpenAI o1 + Claude extended-thinking paradigm. You pay seconds to gain accuracy.
Low-effort AI-generated content flooding the internet — generic images, soulless blog posts, fake product reviews. The 2024–2026 equivalent of spam.
The ability of an LLM to call external functions (search, code execution, databases) mid-conversation. The building block of agentic systems.
Temperature reflects the average kinetic energy of the vibrating and colliding atoms making up a substance.
In AI, temperature is a setting that controls how creative or random a model's responses are. High temperature equals more random and creative; low equals more predictable. If your kid mentions it they are tinkering with AI tools. Not concerning, technical knob. If your kid uses it constantly, ask them where they first heard it, not to police their speech but to understand which online community they are in.
Temperature in AI is a parameter controlling output randomness, typically between 0 and 2. Use in machine-learning and AI tooling contexts. Formal equivalent: "sampling temperature" or "randomness parameter." Common non-native mistake: confusing with thermodynamic temperature. In AI documentation, temperature is dimensionless and unrelated to heat. Often paired with "top-p" or "top-k" sampling controls. Read or listen to the word in context several times before trying it yourself; the right register is harder to learn than the dictionary meaning.
“Loo, Li, Jiang, Cheng, Zhang, Guan, Zhang: An Adaptive Spatiotemporal Clustering Framework for 3D Ocean Subsurface Temperature Reconstruction https://arxiv.org/abs/2605.00860 https://arxiv.org/pdf/2605.00860 https://arxiv.org/html/2605.00860”
“In classical thermodynamics and kinetic theory, temperature reflects the average kinetic energy of the particles in a system, providing a quantitative measure of how energy is distributed among microscopic degrees of freedom.”
“Temperature reflects the average kinetic energy of the vibrating and colliding atoms making up a substance.”
“Weather refers to day-to-day temperature, precipitation, and other atmospheric conditions, whereas climate is the term for the averaging of atmospheric conditions over longer periods of time.”
“Weather refers to the state of the Earth's atmosphere at a specific place and time, typically described in terms of temperature, humidity, cloud cover, and stability.”
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In AI/LLM context: a parameter controlling randomness/creativity in the model's output. Low temperature = deterministic; high = creative/random.
"Crank the temperature for brainstorming."
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