Look up any term in AI.

AI Energy Consumption

How much energy an AI query really uses, how training compares with serving, and how to read the numbers without believing either the hype or the panic.

Random Forest (RF)

A random forest averages many decision trees, each grown on a bootstrap sample and split on a random subset of features, to cut variance without adding bias.

Retrieval-Augmented Generation (RAG)

A technique that retrieves relevant documents at query time and feeds them into a language model's prompt, so it answers from current, external facts.

One-shot Learning

Learning a new class from exactly one example — and the split that matters: one-shot prompting updates no weights; classical one-shot training does.

Reinforcement Learning from Human Feedback (RLHF)

How RLHF works, how it compares with DPO and GRPO, and why it makes language models verbose, agreeable and confidently wrong.

Trust

Trust in AI is a person's willingness to rely on a system's output; the aim is calibration — trusting it as much as its real reliability deserves.