Machine learning (ML)
Beginner
Software that learns patterns from many examples, instead of following rules a person wrote down, and then uses those patterns to make guesses about new cases.
Novice
Software whose behavior comes from fitting a model to examples rather than from hand-written rules. Shown thousands of past chip layouts and how each one turned out, it learns to guess how a new layout will turn out.
Expert
Three styles appear in chip design: supervised prediction (learn to map early data to a later result), black-box optimization (decide which tool settings to try next), and reinforcement learning (learn a sequence of decisions from a score). The recurring problems are scarce labeled data, new designs that differ from the training set, and the hours of tool runtime each label costs.
Explained in AI in EDA (Extras).
See also: Large language model (LLM), Reinforcement learning (RL).