Terms starting with P

19 of 250 glossary terms. Each entry links to its own page with why it matters and where it fits.

Definitions here are written for engineers, not grammarians: what the term means, why it matters when it comes up, and where it sits in the curriculum — most term pages name the lessons that lean on the concept, so you can jump from a definition straight to the teaching. Use the letter bar below to move through the alphabet, or press the slash key to search the whole corpus directly.

Every entry carries three things besides the definition: the plain aliases it travels under (listed as “also”), a category tag for which stretch of the curriculum it belongs to, and the cross-references that place it next to its neighbors — the terms you would meet in the same lesson. A term earns a page here only when a lesson in the curriculum actually uses it, so the corpus stays the shape of the material instead of the shape of a dictionary.

One honest way to use this page: read down the list of entries below and note every term you could not define in a sentence if a colleague asked. That list — not the whole letter — is your revision list, and each entry links to the reading that closes the gap.

Paged KV Cache
Infrastructure & serving
A KV-cache memory manager that stores attention state in fixed-size blocks and maps logical sequence positions to physical blocks instead of requiring one contiguous allocation per sequence.
Parameter
Models & inference
A value learned during training, commonly a weight, bias, embedding element, or normalization parameter. Parameter count is one measure of model capacity, but it does not directly determine quality, memory, or serving cost.
Pass@k
Evaluation & safety
Across a task set, the fraction of tasks for which at least one of k sampled candidates passes a defined correctness test.
Patch
AI-native development
A reviewable representation of changes to one or more files, usually expressed as additions and deletions against a known base revision.
Patch Embedding
Multimodal systems
A learned projection that converts an image patch into a fixed-width vector used as one element of a transformer input sequence.
Perplexity
Models & inference
The exponentiated average negative log-likelihood under a stated tokenization and logarithm convention. Lower values mean the model assigned higher probability to the evaluated sequence.
Pipeline Parallelism
Infrastructure & serving
Partitioning sequential groups of model layers across devices and moving microbatches or requests through those stages as a pipeline.
Planning
Agents & tools
Constructing, selecting, or revising a sequence of actions and dependencies intended to move from the current state to a goal.
Postmortem
Reliability & operations
A durable incident record that explains impact, detection, response, contributing conditions, recovery, and owned follow-up actions without assigning blame as a substitute for analysis.
Precision & Recall
Evaluation & safety
Precision asks how many flagged items were correct; recall asks how many relevant items were found. When you change the decision threshold for one fixed scoring model, improving recall often lowers precision and vice versa. A better model can improve both. F1 is their harmonic mean.
Prefill
also: Prefill Phase
Infrastructure & serving
The initial inference stage that processes all supplied input tokens to produce their representations and the attention state required for subsequent autoregressive generation.
Prefix Caching
Infrastructure & serving
Reusing KV-cache blocks produced for an identical eligible token prefix across requests so the serving runtime can skip repeated prefix computation.
Progressive Disclosure
AI-native development
Supplying a person or model with the minimum useful context first, then revealing deeper detail when the task or evidence requires it.
Prompt Cache
Prompting & context
Reuse of provider-side or application-side computation for an identical or eligible prompt prefix so repeated inference avoids some preprocessing work.
Prompt Engineering
Prompting & context
Designing model-facing instructions, examples, constraints, and output requirements to improve behavior on a defined task.
Prompt Injection
Evaluation & safety
An attack or failure mode in which untrusted content influences a model to disregard intended instructions, expose data, misuse tools, or take actions outside the user's goal. The content can arrive directly from a user or indirectly through retrieved pages, files, messages, or tool output.
Prompt Sensitivity
Prompting & context
Variation in model output or measured performance caused by changes to prompt wording, order, formatting, or examples that preserve the intended task.
Provenance Attestation
Security & governance
Authenticated, machine-readable metadata that binds an artifact to claims about how, where, when, and from which inputs it was produced.
Purpose Limitation
Security & governance
For personal data, collecting and using it only for specified, explicit purposes unless a new use has an appropriate compatible or authorized basis.