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Glossary

2,262 technical terms and definitions

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perplexity

ppl, evaluation, cross-entropy, language model, metric

Perplexity is the standard *intrinsic* measure of how well a language model predicts text, and the cleanest way to understand it is as the model's average *branching factor*…

perplexity

evaluation

Perplexity is the standard *intrinsic* measure of how well a language model predicts text, and the cleanest way to understand it is as the model's average *branching factor*…

perplexity

ppl, perplexity metric, language model perplexity, bits per token, cross entropy perplexity, evaluation

Perplexity is the standard *intrinsic* measure of how well a language model predicts text, and the cleanest way to understand it is as the model's average *branching factor*…

perplexity-based detection

evaluation

Perplexity-based detection uses a language model's perplexity (a measure of surprise or uncertainty) on specific text as a signal to detect whether that text was part of…

perplexity filtering

data quality

Perplexity filtering is quality filtering that removes text with abnormal language-model perplexity values - Very high perplexity often indicates corrupted or nonsensical text…

persistent-data-structure machine learning

persistent data structure, persistent data, data structure

Persistent Data Structure Introduction & Motivation Persistent Data Structure addresses a central problem in data-structures process control and version-storage-logarithmic…

persistent-homology-graphs machine learning

Persistent Homology and Topological Graph Learning Introduction & Motivation Persistent Homology and Topological Graph Learning addresses a central problem in graph network…

persistent kernel

gpu persistent thread, persistent cuda, long running kernel, gpu polling kernel

Persistent Kernels are the GPU programming technique where a kernel is launched once and runs indefinitely, continuously polling for new work from a shared queue rather than being…

persistent kernel gpu

long running gpu kernel, work queue gpu, kernel launch overhead, producer consumer gpu

Persistent GPU Kernels is the programming technique where a single GPU kernel runs continuously for the lifetime of the application (or a large phase of it), consuming work items…

persistent-memory-latency-hierarchy machine learning

persistent memory latency hierarchy and access patterns, persistent memory latency, memory latency hierarchy, latency hierarchy access, hierarchy access patterns, memory latency

Persistent Memory Latency Hierarchy and Access Patterns Introduction & Motivation Persistent Memory Latency Hierarchy and Access Patterns addresses a central problem in storage…

persistent memory programming

pmem concurrency, dax programming model, byte addressable storage runtime, nv memory software

Persistent Memory Programming is the software model for using byte addressable nonvolatile memory as a durable low latency data tier. What It Covers Core concept: combines load…

persistent-storage-processing machine learning

persistent storage processing integration, persistent storage processing, storage processing integration, persistent storage, storage processing, processing integration

Persistent Storage Processing Integration Introduction & Motivation Persistent Storage Processing Integration addresses a central problem in storage-computing process control…

persistent threads gpu

persistent kernel, warp level programming, producer consumer gpu, circular buffer gpu

Persistent Threads is a GPU programming pattern where a fixed number of threads remain alive for the entire program duration — repeatedly fetching work from a shared queue rather…

persistent-volume-management machine learning

persistent volume management, persistent volume, volume management

Persistent Volume Management Introduction & Motivation Persistent Volume Management addresses a central problem in cloud process control and volume-lifecycle-creation-deletion…

person-re-identification-reid machine learning

person re identification reid, person re identification, re identification reid, person re, re identification, identification reid

Person Re Identification ReID Introduction & Motivation Person Re Identification ReID addresses a central problem in vision process control and person-reid-pedestrian-matching…

persona

character, roleplay

AI Persona is the character, personality, and behavioral identity defined in a system prompt that transforms a general-purpose language model into a specific, consistent…

persona-based models

dialogue

Persona-based models is dialogue models that explicitly incorporate persona attributes to shape response behavior - Persona embeddings prompts or adapters steer style preferences…

persona consistency

dialogue

Persona Consistency is the challenge of ensuring AI dialogue systems maintain coherent personality traits, knowledge, and behavioral patterns throughout extended conversations…

persona consistency

dialogue

Persona consistency is the ability to maintain stable style tone and identity traits across conversation turns - Consistency mechanisms condition responses on persona constraints…

persona prompting

persona prompts, role play prompting, assigning a persona, expert persona, system prompt persona, in-context impersonation, LLM persona effect

Persona prompting is the practice of instructing a language model to adopt a specific identity, such as a senior tax accountant, a pirate, a skeptical reviewer or a particular…

personal computer

PC, microprocessor, individual computing, software ecosystem, decentralized computing

The personal computer is a general-purpose computer sized, priced, and designed for use by an individual, a category that emerged in the 1970s and transformed computing…

personalization

user modeling, collaborative filtering, content-based filtering, filter bubble, Eli Pariser, cold start problem, recommender privacy

Personalization is the practice of adapting what a system shows or does to the individual user, based on a model of that person's preferences, behaviour and context. It governs…

personalization-user-modeling machine learning

personalization user modeling, personalization user, user modeling

Personalization User Modeling Introduction & Motivation Personalization User Modeling addresses a central problem in systems process control and personalization-latency-real-time…

personalized-federated-ditto machine learning

Ditto Fair and Robust Personalized Federated Learning Introduction & Motivation Ditto Fair and Robust Personalized Federated Learning addresses a central problem in federated…

personalized federated learning

federated learning

Personalized Federated Learning is an approach that learns models customized to individual clients while leveraging collective knowledge — enabling each participant to benefit…

personalized ranking

recommender systems

Personalized ranking orders items specifically for each user — customizing the order of search results, product listings, or content feeds based on individual preferences…

personalized treatment plans

healthcare ai

Personalized treatment plans use AI to customize therapy for each individual patient — integrating patient history, genomics, biomarkers, comorbidities, preferences…

personnel as contamination source

contamination

Personnel contamination is a fundamental cleanroom challenge where human operators are the largest single source of particles, chemicals, and biological contaminants — the human…

perspective api

ai safety

Perspective API is a free, ML-powered API developed by Google's Jigsaw team that analyzes text and scores it for various toxicity attributes — including toxicity, insults…

perspective api

ai safety

Perspective API is the text-moderation service that scores toxicity-related attributes to help detect abusive or harmful language - it is commonly used as a moderation signal…

perspective taking

reasoning

Perspective taking is the cognitive ability to consider situations, problems, or information from different viewpoints — including those of other individuals, stakeholders…

pert

pert, quality & reliability

PERT is program evaluation and review technique that estimates project duration under uncertainty using three-point time estimates - It is a core method in modern semiconductor…

pessimistic mdp

reinforcement learning advanced

Pessimistic MDP is an offline reinforcement-learning formulation that penalizes uncertain value estimates to avoid over-optimistic actions. - It treats out-of-distribution regions…

pets

pets, reinforcement learning advanced

PETS is probabilistic ensembles with trajectory sampling for model-based control - Ensembles model dynamics uncertainty and planning evaluates action sequences through sampled…

pfas abatement destruction efficiency prediction machine learning

pfas abatement destruction efficiency prediction, pfas abatement destruction, abatement destruction efficiency, destruction efficiency prediction, pfas abatement

PFAS Abatement Destruction Efficiency Prediction with Machine Learning Introduction & Motivation PFAS Abatement Destruction Efficiency Prediction with Machine Learning addresses…

pfas free process transition drift prediction machine learning

pfas-free process transition drift prediction, pfas-free process transition, process transition drift, transition drift prediction, pfas-free process, process transition

PFAS-Free Process Transition Drift Prediction with Machine Learning Introduction & Motivation PFAS-Free Process Transition Drift Prediction with Machine Learning addresses…

pfc abatement

pfc, environmental & sustainability

PFC abatement is reduction of perfluorinated compound emissions from semiconductor process exhaust - Combustion plasma or catalytic systems decompose high-global-warming-gas…

pfc destruction efficiency

pfc, environmental & sustainability

PFC Destruction Efficiency is the effectiveness of abatement systems in destroying perfluorinated compound emissions - It is a critical climate-impact metric for semiconductor…

pgas programming model

partitioned global address space, coarray parallel model, upc language model, shmem programming

PGAS Programming Model is the parallel model that presents a global memory view while preserving data locality awareness. What It Covers Core concept: enables direct remote reads…

pgd attack

pgd, ai safety

PGD (Projected Gradient Descent) is the standard strong adversarial attack — an iterative first-order attack that takes multiple gradient ascent steps to maximize the loss within…

pgd attack

pgd, interpretability

PGD Attack is an iterative projected-gradient adversarial attack that refines perturbations over multiple steps - It is a strong first-order method for stress-testing model…

pgvector

postgres, extension

pgvector: Vector Similarity for PostgreSQL Overview pgvector is an open-source extension for PostgreSQL that enables storing, querying, and indexing vectors. It turns the world's…

ph measurement

manufacturing equipment

pH Measurement is monitoring method that measures acidity or alkalinity of process fluids using electrochemical sensors - It is a core method in modern semiconductor AI…

pharmacophore modeling

healthcare ai

Pharmacophore Modeling defines a drug not by its literal atomic structure or chemical bonds, but as a three-dimensional spatial arrangement of abstract chemical interaction points…

phase alignment accuracy prediction machine learning

phase alignment accuracy prediction, phase alignment accuracy, alignment accuracy prediction, phase alignment, alignment accuracy, accuracy prediction

Phase Alignment Accuracy Prediction with Machine Learning Introduction & Motivation Phase Alignment Accuracy Prediction with Machine Learning addresses a central problem in phase…

phase-change-cooling-material machine learning

phase-change cooling material, phase-change cooling, cooling material

Phase-Change Cooling Material Introduction & Motivation Phase-Change Cooling Material addresses a central problem in cooling process control and latent-heat-capacity prediction…