29,259 technical terms and definitions
AC bias modulation, demodulation frequency, microkelvin sensitivity, gate oxide short localization, backside thermal imaging, failure analysis triage, IR camera defect detection
Lock-in thermography is a non-destructive failure analysis technique that extracts minuscule, defect-generated heat signatures out of a noisy thermal background by applying…
failure analysis advanced
Lock-in thermography detects a defect's heat signature by modulating the device's electrical stimulus at a known frequency and filtering the resulting thermal image signal at that…
STI, isolation, technology, comparison, tradeoffs
LOCOS (local oxidation of silicon), the isolation technique that preceded shallow trench isolation, grows a thick field oxide directly on the silicon surface between active device…
local oxidation of silicon, locos isolation, nitride mask oxidation encroachment
LOCOS Bird's Beak Before shallow trench isolation existed, fabs separated transistors with LOCOS — local oxidation of silicon — and LOCOS had a built-in flaw baked into its own…
LODA Lightweight On-Line Detector of Anomalies Introduction & Motivation LODA Lightweight On-Line Detector of Anomalies addresses a central problem in anomaly detection…
lof, time series models
Temporal LOF is local outlier factor adaptation for anomaly detection in time-indexed data. - It compares local density patterns to flag points that are isolated relative…
lof, time series models
LOF Time Series is local outlier factor anomaly detection applied to embedded time-series windows. - It flags temporal patterns whose local density is unusually low versus…
log aggregation and analysis, log aggregation analysis, log aggregation, aggregation analysis
Log Aggregation and Analysis Introduction & Motivation Log Aggregation and Analysis addresses a central problem in ml-ops process control and ingestion-latency-seconds prediction…
log aggregation search, log aggregation, aggregation search
Log Aggregation Search Introduction & Motivation Log Aggregation Search addresses a central problem in cloud process control and log-ingestion-throughput-rate prediction: how…
time series models
Log-Gaussian Cox is a doubly stochastic point-process model with log-intensity governed by a Gaussian process. - It captures smooth latent risk variation in time or space-time…
model optimization
Log Quantization is a quantization scheme that maps values to logarithmically spaced levels - It represents wide dynamic ranges efficiently with fewer bits. What Is Log…
skew, normalize
Log Transformation is a data preprocessing technique that applies the logarithm function to compress large values and spread out small values — converting right-skewed…
model optimization
Logarithmic quantization applies quantization on a logarithmic scale rather than a linear scale, allocating more precision to smaller values and less precision to larger values.…
metrics, tracing, observability
Observability is the ability to understand the internal state of a system by examining its external outputs — built on three pillars: logs (discrete events for debugging), metrics…
mlops
Logging in AI and ML systems is the practice of recording events, data, and system state for debugging, monitoring, auditing, and improving model performance. Effective logging is…
logging sensitive data, logging sensitive, sensitive data
Logging Sensitive Data Introduction & Motivation Logging Sensitive Data addresses a central problem in programming process control and pii-detection-masking-redaction prediction…
logging structured unstructured, logging structured, structured unstructured
Logging Structured Unstructured Introduction & Motivation Logging Structured Unstructured addresses a central problem in programming process control and log-volume-disk-storage…
logic analyzer integration, logic analyzer, analyzer integration
Logic Analyzer Integration Introduction & Motivation Logic Analyzer Integration addresses a central problem in verification process control and capture-latency-nanoseconds…
advanced test & probe
Logic BIST is an on-chip self-test methodology for exercising digital logic without heavy external tester pattern load - Embedded pattern generators and signature analyzers apply…
lbist, built in self test logic, self test logic, bist controller
Logic BIST (LBIST) is a self-test technique for a chip's combinational and sequential logic that, unlike scan-based ATPG, requires no external test patterns at all. An on-chip…
logic bist diagnosis resolution prediction, logic bist diagnosis, bist diagnosis resolution, diagnosis resolution prediction, logic bist, bist diagnosis
Logic BIST Diagnosis Resolution Prediction with Machine Learning Introduction & Motivation Logic BIST Diagnosis Resolution Prediction with Machine Learning addresses a central…
lec, formal equivalence, sequential equivalence, netlist verification
Logic Equivalence Checking (LEC) is the formal verification technique that mathematically proves two circuit representations compute identical logic functions — comparing RTL…
AND gate, OR gate, NOT gate, NAND gate, XOR gate, half adder, universal gate
A logic gate is an electronic circuit that takes one or more binary inputs, each a high or low voltage standing for 1 or 0, and produces a single binary output determined by…
IC supply chain security, untrusted foundry, key gate XOR, hardware IP protection, split manufacturing, SAT attack logic locking
Logic locking inserts extra key-controlled gates into a chip's design before it ever leaves for fabrication, so the netlist a foundry receives only computes the correct function…
Prolog, Datalog, answer set programming, Colmerauer, Kowalski, Horn clauses, SLD resolution, stable model semantics
Logic programming is a paradigm in which a program is a set of logical statements, typically facts and if-then rules, and computation is the act of proving a query from them, so…
ai architecture
Logic programming with LLMs is the approach of using large language models to interact with, generate code for, and reason within logic programming frameworks — enabling natural…
design
Logic synthesis is the specific step that actually turns a chip's register-transfer-level (RTL) hardware description into an actual gate-level netlist, a concrete network…
synthesis flow, gate level netlist
Logic synthesis basics involve a synthesis tool systematically mapping an RTL design's own described logical behavior onto the specific available logic gates a given standard-cell…
Logic Theory Machine, Newell Shaw Simon 1956, Principia Mathematica, Information Processing Language, IPL, JOHNNIAC, first AI program
The Logic Theorist was a computer program written in 1955–56 by Allen Newell, J. Clifford Shaw and Herbert Simon at RAND and Carnegie Tech that proved theorems of propositional…
lamport logical clocks, lamport logical, logical clocks
Lamport Logical Clocks Introduction & Motivation Lamport Logical Clocks addresses a central problem in distributed-systems process control and causality-detection-accuracy…
deductive reasoning, ai reasoning
Logical reasoning benchmarks are evaluation datasets testing formal reasoning capabilities — measuring whether AI can perform deduction, induction, abduction, and symbolic…
evaluation
LogiQA is the logical reasoning benchmark sourced from the Chinese National Civil Service Examination (NCSE) — providing multiple-choice reading comprehension questions that…
linear, classifier
Logistic regression predicts the probability of a binary outcome by taking a weighted sum of the input features and squashing it through the sigmoid function into a number between…
logistic regression probabilistic classification log odds, logistic regression, probabilistic classification log, f1 l1 l2 mnist passed, logistic regression probabilistic
Logistic Regression: Probabilistic Classification & Log-Odds Introduction & Motivation Logistic regression extends linear regression to classification via logistic (sigmoid)…
supply chain & logistics
Logistics Optimization is the systematic improvement of transport, warehousing, and distribution decisions to minimize cost and delay - It aligns network flows with service…
token control, steering
Logit Bias is a mechanism for directly manipulating the probability of specific tokens in LLM output by adding a bias value to their logits before the softmax step — enabling…
inference
Logit bias manually adjusts token probabilities before sampling to encourage or suppress specific outputs. Mechanism: Add (or subtract) fixed values to logits of specified tokens…
text generation
Logit bias is the token-level decoding control that adds positive or negative score offsets to specific tokens before sampling or search - it enables fine-grained steering…
optimization
Logit Bias is probability adjustment that increases or decreases likelihood of specific tokens during decoding - It is a core method in modern semiconductor AI serving…
explainable ai
Logit lens is the analysis technique that projects intermediate hidden states through the final unembedding to estimate token preferences at each layer - it offers a quick view…
LogME Practical Transferability Estimation without Tuning Introduction & Motivation LogME Practical Transferability Estimation without Tuning addresses a central problem…
reliability
Lognormal distribution is the lifetime distribution model where the logarithm of time-to-failure is normally distributed due to multiplicative variability factors - it is useful…
lognormal yield model prediction accuracy, lognormal yield model, yield model prediction, model prediction accuracy, lognormal yield, yield model, model prediction
Lognormal Yield Model Prediction Accuracy with Machine Learning Introduction & Motivation Lognormal Yield Model Prediction Accuracy with Machine Learning addresses a central…
content creation
Logo generation is the process of creating brand identity marks using AI and design tools — producing distinctive visual symbols, wordmarks, or combination marks that represent…
context, LLM, RoPE, ALiBi, Streaming, LLM, techniques
Long Context LLM Techniques is methods extending large language model context length beyond original training window, enabling processing of longer documents while maintaining…
context window, lost in the middle, needle in a haystack, RoPE scaling, position interpolation, Liu et al. 2023, million-token context
Long context refers to a language model's ability to accept and use very large inputs in a single prompt, measured in tokens, so that whole books, codebases, transcripts…
long context extrapolation positional encoding rope alibi and context window extension, long-context extrapolation positional, positional encoding rope
Long-Context Extrapolation & Positional Encoding: RoPE, ALiBi, and Context-Window Extension Introduction & Motivation Transformer self-attention has no inherent notion of token…
context window extension, rope scaling, context length, yarn context
Long Context LLMs and Context Window Extension is the set of techniques that enable language models to process sequences far exceeding their original training context length…
extended context window, rope scaling, ring attention, context length extrapolation
Long-Context LLMs are the large language model architectures and training techniques that extend the effective context window from the standard 2K-8K tokens to 128K, 1M, or beyond…
context window extension, rope extension interpolation, ntk aware scaling, yarn context scaling
Long Context LLM Processing is the capability of extending large language models to process input sequences of 128K to 1M+ tokens — far beyond the original training context length…