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Glossary

1,012 technical terms and definitions

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bicmos logic 1980s propose merging bipolar and cmos on one die

bicmos logic 1980s step 3 propose merging bipolar and cmos on one die, propose merging bipolar and cmos on one die

BiCMOS Logic (Late 1980s): Step 3 — Propose Merging Bipolar and CMOS on One Die 1. Why Not Just Pick the Right Tool for Each Job Steps 1 and 2 establish a clean complementarity…

bicmos logic 1980s test bicmos against voltage and temperature scaling

bicmos logic 1980s step 18 test bicmos against voltage and temperature scaling, test bicmos against voltage and temperature scaling

BiCMOS Logic (Late 1980s): Step 18 — Test BiCMOS Against Voltage and Temperature Scaling 1. Supply-Voltage Scaling Affects the Two Device Types Differently As supply voltages…

bicmos logic 1980s watch pure cmos scaling close the drive current gap

bicmos logic 1980s step 19 watch pure cmos scaling close the drive current gap, watch pure cmos scaling close the drive current gap

BiCMOS Logic (Late 1980s): Step 19 — Watch Pure CMOS Scaling Close the Drive-Current Gap on Its Own 1. The Premise Step 1 Opened Starts to Erode Step 1 opened this series…

bicmos process

bipolar cmos integration, npn bicmos, heterojunction bicmos, sige bicmos, bipolar transistor cmos

BiCMOS Process Integration is the semiconductor manufacturing technology that fabricates both bipolar junction transistors (BJTs) and CMOS FETs on the same silicon substrate…

bicmos process flow

sige bicmos, bipolar cmos integration, bicmos high speed io, bicmos 130nm 90nm

BiCMOS Process Integration is simultaneous fabrication of bipolar (NPN/PNP) and CMOS transistors on the same chip for high-speed analog/RF applications combining bipolar gain…

bidirectional attention

Bidirectional attention allows each token to attend to all other tokens in the sequence, capturing full context. How it works: No masking of attention (except padding), every…

bidirectional language modeling

foundation model

Bidirectional Language Modeling involves predicting missing or masked information conditioned on BOTH left and right context — used by BERT and RoBERTa, it enables deep…

bifacial cell rear passivation drift prediction machine learning

bifacial cell rear passivation drift prediction, bifacial cell rear, cell rear passivation, rear passivation drift, passivation drift prediction, bifacial cell, cell rear

Bifacial Cell Rear Passivation Drift Prediction with Machine Learning Introduction & Motivation Bifacial Cell Rear Passivation Drift Prediction with Machine Learning addresses…

big-bench

evaluation

BIG-Bench (Beyond the Imitation Game Benchmark) is a collaborative benchmark containing over 200 diverse and challenging tasks designed to probe language model capabilities…

big-bench

evaluation

BIG-bench (Beyond the Imitation Game Benchmark) is a collaborative benchmark consisting of 200+ diverse tasks designed to probe the capabilities and limitations of large language…

big-bench

evaluation

BIG-bench is a large collaborative benchmark suite spanning diverse reasoning, knowledge, and generative tasks - It is a core method in modern AI evaluation and safety execution…

big-data-batch-processing machine learning

big data batch processing, big data batch, data batch processing, big data, data batch, batch processing

Big Data Batch Processing Introduction & Motivation Big Data Batch Processing addresses a central problem in systems process control and batch-throughput-latency-trade-off…

big-little-core-scheduling machine learning

big-little core scheduling and load distribution, big-little core scheduling, core scheduling load, scheduling load distribution, big-little core, core scheduling, scheduling load

Big-Little Core Scheduling and Load Distribution Introduction & Motivation Big-Little Core Scheduling and Load Distribution addresses a central problem in soc-design process…

bigbird

foundation model

BigBird is a sparse attention transformer that combines three attention patterns — local sliding window, global tokens, and random connections — to achieve O(n) complexity while…

bigbird attention

architecture

BigBird attention is the sparse transformer attention pattern combining local, random, and global connections to approximate full attention on long sequences - it is designed…

bigbird attention

optimization

BigBird Attention is a sparse-attention design mixing local, random, and global connections for efficient long-context modeling - It is a core method in modern semiconductor AI…

bignas

neural architecture search

BigNAS is once-for-all style NAS training a very large supernet without external distillation dependencies. - It supports extracting many deployable subnetworks from a single…

bigvgan

audio & speech

BigVGAN is a large-scale GAN vocoder with anti-aliased periodic modeling for high-fidelity waveform generation. - It improves naturalness and reduces upsampling artifacts…

bilstm-crf

structured prediction

BiLSTM-CRF is a sequence-labeling architecture that combines contextual BiLSTM encoding with CRF decoding constraints - BiLSTM layers model bidirectional context while CRF layers…

bin color code

manufacturing operations

Bin Color Code is the standardized mapping of electrical test bins to color classes for wafer-map interpretation and yield review - It is a core method in modern semiconductor…

bin map analysis

yield enhancement

Bin Map Analysis is analysis of wafer or lot bin distributions to identify yield-loss patterns and process anomalies - It links fail-bin topology to probable process and design…

bin shift trend analysis prediction machine learning

bin shift trend analysis prediction, bin shift trend, shift trend analysis, trend analysis prediction, bin shift, shift trend, trend analysis, analysis prediction

Bin Shift Trend Analysis Prediction with Machine Learning Introduction & Motivation Bin Shift Trend Analysis Prediction with Machine Learning addresses a central problem…

bin shift trend analysis prediction machine learning

yield analysis predicting bin shift trends in device performance distributions, yield analysis predicting, analysis predicting bin, predicting bin shift, bin shift trends, yield analysis

Yield Analysis: Predicting bin shift trends in device performance distributions Introduction & Motivation Yield Analysis: Predicting bin shift trends in device performance…

bin shift trend analysis prediction machine learning

bin shift trend analysis prediction, bin shift trend, shift trend analysis, trend analysis prediction, bin shift, shift trend, trend analysis, analysis prediction

Bin Shift Trend Analysis Prediction with Machine Learning Introduction & Motivation Bin Shift Trend Analysis Prediction with Machine Learning addresses a central problem…

bin sort

advanced test & probe

Bin Sort is classification of tested dies into quality bins based on pass-fail and parametric criteria - It enables yield accounting, disposition decisions, and speed-grade…

bin split

production

Bin split is the breakdown of dies by performance categories — sorting chips into speed, power, or quality bins based on test results, enabling product differentiation and revenue…

binarized neural networks (bnn)

binarized neural networks, bnn, model optimization

Binarized Neural Networks (BNN) are a specific implementation framework for training and deploying binary neural networks — using the Straight-Through Estimator (STE) to handle…

binary

base 2, binary number system, two's complement, binary arithmetic, Gottfried Leibniz 1703, Boolean algebra, binary search

Binary is the base-2 positional number system, which writes every quantity using only the digits 0 and 1, with each position worth a power of two instead of a power of ten. It is…

binary collision approximation

simulation

Binary Collision Approximation (BCA) is the fundamental physical simplification that makes atomistic simulation of ion-solid interactions computationally tractable — reducing…

binary embeddings

rag

Binary Embeddings is low-precision embedding representations encoded into binary codes for fast similarity search - It is a core method in modern engineering execution workflows.…

binary-indexed-tree-2d machine learning

binary indexed tree 2d queries, binary indexed tree, indexed tree 2d, tree 2d queries, binary indexed, indexed tree, tree 2d, 2d queries

Binary Indexed Tree 2D Queries Introduction & Motivation Binary Indexed Tree 2D Queries addresses a central problem in data-structures process control…

binary logic

two-valued logic, TTL, CMOS logic levels, noise margin, Shannon 1937, high and low voltage, bits

Binary logic is the use of exactly two states, true and false or 1 and 0, to represent information and to compute with it, and in electronics those two states are carried by two…

binary networks

model optimization

Binary Networks is neural networks that constrain weights or activations to binary values for extreme efficiency - They reduce memory use and replace many multiply operations…

binary neural networks

model optimization

Binary Neural Networks (BNNs) are extreme quantization models where both weights and activations are constrained to two values: +1 and -1 — replacing expensive 32-bit…

binary-neural-networks machine learning

Binary Neural Networks Introduction & Motivation Binary Neural Networks addresses a central problem in reducing the size and cost of compression models: how to Reduce the size…

binary-neural-networks-v2 machine learning

Binary Neural Networks (Extended Study) Introduction & Motivation Binary Neural Networks (Extended Study) addresses a central problem in reducing the size and cost of compression…

binary-neural-networks-v3 machine learning

Binary Neural Networks (Extended Study) Introduction & Motivation Binary Neural Networks (Extended Study) addresses a central problem in reducing the size and cost of compression…

binary-search-variants machine learning

binary search variants, binary search, search variants

Binary Search Variants Introduction & Motivation Binary Search Variants addresses a central problem in algorithms process control and search-iterations-log-n prediction: how…

binder jetting green part density prediction machine learning

binder jetting green part density prediction, binder jetting green, jetting green part, green part density, part density prediction, binder jetting, jetting green, green part

Binder Jetting Green Part Density Prediction with Machine Learning Introduction & Motivation Binder Jetting Green Part Density Prediction with Machine Learning addresses a central…

binding affinity prediction

healthcare ai

Binding Affinity Prediction ( , ) is the regression task of estimating the exact thermodynamic strength of the drug-target binding interaction — quantifying how tightly a drug…

binning

discretize, bucket

Binning (Discretization) is a feature engineering technique that converts continuous variables into categorical "buckets" — transforming exact values like Age=27 into ranges like…

binning

manufacturing

Binning is the process of sorting manufactured chips by tested performance characteristics (speed, power, features) into different product grades, maximizing revenue from…

binning by performance

manufacturing

Binning by performance is the post-test classification of chips into product grades based on measured speed, power, and leakage characteristics - it converts natural process…

binomial distribution

n and p parameters, binomial assumptions independence, A/B testing conversions, normal approximation to binomial

The binomial distribution models the number of successes across a fixed number of independent trials, each with the same probability of success — the number of heads in 20 coin…

bio-inspired-sensing-echolocation machine learning

bio inspired sensing echolocation, bio inspired sensing, inspired sensing echolocation, bio inspired, inspired sensing, sensing echolocation

Bio Inspired Sensing Echolocation Introduction & Motivation Bio Inspired Sensing Echolocation addresses a central problem in robotics process control…

bio-robot-hybrid-system machine learning

bio robot hybrid system, bio robot hybrid, robot hybrid system, bio robot, robot hybrid, hybrid system

Bio Robot Hybrid System Introduction & Motivation Bio Robot Hybrid System addresses a central problem in robotics process control and biological-mechanical-hybrid prediction: how…

bioasq

evaluation

BioASQ is the large-scale biomedical question answering and information retrieval challenge — running since 2013 as an annual shared task requiring systems to retrieve relevant…

biocompatible-implant-power-efficiency machine learning

biocompatible implant power efficiency and wireless power, biocompatible implant power, implant power efficiency, power efficiency wireless, efficiency wireless power

Biocompatible Implant Power Efficiency and Wireless Power Introduction & Motivation Biocompatible Implant Power Efficiency and Wireless Power addresses a central problem…