Glossary

1

1-bit LLMs
1-bit LLMs are an advanced type of Large Language Model. Unlike traditional LLMs that use 16 or 32 bits for each weight parameter, a 1-bit LLM drastically reduces the model's memory footprint and computational demands, making it...

3

3rd Generation Partnership Project (3GPP)
The 3rd Generation Partnership Project (3GPP) is a worldwide collaboration between groups of telecommunications standards associations. The project was established in December 1998 with the aim of making a globally applicable...

5

5G
5G introduces a new global wireless standard characterized by its ability to provide higher speeds, reduced latency, and greater capacity than previous network generations, including the most modern 4G LTE networks. 5G is the...
5G corridor
5G corridors are part of the EU Digital Decade Strategy and aim to provide 5G coverage along transport paths such as roads, railways, and waterways. The goal is to improve road safety, optimize traffic flow, reduce CO2...
5G functional split architecture
The 5G functional split is an architecture that involves dividing the base station functions across different physical nodes, namely the Centralized Unit (CU), Distributed Unit (DU), and Radio Unit (RU). The 5G split...

6

6G
6G, or sixth-generation wireless, is the planned successor to 5G cellular technology. It is currently under research and development, with the aim to provide substantially higher capacity and lower latency than its...

7

7.2 split
The 7.2x split is the most common RAN functional split configuration in use today for 4G and 5G networks due to its balance of fronthaul demands and centralization benefits. Processing Location: In a 7.2x split, the RU handles...

A

access network
An access network is the segment of a telecommunications network that connects subscribers or end-user devices to their immediate service provider. It is the part of the network that facilitates the connection of end-users (and...
AI access point
A physical location in an edge network where AI servers operate and interconnection is performed. These are often operated out of micro modular data centers of varying capacities, but can also be built inside existing data...
AI pipeline
An AI pipeline is an interconnected and streamlined collection of operations designed to automate and manage the workflow of machine learning (ML) and artificial intelligence (AI) processes. It encompasses the entire journey of...
ambient intelligence (Aml)
Ambient intelligence (AmI) refers to electronic environments that are sensitive and responsive to the presence of people. It is a human-centric approach to computing, where the technology is embedded in our everyday environments...
Anthropic (company)
Anthropic is an American artificial intelligence (AI) startup company that focuses on developing general AI systems and large language models with a strong emphasis on safety and ethical considerations. Founded in 2021 by former...
artificial intelligence for IT operations (AIOps)
AIOps, short for "Artificial Intelligence for IT Operations," refers to the application of artificial intelligence (AI), including machine learning and analytics, to automate and enhance IT operations. It involves using big data...
AS (autonomous system)
An Autonomous System (AS) is a group of IP networks operated by one or more network operators that has a single, clearly defined routing policy. Each AS is identified by a unique Autonomous System Number (ASN), and is used for...
ASN (autonomous system number)
An Autonomous System Number (ASN) is a unique identifier allocated to each autonomous system (AS) to facilitate its identification by the Internet Assigned Numbers Authority (IANA) and Regional Internet Registries (RIRs). An AS...
Augmented Reality (AR)
Augmented Reality (AR) is a technology that overlays digital information—such as images, videos, sounds, or other data—onto the real-world environment in real-time. Unlike Virtual Reality (VR), which immerses users in a...
autoencoder
An autoencoder is a type of artificial neural network used to learn efficient representations of data, typically for the purpose of dimensionality reduction or feature learning. It operates under unsupervised learning, meaning...
autoregressive language modeling
Autoregressive language modeling involves predicting the next word in a sequence of words based on previous words. It is a statistical language model that learns the probability of a word given the preceding words in a sequence....

B

backbone network
A backbone network refers to the principal pathway within a network infrastructure that connects multiple networks together, facilitating the exchange of data across various segments of the network. This core part of a computer...
backhaul
Backhaul, in mobile networs, refers to the part of the network infrastructure that connects the edge of the network, such as cell towers or base stations, to the core network, which then connects to the internet or other...
backpropagation
Backpropagation is an algorithm used to improve the accuracy of predictions in neural networks, which are systems designed to mimic the way the human brain processes information. When a neural network is being trained, it makes...
bare-metal cloud
A bare-metal cloud refers to a service that provides users with dedicated, physical servers managed and maintained by a third-party managed service provider (MSP). These servers are “bare metal,” meaning they come without any...
Baseband Unit (BBU)
A Baseband Unit (BBU) is a telecommunications device that processes baseband signals, which are the original frequencies of transmissions before any modulation. In a Radio Access Network (RAN), the BBU is responsible for...
beamforming
Beamforming is a technique used in wireless communication systems to enhance the directionality and strength of a transmitted or received signal. It involves focusing the transmission or reception of electromagnetic waves in a...
BERT (Bidirectional Encoder Representations from Transformers)
BERT, which stands for Bidirectional Encoder Representations from Transformers, is a groundbreaking model in the field of natural language processing (NLP). Shared by Google in 2018, BERT is designed to understand the context of...
BGP (Border Gateway Protocol)
Border Gateway Protocol (BGP) is the protocol that determines the best routes for data transmission on the internet by exchanging routing and reachability information among autonomous systems (AS). BGP is crucial for the...
BGP convergence
BGP convergence refers to the process by which the Border Gateway Protocol (BGP) reaches a stable state where all BGP routers have the same understanding of the best paths to various networks. This state is achieved after all...
BGP path selection process
The Border Gateway Protocol (BGP) is a complex routing protocol that plays a crucial role in the functioning of the internet. It is responsible for finding the best route for data transmission between different networks,...
BitNet b1.58
BitNet b1.58 is a new type of Large Language Model called a 1-bit LLM. 1-bit LLMs achieve remarkable efficiency without sacrificing performance. They do this by representing the majority of its knowledge with a simplified code...
BlueField
BlueField is Nvidia’s line of data processing units (DPUs) designed for data centers and high-performance computing applications. BlueField is a system-on-a-chip that integrates networking, storage, security, and management...
Border Gateway Protocol (BGP)
Border Gateway Protocol (BGP) is a critical component of the internet’s infrastructure, acting as the protocol that manages how data packets are routed across different networks to reach their destination. It is an Internet...
bump-in-the-wire (BITW)
“Bump-in-the-wire” (BITW) refers to a network security device or system that is inserted into the network flow to inspect, and potentially modify or block, traffic without the need for any significant reconfiguration of the...

C

Camara Project
The Camara Project is an initiative within the Linux Foundation aimed at creating a federated platform solution for exposing operator network capabilities to external applications through standardized APIs. It is a collaborative...
classification
Classification is a machine learning technique where a computer program learns to automatically sort things into different groups. After learning from pre-labeled examples (supervised learning), the program can then take new,...
Claude
Claude is an AI assistant developed by Anthropic, designed to perform a wide range of conversational and text processing tasks. Claude is accessible through a chat interface and API, and it has been integrated into various...
CLIP (Contrastive Language-Image Pre-training)
CLIP (Contrastive Language–Image Pre-training) is a neural network model developed by OpenAI, introduced on January 5, 2021. It efficiently learns visual concepts from natural language supervision, marking a significant...
cloud GPU
A cloud GPU typically refers to a single GPU or a set of GPUs that are available for rent on a cloud platform. Users can access these GPUs over the internet to perform computationally intensive tasks such as machine learning,...
cloudlet
A cloudlet refers to a small-scale data center or a cluster of computers designed to provide cloud computing services to mobile devices, such as smartphones, tablets, and wearable devices, within close geographical proximity....
cluster management
Cluster management refers to the organization, coordination, and oversight of a group of interconnected computers or servers, known as a cluster, to ensure that they work together effectively and efficiently. The primary goal of...
clustered MEC
Clustered Multi-access Edge Computing (MEC) in the context of 5G refers to a network architecture that organizes MEC servers into clusters to optimize their performance and efficiency in delivering services. This approach is...
common public radio interface (CPRI)
CPRI, or Common Public Radio Interface, is a specification for wireless communication networks that defines the connectivity and control communications between baseband units (BBUs) and remote radio units (RRUs), also known as...
computer vision
Computer vision is a field of artificial intelligence (AI) that enables computers and systems to interpret and understand images, videos, and other visual inputs in a manner similar to human vision. It has the capability to...
concept drift
In machine learning, concept drift is when the data a machine learning model used to learn has become out of sync to the real-world situation it's trying to predict. Imagine a model trained to identify fraudulent transactions;...
continuous training
Continuous training, also known as continuous machine learning (CML), is a process where a machine learning model is updated continually with new data to adapt to changes over time. Continuously training the machine learning...
contrastive learning
Contrastive learning is a type of self-supervised machine learning where the machine learns without the need for explicit labels by comparing and contrasting examples. The machine is given a set of data points, and it tries to...
convergence
Convergence (or, more formally, model convergence) refers to the point at which the parameters of a machine learning model, distributed across multiple computational nodes, stabilize and cease to change significantly with...
coordinated multipoint (CoMP)
Coordinated MultiPoint (CoMP) is a technology designed to improve the performance of cellular networks, particularly at the cell edges, where users experience poor signal quality due to interference from neighboring cells. CoMP...
CU, DU, RU (5G RAN)
A 5G Radio Access Network (RAN) is divided into three functional parts: The CU, DU and RU. This is the role that each plays: Centralized Unit (CU): The CU is responsible for the non-real-time, higher Layer 2 (L2) and Layer 3...
CUDA
CUDA, or Compute Unified Device Architecture, is a proprietary and closed-source parallel computing platform and application programming interface (API) developed by Nvidia. It was first introduced in 2006 and is designed to...
cyber-physical systems (CPS)
Cyber-physical systems (CPS) are integrations of computation, networking, and physical processes. Embedded computers and networks monitor and control the physical processes, with feedback loops where physical processes affect...

D

DALL-E
DALL-E is a series of generative AI models developed by OpenAI that create digital images from natural language descriptions, also known as prompts. The name “DALL-E” is a portmanteau of the artist Salvador Dalí and Pixar’s...
data lake
A data lake is a centralized repository designed to store, process, and secure a vast amount of data in various formats, including structured, semi-structured, and unstructured data. It allows for the storage of data in its...
data lakehouse
A data lakehouse is a modern data management architecture that merges the features of data lakes and data warehouses into a unified platform. This architecture aims to leverage the strengths of both systems to provide a...
data processing unit (DPU)
A data processing unit (DPU) is a programmable processor designed to handle data-centric tasks within data centers efficiently. It is a system on a chip (SoC) that integrates several components: A general-purpose CPU, often...
data warehouse
A data warehouse is a centralized data management system that aggregates and consolidates large amounts of data from multiple sources. Its primary purpose is to enable and support business intelligence (BI) activities,...
deep learning
Deep learning is a sophisticated subset of machine learning that employs artificial neural networks with multiple layers to simulate the way humans acquire knowledge. This approach enables machines to process data in a manner...
deep neural network (DNN)
Deep Neural Networks (DNNs) are a class of artificial neural networks that have multiple layers between the input and output layers, which enable the modeling of complex data with high levels of abstraction. DNNs are widely used...

E

edge computing
Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth. The “edge” in edge computing refers to the...
edge intelligence
Edge intelligence refers to the capability to analyze data locally at the edge network, where the data is collected, rather than sending it to the cloud for analysis. It includes various aspects like intelligent offloading from...
edge ML
Edge Machine Learning (Edge ML) refers to the deployment and execution of machine learning models at the periphery of a network, closer to the source of data or the user. Edge ML is a powerful approach that combines the...
emergence vs homogenization (in AI)
In the context of AI, “emergence” and “homogenization” represent two contrasting phenomena that have significant implications for the development and application of artificial intelligence technologies. Emergence Emergence in...
empirical risk minimization (ERM)
Empirical risk minimization (ERM) is a principle where the model is trained to minimize the average loss (empirical risk) over the training dataset. The empirical risk is calculated as the average of the loss function over all...
enhanced common public radio interface (eCPRI)
Enhanced Common Public Radio Interface (eCPRI) is a significant evolution from the traditional Common Public Radio Interface (CPRI), specifically designed to meet the demands of 5G and open virtual Radio Access Networks (vRAN)....
enhanced mobile broadband (eMBB)
Enhanced Mobile Broadband (eMBB) is a service category of 5G technology. It is one of the three main service categories defined by the International Telecommunication Union (ITU) and developed by the 3rd Generation Partnership...
eNodeB (Evolved Node B)
The term eNodeB, an abbreviation for Evolved Node B, is a fundamental component in the architecture of LTE (Long Term Evolution) networks, representing the evolution of Node B from UMTS (Universal Mobile Telecommunications...
ETSI (the European Telecommunications Standards Institute)
ETSI (European Telecommunications Standards Institute) is a non-profit organization crucial for developing technical standards within Europe's telecommunications, broadcasting, and related industries. ETSI plays a key role in...
explainable AI (XAI)
Explainable AI (XAI) addresses the need to understand the decision-making processes of AI systems. XAI provides methods and techniques to uncover the reasoning behind an AI's outputs, elucidating the relationships between...
extract, transform, load (ETL)
Extract, transform, load (ETL) is a process in data warehousing that combines data from multiple sources into a single data set that has been pre-processed with consistent business rules. The ETL process allows data from many...

F

far edge
In the context of edge computing and the internet, "far edge" refers to the infrastructure that is deployed at the outermost boundary of the network, closest to the end-users or data sources, and farthest from centralized cloud...
fault tolerant (FT)
Fault tolerance refers to the ability of a system to continue operating without interruption when one or more of its components fail. A fault-tolerant system is designed to have no service interruption, but typically comes at a...
feature
In machine learning and pattern recognition, a feature is defined as an individual measurable property or characteristic of a phenomenon being observed[1]. Features play a crucial role in the development of machine learning...
feature extraction
Feature extraction is a crucial process in machine learning and data analysis that involves identifying and extracting relevant features from raw data. These features, once extracted, are used to create a more informative...
feature space
A feature space is a conceptual environment where each dimension represents a specific feature of the data being analyzed or used in machine learning models. It’s essentially the n-dimensional space where your variables (or...
feature store
A feature store is a centralized repository designed to store, manage, and facilitate the use of features for machine learning models. Features, in machine learning, are individual measurable properties or characteristics of a...
feature vector
A feature vector is an ordered list of numerical values that represent the characteristics (or features) of an object or phenomenon. Each value in the vector corresponds to a specific feature. For example, in a dataset...
federated learning (FL)
Federated learning (FL) is a machine learning approach that allows multiple clients or devices to collaboratively train a model while keeping the data localized, thus addressing privacy, security, and data ownership concerns. It...
fine-tuning
Fine-tuning is a process in deep learning where a pre-trained model is further trained (or “fine-tuned”) on a new dataset, which may be smaller or from a different domain than the original training data. The idea is to leverage...
Fixed Wireless Access (FWA)
5G Fixed Wireless Access (FWA) is a broadband access technology that uses the 5G cellular network to provide high-speed internet connectivity to homes and businesses without the need for traditional wired connections such as...
floating point precision (FP64, FP32, and FP16)
FP64, FP32, and FP16 are different levels of precision in floating-point arithmetic, which is a method for representing real numbers in computers. The numbers 64, 32, and 16 refer to the number of bits used to store the...
foundation model
A foundation model refers to a type of machine learning model that is trained on a broad dataset, enabling it to be applied across a wide range of tasks. The term was popularized by the Stanford Institute for Human-Centered...
fronthaul
In telecom, fronthaul is the connectivity between the radio unit and the distributed unit. Or, more formally, it describes the segment of the network that connects the remote radio heads (RRHs) at cell sites to the more...

G

gated recurrent unit (GRU)
A Gated Recurrent Unit (GRU) is a simplified version of Long Short-Term Memory (LSTM) designed to solve the same problem of learning long-term dependencies in sequential data but with a more streamlined architecture. GRUs merge...
GDDR (Graphics Double Data Rate)
GDDR (Graphics Double Data Rate) Synchronous Dynamic Random-Access Memory (SDRAM) is a type of high-speed memory designed specifically for graphics processing units (GPUs). It is a specialized form of DDR (Double Data Rate)...
GDDR5 (Graphics Double Data Rate Type 5)
Graphics Double Data Rate 5 Synchronous Dynamic Random-Access Memory (GDDR5 SDRAM) is a type of synchronous graphics random-access memory (SGRAM) with a high bandwidth (“double data rate”) interface designed for use in graphics...
GDDR6 (Graphics Double Data Rate 6)
GDDR6 Dynamic Random-Access Memory is the sixth generation of GDDR SDRAM, a type of memory specifically designed for use in graphics cards, game consoles, and high-performance computing. It is the successor to GDDR5 and GDDR5X,...
GDDR7 (Graphics Double Data Rate 7)
Definition of GDDR7 Graphics Double Data Rate 7 Synchronous Dynamic Random-Access Memory (GDDR7 SDRAM) is the latest generation of synchronous graphics random-access memory (SGRAM) specified by the JEDEC Semiconductor Memory...
general-purpose graphics processing unit (GPGPU)
General-Purpose Graphics Processing Unit (GPGPU) refers to the use of a Graphics Processing Unit (GPU) to perform computations typically conducted by a Central Processing Unit (CPU). This trend of using GPUs for non-specialized...
generative adversarial Network (GAN)
A Generative Adversarial Network (GAN) is a type of machine learning model that consists of two neural networks, the generator and the discriminator, which are trained simultaneously through adversarial processes. The generator...
generative AI
Generative AI, or generative artificial intelligence, refers to a subset of AI technologies that are capable of generating new content, ideas, or data that mimic human-like creativity. This includes the creation of text, images,...
generative pre trained transformer (GPT)
GPT stands for Generative Pre-trained Transformer, which is an artificial intelligence language model developed by OpenAI. The “generative” aspect refers to the model’s ability to generate text, “pre-trained” indicates that the...
GNU Octave
GNU Octave is a high-level interpreted programming language, primarily intended for numerical computations. It provides a command line interface for solving linear and nonlinear problems numerically, and for performing other...
GPT-3, GPT-3.5, GPT-4
The main differences between GPT-3, GPT-3.5, and GPT-4 are in their capabilities, size, and the types of inputs they can process. GPT-3 GPT-3, with 175 billion parameters, was a significant leap forward in language model...
GPU cloud
A “GPU cloud” refers to the service or infrastructure that provides access to cloud-based GPU resources. It refers to the collective offering of GPU resources and related services by a cloud provider. This includes not just the...
GPU memory clock
In the context of GPUs, the memory clock, also known as memory frequency, refers to the speed at which the GPU’s memory (VRAM) operates. It is measured in megahertz (MHz) or gigahertz (GHz) and indicates how many times per...
GPU-accelerated RAN
Their parallel architecture of GPUs makes them suitable for the computational demands of modern Radio Access Networks (RANs), particularly with the advent of 5G, which requires significant signal processing and AI/ML workloads...
gradient
In the context of neural networks, a gradient is a vector that represents the direction and rate of the fastest increase of a function. More specifically, it is the collection of partial derivatives of a function with respect to...
gradient descent
Gradient descent is an optimization algorithm used to minimize some function by iteratively moving in the direction of steepest decrease, as defined by the negative of the gradient. In the context of machine learning, this...
graphics processing unit (GPU)
A GPU, or Graphics Processing Unit, is a processor designed for high-speed image rendering and parallel data computation. They are very efficient at processing large blocks of data in parallel, which makes them superior to...

H

high availability (HA)
High availability refers to the ability of a system to operate continuously without failing for a designated period of time. It is designed to ensure that the system meets an agreed-upon operational performance level, often...
high performance computing (HPC)
High Performance Computing (HPC) refers to the practice of aggregating computing power to achieve much higher performance than what a typical desktop computer or workstation can provide. This is done in order to solve large,...
human-in-the-loop (HITL)
Human-in-the-Loop (HITL) refers to systems or processes where human intervention is integral to the operation and success of the system. In the context of machine learning and artificial intelligence, HITL involves humans...
human-scale time
Human-scale time refers to the range of time that is directly perceptible and relevant to human beings in their daily lives. It encompasses the durations over which we can maintain attention, the time it takes to perform tasks,...
hybrid intelligence
Hybrid intelligence refers to a system that combines elements of both artificial intelligence (AI) and human intelligence. It is designed to bridge the gap between the strengths and weaknesses of both types of intelligence,...
hyperconnectivity
Hyperconnectivity is a term that describes the high-tech communications of the 21st century, primarily facilitated by the internet. It encompasses various forms of communication such as radio, TV, phone and video calls, texting,...

I

Industrial Internet of Things (IIoT)
The Industrial Internet of Things (IIoT) refers to the application of the Internet of Things (IoT) principles in industrial settings. It involves the use of smart sensors, actuators, and other devices networked together to...
industry 4.0
Industry 4.0 represents the fourth industrial revolution, characterized by the integration of smart technologies like the Internet of Things (IoT), cyber-physical systems, artificial intelligence (AI), and cloud computing into...
inferencing
Inferencing in AI is where the trained model is used to make predictions or decisions on new, unseen data. It is the application of the learned model to real-world tasks, such as classifying images, recognizing speech, or...
InfiniBand
InfiniBand is a high-performance, channel-based communication protocol used to interconnect servers, storage systems, and other data center infrastructure. It is known for its high throughput and low latency, making it an ideal...
integrated sensing and communications (ISAC)
Integrated Sensing and Communications (ISAC) uses radio signals to simultaneously convey communication data and provide sensing information about the environment. ISAC systems can utilize the radio signals transmitted and...
intelligent application
An intelligent application is a software application that incorporates artificial intelligence (AI) technologies such as machine learning, natural language processing, and data analytics to improve functionality, user...
internet of medical things (IoMT)
The Internet of Medical Things (IoMT) is a network of interconnected medical devices, applications, and infrastructure that collect and transmit medical data. It’s a subset of the broader Internet of Things (IoT) concept, but...
internet of things (IoT)
The Internet of Things (IoT) is a concept that describes the network of physical objects, or “things,” that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other...
IPv4
Internet Protocol version 4 (IPv4) is the fourth iteration of the Internet Protocol (IP), which is a set of rules that govern the format of data sent over the internet or other networks. IPv4 is responsible for identifying...
IPv6
Internet Protocol version 6 (IPv6) is the most recent version of the Internet Protocol (IP), which is the communications protocol that provides an identification and location system for computers on networks and routes traffic...
IT (Information Technology) vs. OT (Operational Technology)
Information Technology (IT) and Operational Technology (OT) are two distinct areas within an organization that serve different purposes. IT is primarily concerned with the management of data, including its storage, retrieval,...
IT/OT convergence
IT/OT convergence refers to the integration of IT systems with OT systems. This integration aims to enable data and control flow between the traditionally separate domains of IT and OT. The convergence is driven by the need for...

J

Jevons Paradox
The Jevons Paradox, named after the English economist William Stanley Jevons, is an economic theory that suggests improvements in efficiency for using a resource can lead to an overall increase in the consumption of that...

K

kubernetes (K8S)
Kubernetes, commonly abbreviated as K8s, is an open-source platform designed to automate deploying, scaling, and operating application containers. It was originally developed by Google and is now maintained by the Cloud Native...

L

large language model (LLM)
Large Language Models (LLMs) are advanced deep learning models that have been pre-trained on extensive datasets to understand and generate human language. These models, such as OpenAI’s GPT-3, are based on transformer...
large vision model (LVM)
Large Vision Models (LVMs) are a class of artificial intelligence models that are designed to understand and interpret visual information. They are analogous to Large Language Models (LLMs) but are focused on the visual domain...
layer 2 networking (L2)
Based on the search results, layer 2 refers to the data link layer in the OSI and TCP/IP network models. Layer 2 handles local data transfer over the physical medium while layer 3 handles global routing. Understanding what...
layer 3 networking (L3)
Layer 3 in networking, also known as the Network Layer, is a crucial component of both the OSI (Open Systems Interconnection) and TCP/IP (Transmission Control Protocol/Internet Protocol) models. It plays a pivotal role in...
LF Edge
LF Edge, or Linux Foundation Edge, is an umbrella organization under the Linux Foundation that aims to create an open, interoperable framework for edge computing that is independent of hardware, silicon, cloud, or operating...
LLaMa (Large Language Model Meta AI)
Meta’s LLaMA (Large Language Model Meta AI) is a family of autoregressive large language models developed by Meta. The first version of LLaMA, released in February 2023, included models with 7, 13, 33, and 65 billion parameters....
long short-term memory network (LSTM)
Long Short-Term Memory networks, commonly known as LSTMs, are a special kind of Recurrent Neural Network (RNN) capable of learning long-term dependencies. They were introduced to overcome the limitations of traditional RNNs,...
loss function
A loss function (or cost function) measures the difference between the predicted and actual output of an AI model. The loss function outputs a higher number when the predictions are poor and a lower number when they are more...
LTE-M (Long Term Evolution Machine Type Communication)
LTE-M, short for Long Term Evolution Machine Type Communication, is a low-power wide-area network (LPWAN) technology that is part of the 4G cellular network and is specifically designed for the Internet of Things (IoT). It...

M

MAC address
A Media Access Control (MAC) address is a unique identifier assigned to a network interface controller (NIC) for use as a network address in communications within a network segment. This identifier is used for making...
machine learing operations (MLOps)
Machine learning operations (MLOps) is a set of practices and tools that aim to streamline and automate the deployment, monitoring, and management of machine learning models in production. MLOps combines elements of software...
machine learning (ML)
Machine learning (ML) is a field of artificial intelligence (AI) where computer systems learn to perform tasks by analyzing data, rather than following explicitly programmed instructions. Most of today's AI systems today are...
machine-scale time
Machine-scale time refers to the time scale at which computers operate, which is significantly faster than human perception of time. For instance, a computer can process information and execute tasks in nanoseconds, a speed that...
massive machine-type communications (mMTC)
Massive machine-type communications (mMTC) is a key service area of 5G technology, designed to support the Internet of Things (IoT) by enabling the connection of a vast number of devices. mMTC focuses on connecting large numbers...
Massive MIMO (Multiple Input, Multiple Output)
Massive MIMO (Multiple-Input, Multiple-Output) are antenna devices that have many small, individually controllable antennas capable. By controlling many antennas in unison, in a process called beamforming, signals can be...
MATLAB (Matrix Laboratory)
MATLAB, short for “Matrix Laboratory,” is a proprietary programming language and numeric computing environment developed by MathWorks. It is designed specifically for engineers and scientists to analyze and design systems using...
MEC (multi-access edge computing)
MEC (Multi-access Edge Computing), is a network architecture concept that enables cloud computing capabilities and an IT service environment at the edge of the cellular network. In the context of 5G and telecommunications...
Metro Ethernet Forum (MEF)
The Metro Ethernet Forum (MEF) is a significant global industry alliance that plays a crucial role in the development, adoption, and certification of Carrier Ethernet and other network services. With over 220 member...
millimeter wave (mmWave)
Millimeter wave (mmWave), also known as the millimeter band, is a spectrum of electromagnetic frequencies that falls between microwaves and infrared waves. It encompasses frequencies from 30 GHz to 300 GHz, corresponding to...
MIMD (Multiple Instruction, Multiple Data)
MIMD (Multiple Instruction, Multiple Data) is a parallel computing architecture where multiple processors execute different instructions on different pieces of data simultaneously. This model is more flexible than Single...
misalignment, temporal and spatial
Temporal and spatial misalignment in sensor fusion refers to the challenges associated with aligning data from multiple sensors in both time and space. These misalignments can significantly impact the accuracy and effectiveness...
mobile infrastructure sharing
Infrastructure sharing among Mobile Network Operators (MNOs) is a strategic approach that allows multiple operators to utilize the same physical and network infrastructure. This practice aims to reduce the costs associated with...
Mobile Network Operator (MNO)
Mobile Network Operator (MNO) A Mobile Network Operator (MNO) is a telecommunications service provider organization that provides wireless voice and data communication services to its subscribers. An MNO owns or controls all the...
Mobile Virtual Network Enabler (MVNE)
A Mobile Virtual Network Enabler (MVNE) is a company that provides network infrastructure and related services to Mobile Virtual Network Operators (MVNOs). These services include business support systems (BSS), administration,...
Mobile Virtual Network Operator (MVNO)
A Mobile Virtual Network Operator (MVNO) is a reseller of wireless communications services. MVNOs lease wireless capacity, such as minutes or data bandwidth, from a third-party MNO at wholesale prices and resell it to consumers...
model stability
Model stability, also known as algorithmic stability, means that a model's predictions remain consistent and accurate even when facing slight variations in input data. Model stability in AI implies that a model delivers...

N

Narrowband Internet of Things (NB-IoT)
Narrowband Internet of Things (NB-IoT) is a standards-based low power wide area (LPWA) technology developed to enable a wide range of new IoT devices and services. It is designed to support massive numbers of devices over a wide...
natural language generation (NLG)
Natural Language Generation (NLG) is the branch of artificial intelligence that focuses on generating natural language text or speech from a data source. It involves the use of AI programming to transform structured data into...
natural language processing (NLP)
Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) that focuses on the interaction between computers and human language. It encompasses the development of algorithms and systems that enable computers...
natural language understanding (NLU)
Natural Language Understanding (NLU) is a branch of artificial intelligence that focuses on the comprehension of human language by machines. NLU systems are designed to understand the meaning and context of human language in a...
near edge
In the context of edge computing and the internet, "near edge" refers to the infrastructure that is deployed closer to the data source than traditional cloud data centers but not as close as the "far edge." Near edge...
near real-time
The term "near real-time" (NRT) refers to the timeliness of data or information processing that is slightly delayed by the time required for electronic communication and automatic data processing, as opposed to real-time...
near-premises
The term “near-premises” refers to a relatively new concept in the IT and telecommunications sectors, focusing on delivering IT services and infrastructure that, while not located directly on-site (as with traditional...
Near-Realtime RAN Intelligent Controller (Near-RT RIC)
A Near-Realtime RAN Intelligent Controller (Near-RT RIC) is a software-defined component within the Open Radio Access Network (Open RAN) architecture that plays a crucial role in controlling and optimizing the Radio Access...
Near-RT RIC vs Non-RT RIC
The main differences between a Near-Realtime RAN Intelligent Controller (Near-RT RIC) and a Non-Realtime RAN Intelligent Controller (Non-RT RIC) are their operational timescales, functions, and locations within the...
network delay, types of
Network processing delay, propagation delay, and transmission delay are three key components of network delay, which is the total time it takes for a bit of data to travel across a network from one communication endpoint to...
network processing delay
Network processing delay, also known as processing delay, is the time it takes for a router or a switch to process a packet's header and make a decision about where to direct the packet next. This delay is a critical component...
network propagation delay
Network propagation delay refers to the time it takes for a signal to travel from one point in a network to another. It measures the latency experienced by data packets as they travel across the network. This delay is...
network slicing
Network slicing is a form of network configuration that enables the creation of multiple virtual networks on top of a single physical network infrastructure. This technique is particularly significant in the context of 5G...
network transmission delay
Transmission delay in networking is the time it takes to push all the bits of a data packet onto the network medium. It is a function of the packet's length and the bandwidth of the network. Transmission delay is independent of...
network-as-a-service (NaaS)
Network as a Service (NaaS) is an innovative model that allows organizations to consume network infrastructure and services on a subscription basis, rather than investing in and managing physical network components themselves....
neural network
A neural network, in the context of machine learning, is a computational model designed to recognize patterns and make decisions based on input data. It is inspired by the structure and function of the human brain’s biological...
Non-Realtime RAN Intelligent Controller (Non-RT RIC)
A Non-Realtime RAN Intelligent Controller (Non-RT RIC) is a key component of the Open Radio Access Network (Open RAN) architecture, focusing on orchestration and automation functions as described by the O-RAN Alliance. Its...
NVIDIA DGX, MGX, EGX and HGZ platforms
NVIDIA’s product lines, including DGX, MGX, EGX, and HGX, cater to various aspects of computing, from AI and deep learning to modular server design and edge computing. Each of these platforms is designed with specific use cases...
NVIDIA H100, H200, GH100, GH200
NVIDIA GH100 and GH200 The terms "GH100" and "GH200" are associated with NVIDIA's integrated solutions that combine GPUs with CPUs for enhanced computing capabilities. Specifically, the "GH" prefix refers to a combination of...
NVIDIA Jetson
NVIDIA Jetson is a series of embedded computing boards that integrate a system on a chip (SoC) with NVIDIA’s GPU technology to provide accelerated AI and machine learning capabilities in a compact and energy-efficient form...
NVLink
NVLink, developed by Nvidia, is a high-speed, direct GPU-to-GPU interconnect that enhances multi-GPU communication within servers. NVLink represents a significant advancement in GPU interconnect technology, offering high...

O

observability
In the broadest sense, observability is about enhancing the visibility and understanding of systems to improve decision-making and operational efficiency. AI Observability In the context of AI, observability refers to a...
on-premises
"On-premises" is a term used to describe IT infrastructure, hardware, and software applications that are hosted on-site, within an organization's physical location, as opposed to being hosted off-site in a cloud or remote data...
one-shot learning
One-shot learning is a machine learning technique where a model can learn to recognize patterns from just one or a very few examples. It is a machine learning paradigm specifically designed to address the challenge of object...
Open RAN
Open RAN, or Open Radio Access Network, is a transformative approach in mobile network architecture that disaggregates the Radio Access Network (RAN) into its core components: Radio Units (RUs), Distributed Units (DUs), and...
Open RAN vs O-RAN
The terms “Open RAN” and “O-RAN” are often used interchangeably in discussions about the evolution of mobile networks, but they refer to slightly different concepts within the broader movement towards more open, flexible, and...
OpenCV (Open Source Computer Vision Library)
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use...
overfitting
Overfitting in the context of AI refers to a situation where a machine learning model learns the training data too well, including its noise and random fluctuations, to the extent that it negatively impacts the model’s...

P

parallel processing
Parallel processing in computing refers to the method of running two or more processors (CPUs) to handle separate parts of an overall task, allowing for the simultaneous execution of multiple calculations or data processing...
Pervasive computing
Pervasive computing, also known as ubiquitous computing, is a concept where computing is made to appear anytime and everywhere, integrating seamlessly into our daily lives. This form of computing is characterized by the...
point cloud
A point cloud is a collection of data points in space, representing a 3D object, shape, or scene. Each point in the point cloud points represents the X, Y, and Z geometric coordinates of a single point on an underlying sampled...
point cloud library (PCL)
The Point Cloud Library (PCL) is an extensive, open-source project designed for 2D/3D image and point cloud processing. It contains algorithms that facilitate tasks such as filtering, feature estimation, surface reconstruction,...
prediction
Prediction refers to the output of a machine learning model when given new, unseen data. More specifically, prediction is the process of using a trained machine learning model to estimate or forecast a target variable based on...
pretraining
Pretraining is a technique in deep learning that enables models to leverage prior knowledge for improved performance on new tasks. It refers to the process of training a neural network model on one task or dataset and then using...
PyTorch
PyTorch is an open-source machine learning (ML) framework based on the Python programming language and the Torch library. It’s primarily used for creating deep neural networks and is one of the preferred platforms for deep...

R

radio access network (RAN)
The RAN is a critical part of wireless communication systems, enabling the connection between user devices and the core network, using wireless radio waves.[1][2] The RAN consists of various elements, including radio equipment...
RAN pooling
RAN pooling refers to the concept of aggregating or centralizing the resources and functions of the Radio Access Network (RAN) to improve efficiency, flexibility, and scalability within mobile telecommunications networks. This...
real-time
In applications like autonomous vehicles or high-frequency trading systems, it is crucial to have a real-time system that can quickly process information and respond to changes or inputs. This ensures that any delays are...
recurrent neural network (RNN)
A Recurrent Neural Network (RNN) is a class of artificial neural networks where connections between nodes form a directed graph along a temporal (time-based) sequence. RNNs belong to the most promising algorithms in use because...
reinforcement learning (RL)
Reinforcement learning (RL) is a machine learning paradigm where an agent learns to make decisions by performing actions in an environment to maximize cumulative reward. It is characterized by the agent’s ability to learn...
remote radio head (RRH)
A Remote Radio Head (RRH), also known as a Remote Radio Unit (RRU), is essentially a compact, remote radio transceiver that is physically separated from the base station and is used in older 3G and 4G networks. Modern 5G...
remote radio unit (RRU)
A Remote Radio Unit (RRU), also known as a Remote Radio Head (RRH), is responsible for the transmission and reception of radio signals, connecting wireless devices to the network. The RRU performs functions such as receiving,...
Retrieval-Augmented Generation (RAG)
Retrieval-Augmented Generation (RAG) is an artificial intelligence (AI) framework that enhances the capabilities of generative AI models, particularly large language models (LLMs), by incorporating external knowledge sources...
ring-fencing
Ring-fencing refers to the practice of creating a virtual barrier around certain data assets within an organization to segregate them from the rest of the entity's data. This can be done for various reasons, such as ensuring...
robot operating system (ROS)
The Robot Operating System (ROS) is an open-source toolbox for building and operating robots. It’s not an actual operating system like Windows or macOS, but a collection of software tools and middleware that helps developers...

S

self-supervised learning (SSL)
Self-supervised learning (SSL) is a way for machines to learn by generating labels from the input data instead of using labels from people. This approach is particularly useful when dealing with large amounts of unlabeled data,...
semi-supervised learning
Semi-supervised learning is a machine learning approach that combines elements of both supervised and unsupervised learning. It involves using a small set of labeled data along with a larger set of unlabeled data to train...
sensor fusion
Sensor fusion is a process that integrates data from multiple sensors to produce a more accurate, complete, or dependable understanding of an environment or situation. This integration helps to reduce the uncertainty inherent in...
SGRAM (Synchronous Graphics Random Access Memory)
SGRAM, which stands for Synchronous Graphics Random Access Memory, is a type of DRAM specifically designed for use in graphics applications. It is synchronized with the clock speed of the CPU, allowing for efficient data...
SIMD (Single Instruction, Multiple Data)
SIMD, which stands for Single Instruction, Multiple Data, is a parallel computing architecture that allows a single instruction to be executed on multiple data points simultaneously. This is particularly useful in the context of...
smart building
A smart building is a structure that uses advanced technology to automate and optimize various building-wide systems such as heating, ventilation, and air conditioning (HVAC), lighting, alarms, and security. These systems are...
smart city
A smart city is an urban area that uses information and communication technologies (ICT) to enhance the quality and performance of urban services such as energy, transportation, and utilities to reduce resource consumption,...
smart grid
A smart grid is an electricity network that uses digital and other advanced technologies to monitor and manage the transport of electricity from all generation sources to meet the varying electricity demands of end users. It is...
smart healthcare
## Smart Healthcare Definition Smart healthcare is a health service system that leverages advanced technologies such as wearable devices, the Internet of Things (IoT), and mobile internet to dynamically access information,...
smart manufacturing
Smart manufacturing refers to the integration of advanced technologies into traditional manufacturing processes to enhance efficiency, productivity, and flexibility. It is characterized by the use of computer controls, big data...
smart retail
Smart retail refers to the integration of traditional shopping methods with modern “smart” technologies to enhance the shopping experience for customers and improve operations for retailers[1][2][6]. This involves the use of a...
smart transportation
Smart transportation refers to the integrated application of modern technologies and management strategies into transportation systems to enhance efficiency, safety, and sustainability. It involves the use of advanced...
SmartNIC
A SmartNIC, short for Smart Network Interface Card, is a programmable accelerator designed to enhance the efficiency and flexibility of data center networking, security, and storage. It achieves this by offloading a variety of...
supervised learning
Supervised learning is a machine learning approach where a model is trained using a dataset that contains input-output pairs, with the outputs being the correct answers or labels for the inputs. The goal is for the model to...

T

task offloading
Task offloading refers to the process of transferring computational tasks from a device, such as an IoT sensor or mobile device, to edge servers for execution. This is designed to improve the performance and efficiency of the...
TCP/IP
Transmission Control Protocol/Internet Protocol (TCP/IP) is the backbone of the internet, enabling different devices to communicate over vast and varied networks. Its design addresses key networking challenges such as data...
Tensor Cores
Tensor Cores are specialized processing units within NVIDIA GPUs designed to accelerate deep learning and artificial intelligence (AI) applications. They are particularly adept at performing mixed-precision matrix...
TensorFlow
TensorFlow is an open-source machine learning framework developed by Google. It is designed to facilitate the development, training, and deployment of machine learning (ML) models across a wide range of computational platforms,...
terahertz (THz) wavelengths
Terahertz (THz) wavelengths, occupying the spectrum between microwaves and infrared light, are poised to play a pivotal role in the evolution of telecommunications, particularly in the development of 6G networks. This segment of...
tokenization
In the context of Large Language Models (LLMs), a token is essentially a chunk of text that the model processes during its operations, such as reading or generating text. Tokens can vary in size and nature; they might represent...
TPU (Tensor Processing Unit)
Tensor Processing Units (TPUs) are specialized hardware accelerators designed by Google specifically for deep learning tasks. They are application-specific integrated circuits (ASICs) that excel in performing the large matrix...
training
Training is the process of teaching an AI system to recognize patterns, make decisions, and predictions based on input data. During training, the model learns from a dataset that has been carefully prepared with input-output...
transfer learning
Transfer learning is a machine learning technique where a model developed for a particular task is reused as the starting point for a model on a second task. It is an effective strategy when you have a limited amount of data for...
transformer model
A transformer model is a type of deep learning architecture that has become the foundation for many state-of-the-art natural language processing (NLP) systems. Introduced in the paper “Attention Is All You Need” by Vaswani et...
triplet
The term “triplet” refers to a specific method in machine learning for training models to recognize similarities and differences. The underlying method involves using three pieces of data at a time: an anchor, a positive example...
Triton Inference Server
Triton Inference Server is an open-source software platform designed by NVIDIA to streamline and optimize the deployment and execution of AI models across various environments and hardware configurations. It supports a wide...

U

ubiquitous computing
See: pervasive computing
Ultra-Reliable Low Latency Communications (URLLC)
Ultra-Reliable Low Latency Communications (URLLC) is a critical component of 5G technology, designed to support applications that require highly reliable data transmission and extremely low latency. Key aspects of URLLC...
underfitting
Underfitting occurs when a machine learning model is too simple to capture the underlying structure or relationships in the data it is trained on, resulting in a high error rate on both the training set and unseen data[1][2][3]....
unsupervised learning
Unsupervised learning is a machine learning technique where algorithms are used to identify patterns and structures in data that has not been labeled or classified by humans. It works without guidance, finding natural groupings,...

V

V2X (Vehicle to Everything)
Vehicle-to-Everything (V2X) communication is a transformative technology that enables vehicles to communicate with each other (V2V), with infrastructure (V2I), and with pedestrians (V2P), enhancing road safety, traffic...
vCPU (virtual Central Processing Unit)
A vCPU, or virtual Central Processing Unit, represents a share or portion of a physical CPU that is allocated to a VM. It is managed by a hypervisor, which schedules the vCPU's time on the physical CPU. The concept of vCPUs...
vector database
Vector databases store information uniquely compared to traditional databases. Instead of rows and columns, they use high-dimensional “vectors” to represent data points. Imagine each vector as a unique address in a vast,...
Vehicle-to-Cloud (V2Cloud) Cruise Assist
Vehicle-to-Cloud (V2Cloud) Cruise Assist offers several benefits that enhance the driving experience, vehicle safety, and efficiency in the context of connected vehicles and intelligent driving systems. These benefits stem from...
vGPU (virtual Graphics Processing Unit)
A vGPU, or virtual Graphics Processing Unit, is a technology that allows the power of a physical GPU to be shared across multiple virtual machines (VMs). This is achieved by installing virtual GPU software on a physical GPU in a...
virtual digital assistant (VDA)
Virtual assistants are passive listening devices that respond once they recognize a command or wake word. They must be connected to the internet to conduct web searches and communicate with other devices or services. Privacy...
Virtual Reality (VR)
Virtual Reality (VR) is a technology that creates a simulated environment distinct from the real world. This environment is computer-generated, offering a three-dimensional experience that can be both interactive and immersive....
virtualized radio access network (vRAN)
A Virtualized Radio Access Network (vRAN) is a transformative approach in telecommunications that applies virtualization principles to the Radio Access Network (RAN) components. This innovation allows telecommunications...
VM (Virtual Machine)
A virtual machine (VM) is a software emulation of a physical computer, running an operating system and applications as if it were a real computer. VMs are created and run within a host system, allowing multiple VMs to operate on...
VM profile
A VM profile or Virtual Machine profile is a comprehensive set of configurations that define how a virtual machine is set up and operates within a virtualized environment. This profile encompasses various aspects of a VM’s...
VNF (virtualized network function) vs NFC (network functions virtualization)
NFV and VNF are closely related but distinct concepts within modern network architecture. NFV provides the framework and infrastructure for virtualizing network functions, while VNFs are the virtualized implementations of these...
VRAM (Video Random Access Memory
Different Types of VRAM VRAM (Video Random Access Memory) is a critical component in graphics processing units (GPUs), serving as a dedicated memory to store image data for rendering. The evolution of VRAM technologies has been...
VXLAN (Virtual Extensible LAN)
VXLAN, which stands for Virtual Extensible Local Area Network, is a network virtualization technology designed to address the scalability problems associated with large cloud computing deployments. It operates by encapsulating...

X

xHaul
xHaul represents a comprehensive approach to managing the transport networks in 5G, encompassing fronthaul, midhaul, and backhaul. Each segment plays a distinct role within the network infrastructure to support the high...