Defense Industry Artificial Intelligence Capability Cluster

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Annotation

The process of labeling or marking data sets. In data sets used for training AI models, adding relevant labels or markers to the data can improve the accuracy o...

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Anomaly Detection

Anomaly detection is the process of identifying data points, events or observations that show significant deviations from normal data patterns. This method is u...

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Architecture

It refers to the structural design and components of artificial intelligence models. Architecture describes the layers, neurons and connections of a model.

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Artificial General Intelligence

Artificial General Intelligence (AGI) are artificial intelligence systems that can mimic the wide-ranging cognitive capabilities of human intelligence and perfo...

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Artificial Intelligence

Artificial intelligence is the ability of a computer or computer-controlled robot to perform tasks usually associated with intelligent beings.

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Artificial Neural Network

An artificial neural network is an artificial intelligence model consisting of interconnected nodes (artificial neurons) that model the information processing a...

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Augmented Reality

Augmented reality is the technology of layering digital information or objects on top of a real-world environment. This allows users to experience the real worl...

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Big Data

Big data refers to datasets generated at a size, variety and velocity that traditional data processing tools cannot handle. Its analysis can offer new insights,...

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Chatbot

A chatbot is a software application that can interact with humans through natural language, either written or spoken. Using artificial intelligence, natural lan...

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Cloud Computing

Cloud computing is a technology that provides on-demand access to computing resources (e.g. servers, storage, applications and services) over the internet. User...

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Clustering

It is a machine learning technique used to group data points with similar characteristics. It is used to understand the data set, segment it and discover patter...

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Cognitive Computing

Cognitive computing is the development of computer systems that aim to mimic human thinking processes. By modeling cognitive abilities such as learning, underst...

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Cognitive Robotics

Cognitive robotics is a field of research that aims to give robots human-like thinking, learning and problem-solving capabilities. This approach allows robots t...

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Computer Vision

Computer vision is a field of technology that enables computers to analyze images and videos and understand them in a way that the human eye can see. This proce...

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Consistency

It is the ability of an AI model to produce the same results under different data sets or conditions. Consistency indicates the model's reliability and ability ...

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Cost Function

It is a function used to evaluate and optimize the performance of a machine learning model. The cost function measures how far the model's predictions are from ...

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Cross-validation

It is a method used to evaluate the performance of a machine learning model. The dataset is divided into training and test sets to measure the generalization ab...

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Data Analytics

Data analytics is a systematic process of examining raw data in order to extract useful information from it and support decision-making processes. This process ...

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Data Mining

Data mining is the process of discovering previously unknown, interesting patterns, relationships and information from large data sets. It analyzes data and ext...

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Data Visualization

Data visualization is the process of presenting data in an understandable and interactive way using graphs, maps and other visual formats. This method allows in...

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Data Warehousing

Data warehousing is a storag A data warehouse is a centralized storage system that consolidates, stores and manages large amounts of an organization's structure...

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Deep Learning

Deep learning is the process of learning complex patterns and representations from data using multilayer artificial neural networks. This method is characterize...

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Deep Reinforcement Learning

Deep reinforcement learning is a machine learning method that combines deep learning and reinforcement learning. This approach enables AI systems to make optima...

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Dropout

It is a method used to increase the generalization ability of a deep learning model. During training, the complexity of the network is reduced by randomly deact...

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Edge Computing

Edge AI is a technology approach where data processing and artificial intelligence algorithms are executed on local devices, without the need for cloud-based da...

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Explainable AI

Explainable AI (XAI) is an approach that aims to make the decision-making processes of AI systems understandable and assessable by humans. This approach, partic...

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Feature

Refers to a characteristic or variable of a data point or observation. Features represent attributes of a data point or observation and are usually expressed in...

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Feature Extraction

The process of transforming information in data sets into meaningful features. Feature extraction helps AI models better understand and learn from data.

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Federated Learning

Federated learning is a method used to train machine learning models without sharing data across multiple devices or servers. The fundamental idea is to train m...

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Filtering

It is a process used to extract noise or redundant information from data sets. It is widely used in artificial intelligence and machine learning applications fo...

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Generative Adversarial Network

It is a model of artificial intelligence where two networks compete against each other. One network tries to generate realistic data while the other network tri...

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Genetic Algorithms

Genetic algorithms are search and optimization techniques inspired by natural selection and genetic mechanisms that aim to achieve optimal or near-optimal solut...

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Graphics Processing Unit (GPU)

A piece of hardware in a computer that is specially designed to process graphics. GPUs are used to quickly process images, render graphics and run 3D games or g...

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Hierarchical Learning

It is the process by which an artificial intelligence system learns by decomposing complex concepts into simple components. This approach can improve learning e...

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Hybrid Artificial Intelligence

It refers to an approach that combines different artificial intelligence techniques. Hybrid artificial intelligence systems aim to achieve more powerful and eff...

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Hyperparameter

They are adjustable parameters used to control the training process of a machine learning model that are not learned by the model itself. For example, values su...

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Image Recognition

Image recognition is the process by which computer systems automatically recognize and classify objects, patterns or features within images. This is accomplishe...

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Inference

The process of making predictions on data on which a model has been trained. After training, an AI model can make inferences or draw conclusions based on new in...

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Interactive Learning

A learning method where the AI model interacts with the user or external influences. The model receives feedback and continuously improves itself based on this ...

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Internet of Things

The Internet of Things (IoT) is the interconnection of physical devices, vehicles and other objects with an internet connection so that they can exchange data w...

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Iteration

The repetition of an algorithm or process. In the context of AI and machine learning, an iteration can refer to the completion of a cycle during training or opt...

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Knowledge Discovery

It is a process used to discover patterns and relationships in data sets. AI models can be used to improve decision-making by extracting useful information from...

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Large Language Model (LLM)

Large Language Models (LLM) are artificial intelligence systems that learn from large amounts of textual data and, as a result of this learning, gain the abilit...

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Localization

The process of determining the position of an object or objects in an environment. In artificial intelligence applications, it is often used in object detection...

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Logistic Regression

It is a classification algorithm. It takes the linear combination between input data and weights and passes the result to a logistic function to obtain probabil...

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Machine Learning

Machine learning is a branch of artificial intelligence used for computer systems to automatically improve and develop themselves by learning from data or exper...

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Missing Data

A situation where certain attributes or values are missing from a dataset. This can pose a significant challenge for data analysis and machine learning models a...

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Model

It is the structure that represents the results or predictions generated by a machine learning or artificial intelligence algorithm. The model contains patterns...

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Multi-labeling

The process of assigning multiple labels to an item or document. Especially used in multi-class classification problems, e.g. classifying a document into more t...

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Natural Language Generation

Natural Language Generation (NLG) is a sub-branch of artificial intelligence that enables computer systems to produce text or speech that humans can understand....

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Natural Language Processing

Natural Language Processing (NLP) is a field of artificial intelligence and linguistics used for computers to understand, interpret and process human language d...

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Neural Network

A neural network is an artificial intelligence model composed of interconnected nodes (artificial neurons) that tries to mimic the way the human brain processes...

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Object Detection

It is the process of detecting and classifying objects in an image. Object recognition algorithms are used to identify objects in an image and predict to which ...

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Object Segmentation

It is the process of determining to which object or region each pixel in an image belongs. Object segmentation is used to separate objects from other objects or...

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Object Tracking

It is the process of tracking the movement of an object within a video stream or series. Object tracking algorithms are used to determine and track the position...

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Objective Function

The objective function of an artificial intelligence model that should be optimized. This function is a metric or criterion that evaluates the performance of th...

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Optimization

The process of improving the performance or optimizing the objective function of an artificial intelligence model. This usually involves methods such as paramet...

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Optimization Algorithm

A mathematical algorithm used to maximize the performance of an AI model or to optimize a specific goal. For example, it is used to find the best parameters or ...

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Parameter Tuning

It is an optimization process used in machine learning models. Parameter tuning is used to optimize the hyperparameters of the model (e.g., learning rate, numbe...

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Predictive Maintenance

Predictive maintenance is a management strategy that anticipates maintenance needs of machinery and equipment before they fail, thus reducing unexpected downtim...

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Pyramid of Knowledge

Data is a structure that is a combination of the words Data, Information, Knowledge and Wisdom, and describes how data is valued from private to general and rea...

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RAG (Retrieval Augmented Generation)

RAG - Retrieval-Augmented Generation; is a technique for increasing the accuracy and reliability of generative artificial intelligence models with information a...

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Random Forest

It is a machine learning algorithm that uses an ensemble of decision trees. Random forests offer high accuracy and robustness because they are structured with m...

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Recommender System

A recommender system is a technology that provides personalized product, service or content recommendations based on users' past behavior, preferences and inter...

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Recurrent Neural Network

A Recurrent Neural Network (RNN) is a type of artificial neural network that can operate on time-varying data sequences by memorizing prior knowledge. This feat...

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Recursive Neural Network

Recurrent neural networks, a type of artificial neural network architecture, are used to process sequential data. Used especially in areas such as natural langu...

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Recursive Neural Networks

It is a type of artificial neural network that uses the same weights and connections when processing each element of the input. Recursive neural networks are su...

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Regression Analysis

It is a statistical analysis method used to understand the relationship between two or more variables. Regression analysis is used to determine the effect of on...

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Reinforcement Learning

Reinforcement learning is the process by which an agent learns the best actions through trial and error and feedback (rewards or punishments). This method aims ...

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Robotics

Robotics is a multidisciplinary branch of engineering and science concerned with the design, construction, operation and use of robots. In this field, mechanica...

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Self-Driving Car

A driverless vehicle is an automated vehicle that can navigate, sense its surroundings and make decisions on its own without the need for human intervention. Th...

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Self-learning

The ability of an artificial intelligence system to learn on its own without external intervention. These systems often use their experience to process data and...

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Semantic Segmentation

It is a method used in image processing. It classifies an image at the pixel level and assigns each pixel to the corresponding class. This method is used to ide...

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Sensitivity

It refers to how sensitive an AI model is to small changes in the input data. Sensitivity is important for determining the stability and reliability of the mode...

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Speech Recognition

Speech recognition is the process by which computer systems detect and transcribe human speech or understand given commands. This technology uses natural langua...

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Supervised Learning

Supervised learning is a learning method that uses labeled datasets to learn.

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Swarm Intelligence

Swarm intelligence is a form of collective behavior and intelligence that results from the interactions of a group of individuals (usually simple agents). It is...

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Template Matching

It is a method used in image processing. It is the process of finding a specific pattern or pattern in an image. This method is used in applications such as obj...

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Training Data

The data set used in training an artificial intelligence model. This data set helps the model learn a specific task and improve its ability to generalize. Train...

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Transformers

Transformers is a type of architecture used in deep learning models and has revolutionized natural language processing (NLP) tasks in particular. These models w...

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Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) are aerial vehicles that can be remotely controlled without a pilot or can perform pre-programmed tasks automatically. They are ...

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Unsupervised Learning

Unsupervised learning is a machine learning method in which computer algorithms aim to discover hidden structures or patterns in unlabeled data. In this approac...

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User Identification

It is the process by which artificial intelligence systems recognize or verify the identity of users. It is performed by analyzing user-specific features or beh...

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User Interface (UI)

An interface that allows users to interact with a software or system. In AI systems, user interfaces are designed to enable users to use the system interactivel...

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Virtual Reality

Virtual reality is a technology that immerses the user in a fully computer-generated, interactive 3D environment. This environment can mimic real world experien...

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