Generative adversarial networkA generative adversarial network (GAN) is a class of machine learning framework and a prominent framework for approaching generative AI. The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. In a GAN, two neural networks contest with each other in the form of a zero-sum game, where one agent's gain is another agent's loss. Given a training set, this technique learns to generate new data with the same statistics as the training set.
GlobalizationGlobalization, or globalisation (Commonwealth English; see spelling differences), is the process of interaction and integration among people, companies, and governments worldwide. The term globalization first appeared in the early 20th century (supplanting an earlier French term mondialization), developed its current meaning some time in the second half of the 20th century, and came into popular use in the 1990s to describe the unprecedented international connectivity of the post-Cold War world.
Human development (economics)Human development involves studies of the human condition with its core being the capability approach. The inequality adjusted Human Development Index is used as a way of measuring actual progress in human development by the United Nations. It is an alternative approach to a single focus on economic growth, and focused more on social justice, as a way of understanding progress The United Nations Development Programme defines human development as "the process of enlarging people's choices", said choices allowing them to "lead a long and healthy life, to be educated, to enjoy a decent standard of living", as well as "political freedom, other guaranteed human rights and various ingredients of self-respect".
Self-supervised learningSelf-supervised learning (SSL) is a paradigm in machine learning for processing data of lower quality, rather than improving ultimate outcomes. Self-supervised learning more closely imitates the way humans learn to classify objects. The typical SSL method is based on an artificial neural network or other model such as a decision list. The model learns in two steps. First, the task is solved based on an auxiliary or pretext classification task using pseudo-labels which help to initialize the model parameters.
Adversarial systemThe adversarial system or adversary system is a legal system used in the common law countries where two advocates represent their parties' case or position before an impartial person or group of people, usually a judge or jury, who attempt to determine the truth and pass judgment accordingly. It is in contrast to the inquisitorial system used in some civil law systems (i.e. those deriving from Roman law or the Napoleonic code) where a judge investigates the case.
Generative modelIn statistical classification, two main approaches are called the generative approach and the discriminative approach. These compute classifiers by different approaches, differing in the degree of statistical modelling. Terminology is inconsistent, but three major types can be distinguished, following : A generative model is a statistical model of the joint probability distribution on given observable variable X and target variable Y; A discriminative model is a model of the conditional probability of the target Y, given an observation x; and Classifiers computed without using a probability model are also referred to loosely as "discriminative".
Global North and Global SouthThe concept of Global North and Global South (or North–South divide in a global context) is used to describe a grouping of countries along the lines of socio-economic and political characteristics. The Global South is a term that broadly comprises countries in the regions of Africa, Latin America and the Caribbean, Asia (without Israel, Japan, and South Korea), and Oceania (without Australia and New Zealand), according to the United Nations Conference on Trade and Development (UNCTAD).
Supervised learningSupervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data on expected output values. An optimal scenario will allow for the algorithm to correctly determine output values for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way (see inductive bias).
Computer visionComputer vision tasks include methods for , , and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. Understanding in this context means the transformation of visual images (the input to the retina in the human analog) into descriptions of the world that make sense to thought processes and can elicit appropriate action.
Global studiesGlobal studies (GS) or global affaires (GA) is the interdisciplinary study of global macro-processes. Predominant subjects are political science in the form of global politics, as well as economics, law, the sociology of law, ecology, environmental studies, geography, sociology, culture, anthropology and ethnography. It distinguishes itself from the related discipline of international relations by its comparatively lesser focus on the nation state as a fundamental analytical unit, instead focusing on the broader issues relating to cultural and economic globalisation, global power structures, as well of the effect of humans on the global environment.
Feature learningIn machine learning, feature learning or representation learning is a set of techniques that allows a system to automatically discover the representations needed for feature detection or classification from raw data. This replaces manual feature engineering and allows a machine to both learn the features and use them to perform a specific task. Feature learning is motivated by the fact that machine learning tasks such as classification often require input that is mathematically and computationally convenient to process.
Global citizenshipGlobal citizenship is the idea that one's identity transcends geography or political borders and that responsibilities or rights are derived from membership in a broader class: "humanity". This does not mean that such a person denounces or waives their nationality or other, more local identities, but that such identities are given "second place" to their membership in a global community. Extended, the idea leads to questions about the state of global society in the age of globalization.
Experimental psychologyExperimental psychology refers to work done by those who apply experimental methods to psychological study and the underlying processes. Experimental psychologists employ human participants and animal subjects to study a great many topics, including (among others) sensation & perception, memory, cognition, learning, motivation, emotion; developmental processes, social psychology, and the neural substrates of all of these.
Rate of convergenceIn numerical analysis, the order of convergence and the rate of convergence of a convergent sequence are quantities that represent how quickly the sequence approaches its limit. A sequence that converges to is said to have order of convergence and rate of convergence if The rate of convergence is also called the asymptotic error constant. Note that this terminology is not standardized and some authors will use rate where this article uses order (e.g., ).
Feature (computer vision)In computer vision and , a feature is a piece of information about the content of an image; typically about whether a certain region of the image has certain properties. Features may be specific structures in the image such as points, edges or objects. Features may also be the result of a general neighborhood operation or feature detection applied to the image. Other examples of features are related to motion in image sequences, or to shapes defined in terms of curves or boundaries between different image regions.
Neural oscillationNeural oscillations, or brainwaves, are rhythmic or repetitive patterns of neural activity in the central nervous system. Neural tissue can generate oscillatory activity in many ways, driven either by mechanisms within individual neurons or by interactions between neurons. In individual neurons, oscillations can appear either as oscillations in membrane potential or as rhythmic patterns of action potentials, which then produce oscillatory activation of post-synaptic neurons.
Local area networkA local area network (LAN) is a computer network that interconnects computers within a limited area such as a residence, school, laboratory, university campus or office building. By contrast, a wide area network (WAN) not only covers a larger geographic distance, but also generally involves leased telecommunication circuits. Ethernet and Wi-Fi are the two most common technologies in use for local area networks. Historical network technologies include ARCNET, Token Ring and AppleTalk.
Problem solvingProblem solving is the process of achieving a goal by overcoming obstacles, a frequent part of most activities. Problems in need of solutions range from simple personal tasks (e.g. how to turn on an appliance) to complex issues in business and technical fields. The former is an example of simple problem solving (SPS) addressing one issue, whereas the latter is complex problem solving (CPS) with multiple interrelated obstacles.
Societal collapseSocietal collapse (also known as civilizational collapse) is the fall of a complex human society characterized by the loss of cultural identity and of social complexity as an adaptive system, the downfall of government, and the rise of violence. Possible causes of a societal collapse include natural catastrophe, war, pestilence, famine, economic collapse, population decline or overshoot, mass migration, and sabotage by rival civilizations. A collapsed society may revert to a more primitive state, be absorbed into a stronger society, or completely disappear.
Capability approachThe capability approach (also referred to as the capabilities approach) is a normative approach to human welfare that concentrates on the actual capability of persons to achieve lives they value rather than solely having a right or freedom to do so. It was conceived in the 1980s as an alternative approach to welfare economics. In this approach, Amartya Sen and Martha Nussbaum combine a range of ideas that were previously excluded from (or inadequately formulated in) traditional approaches to welfare economics.
