Generative pre-trained transformerGenerative pre-trained transformers (GPT) are a type of large language model (LLM) and a prominent framework for generative artificial intelligence. The first GPT was introduced in 2018 by OpenAI. GPT models are artificial neural networks that are based on the transformer architecture, pre-trained on large data sets of unlabelled text, and able to generate novel human-like content. As of 2023, most LLMs have these characteristics and are sometimes referred to broadly as GPTs.
Rec. 601ITU-R Recommendation BT.601, more commonly known by the abbreviations Rec. 601 or BT.601 (or its former name CCIR 601), is a standard originally issued in 1982 by the CCIR (an organization, which has since been renamed as the International Telecommunication Union - Radiocommunication sector) for encoding interlaced analog video signals in digital video form. It includes methods of encoding 525-line 60 Hz and 625-line 50 Hz signals, both with an active region covering 720 luminance samples and 360 chrominance samples per line.
User researchUser research focuses on understanding user behaviors, needs and motivations through interviews, surveys, usability evaluations and other forms of feedback methodologies. It is used to understand how people interact with products and evaluate whether design solutions meet their needs. This field of research aims at improving the user experience (UX) of products, services, or processes by incorporating experimental and observational research methods to guide the design, development, and refinement of a product.
User experience designUser experience design (UX design, UXD, UED, or XD) is the process of defining the experience a user would go through when interacting with a company, its services, and its products. Design decisions in UX design are often driven by research, data analysis, and test results rather than aesthetic preferences and opinions. Unlike user interface design, which focuses solely on the design of a computer interface, UX design encompasses all aspects of a user's perceived experience with a product or website, such as its usability, usefulness, desirability, brand perception, and overall performance.
Large language modelA large language model (LLM) is a language model characterized by its large size. Their size is enabled by AI accelerators, which are able to process vast amounts of text data, mostly scraped from the Internet. The artificial neural networks which are built can contain from tens of millions and up to billions of weights and are (pre-)trained using self-supervised learning and semi-supervised learning. Transformer architecture contributed to faster training.
Modality (human–computer interaction)In the context of human–computer interaction, a modality is the classification of a single independent channel of input/output between a computer and a human. Such channels may differ based on sensory nature (e.g., visual vs. auditory), or other significant differences in processing (e.g., text vs. image). A system is designated unimodal if it has only one modality implemented, and multimodal if it has more than one. When multiple modalities are available for some tasks or aspects of a task, the system is said to have overlapping modalities.
Artificial neural networkArtificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.
Attention (machine learning)Machine learning-based attention is a mechanism mimicking cognitive attention. It calculates "soft" weights for each word, more precisely for its embedding, in the context window. It can do it either in parallel (such as in transformers) or sequentially (such as recursive neural networks). "Soft" weights can change during each runtime, in contrast to "hard" weights, which are (pre-)trained and fine-tuned and remain frozen afterwards. Multiple attention heads are used in transformer-based large language models.
Explainable artificial intelligenceExplainable AI (XAI), also known as Interpretable AI, or Explainable Machine Learning (XML), either refers to an AI system over which it is possible for humans to retain intellectual oversight, or to the methods to achieve this. The main focus is usually on the reasoning behind the decisions or predictions made by the AI which are made more understandable and transparent. XAI counters the "black box" tendency of machine learning, where even the AI's designers cannot explain why it arrived at a specific decision.
ITU-TThe International Telecommunication Union Telecommunication Standardization Sector (ITU-T) is one of the three Sectors (branches) of the International Telecommunication Union (ITU). It is responsible for coordinating standards for telecommunications and Information Communication Technology, such as X.509 for cybersecurity, Y.3172 and Y.3173 for machine learning, and H.264/MPEG-4 AVC for video compression, between its Member States, Private Sector Members, and Academia Members.
