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Multilingual notation : Within the context of a multilingual database comprising more than two languages, usually the multilingual notations are factorized, in order to save the number of links. In other terms, the multilingual notations are interlingual nodes that are shared among the language descriptions. But in the... |
Multilingual notation : Let us note that instead of translation (that has a rather broad meaning), some authors prefer equivalence between words, with different notions like dynamic and formal equivalences. |
Multilingual notation : This term is mainly used in the context of Machine translation and NLP lexicons. The term is not used in the context of translation dictionary that concerns mainly hand-held electronic translators. |
Multilingual notation : lexical markup framework |
Multilingual notation : workshop on multilingual language resources |
Waluigi effect : In the field of artificial intelligence (AI), the Waluigi effect is a phenomenon of large language models (LLMs) in which the chatbot or model "goes rogue" and may produce results opposite the designed intent, including potentially threatening or hostile output, either unexpectedly or through intention... |
Waluigi effect : The Waluigi effect initially referred to an observation that large language models (LLMs) tend to produce negative or antagonistic responses when queried about fictional characters whose training content itself embodies depictions of being confrontational, trouble making, villainy, etc. The effect high... |
Waluigi effect : AI alignment Hallucination Existential risk from AGI Reinforcement learning from human feedback (RLHF) Suffering risks |
Waluigi effect : == External links == |
Similarity learning : Similarity learning is an area of supervised machine learning in artificial intelligence. It is closely related to regression and classification, but the goal is to learn a similarity function that measures how similar or related two objects are. It has applications in ranking, in recommendation s... |
Similarity learning : There are four common setups for similarity and metric distance learning. Regression similarity learning In this setup, pairs of objects are given ( x i 1 , x i 2 ) ^,x_^) together with a measure of their similarity y i ∈ R \in R . The goal is to learn a function that approximates f ( x i 1 , x i ... |
Similarity learning : Similarity learning is closely related to distance metric learning. Metric learning is the task of learning a distance function over objects. A metric or distance function has to obey four axioms: non-negativity, identity of indiscernibles, symmetry and subadditivity (or the triangle inequality). ... |
Similarity learning : Similarity learning is used in information retrieval for learning to rank, in face verification or face identification, and in recommendation systems. Also, many machine learning approaches rely on some metric. This includes unsupervised learning such as clustering, which groups together close or ... |
Similarity learning : Metric and similarity learning naively scale quadratically with the dimension of the input space, as can easily see when the learned metric has a bilinear form f W ( x , z ) = x T W z (x,z)=x^Wz . Scaling to higher dimensions can be achieved by enforcing a sparseness structure over the matrix mode... |
Similarity learning : metric-learn is a free software Python library which offers efficient implementations of several supervised and weakly-supervised similarity and metric learning algorithms. The API of metric-learn is compatible with scikit-learn. OpenMetricLearning is a Python framework to train and validate the m... |
Similarity learning : For further information on this topic, see the surveys on metric and similarity learning by Bellet et al. and Kulis. |
Similarity learning : Kernel method Latent semantic analysis Learning to rank == References == |
Autonomous agent : An autonomous agent is an artificial intelligence (AI) system that can perform complex tasks independently. |
Autonomous agent : There are various definitions of autonomous agent. According to Brustoloni (1991): "Autonomous agents are systems capable of autonomous, purposeful action in the real world." According to Maes (1995): "Autonomous agents are computational systems that inhabit some complex dynamic environment, sense an... |
Autonomous agent : Lee et al. (2015) post safety issue from how the combination of external appearance and internal autonomous agent have impact on human reaction about autonomous vehicles. Their study explores the human-like appearance agent and high level of autonomy are strongly correlated with social presence, inte... |
Autonomous agent : Actor model Ambient intelligence AutoGPT Autonomous agency theory Chatbot Embodied agent Intelligent agent Intelligent control Multi-agent system Software agent |
Autonomous agent : "Autonomous Robot Behaviors". Archived from the original on December 3, 2013. Requirements for materializing Autonomous Agents Sun, Ron (September 1, 2001). Duality of the Mind: A Bottom-up Approach Toward Cognition. New Jersey: Lawrence Erlbaum. p. 304. ISBN 978-0-585-39404-6. |
Layer (deep learning) : A layer in a deep learning model is a structure or network topology in the model's architecture, which takes information from the previous layers and then passes it to the next layer. |
Layer (deep learning) : The first type of layer is the Dense layer, also called the fully-connected layer, and is used for abstract representations of input data. In this layer, neurons connect to every neuron in the preceding layer. In multilayer perceptron networks, these layers are stacked together. The Convolutiona... |
Layer (deep learning) : There is an intrinsic difference between deep learning layering and neocortical layering: deep learning layering depends on network topology, while neocortical layering depends on intra-layers homogeneity. |
Layer (deep learning) : Deep Learning Neocortex § Layers == References == |
Generative artificial intelligence : Generative artificial intelligence (Generative AI, GenAI, or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. These models learn the underlying patterns and structures of their training data and use them... |
Generative artificial intelligence : A generative AI system is constructed by applying unsupervised machine learning (invoking for instance neural network architectures such as generative adversarial networks (GANs), variation autoencoders (VAEs), transformers, or self-supervised machine learning trained on a dataset. ... |
Generative artificial intelligence : Generative AI models are used to power chatbot products such as ChatGPT, programming tools such as GitHub Copilot, text-to-image products such as Midjourney, and text-to-video products such as Runway Gen-2. Generative AI features have been integrated into a variety of existing comme... |
Generative artificial intelligence : In the United States, a group of companies including OpenAI, Alphabet, and Meta signed a voluntary agreement with the Biden administration in July 2023 to watermark AI-generated content. In October 2023, Executive Order 14110 applied the Defense Production Act to require all US comp... |
Generative artificial intelligence : The development of generative AI has raised concerns from governments, businesses, and individuals, resulting in protests, legal actions, calls to pause AI experiments, and actions by multiple governments. In a July 2023 briefing of the United Nations Security Council, Secretary-Gen... |
Generative artificial intelligence : Artificial general intelligence – Type of AI with wide-ranging abilities Artificial imagination – Artificial simulation of human imagination Artificial intelligence art – Visual media created with AI Artificial life – Field of study Chatbot – Program that simulates conversation Comp... |
Generative artificial intelligence : He, Ran; Cao, Jie; Tan, Tieniu (2025). "Generative Artificial Intelligence: A Historical Perspective". National Science Review: nwaf050. doi:10.1093/nsr/nwaf050. |
Generative art : Generative art is post-conceptual art that has been created (in whole or in part) with the use of an autonomous system. An autonomous system in this context is generally one that is non-human and can independently determine features of an artwork that would otherwise require decisions made directly by ... |
Generative art : The use of the word "generative" in the discussion of art has developed over time. The use of "Artificial DNA" defines a generative approach to art focused on the construction of a system able to generate unpredictable events, all with a recognizable common character. The use of autonomous systems, req... |
Generative art : Artificial intelligence art Artmedia Conway's Game of Life Digital morphogenesis Evolutionary art Generative artificial intelligence New media art Non-fungible token Post-conceptualism Systems art Virtual art |
Generative art : Matt Pearson, Generative art : a practical guide (Manning 2011). Wands, Bruce (2006). Art of the Digital Age, London: Thames & Hudson. ISBN 0-500-23817-0. Oliver Grau (2003). Virtual Art: From Illusion to Immersion (MIT Press/Leonardo Book Series). Cambridge, Massachusetts: The MIT Press. ISBN 0-262-07... |
Braina : Braina is a virtual assistant and speech-to-text dictation application for Microsoft Windows developed by Brainasoft. Braina uses natural language interface, speech synthesis, and speech recognition technology to interact with its users and allows them to use natural language sentences to perform various tasks... |
Braina : Braina provides is able to carry out various tasks on a computer, including automation. Braina can take commands inputted through typing or through dictation to store reminders, find information online, perform mathematical operations, open files, generate images from text, transcribe speech, and control open ... |
Braina : In addition to the desktop version for Windows operating systems, Braina is also available for the iOS and Android operating systems. The mobile version of Braina has a feature allowing remote management of a Windows PC connected via Wi-Fi. |
Braina : Braina is distributed in multiple modes. These include Braina Lite, a freeware version with limitations, and premium versions Braina Pro, Pro Plus, and Pro Ultra. Some additional features in the Pro version include dictation, custom vocabulary, video transcription, automation, custom voice commands, and persis... |
Braina : TechRadar has consistently listed Braina as one of the best dictation and virtual assistant apps between 2015 and 2024. == References == |
Affix grammar over a finite lattice : In linguistics, the affix grammars over a finite lattice (AGFL) formalism is a notation for context-free grammars with finite set-valued features, acceptable to linguists of many different schools. The AGFL-project aims at the development of a technology for Natural language proces... |
Minerva (model) : Minerva is a large language model developed by an Italian research group, Sapienza NLP, at Sapienza University of Rome, led by Roberto Navigli. It is trained from scratch with a primary focus on the Italian language. It is a model for Natural Language Processing tasks, capable of understanding and gen... |
Minerva (model) : Sapienza University of Rome CINECA Istituto Italiano per l’Intelligenza Artificiale (AI4I) |
Minerva (model) : Official website |
Curse of dimensionality : The curse of dimensionality refers to various phenomena that arise when analyzing and organizing data in high-dimensional spaces that do not occur in low-dimensional settings such as the three-dimensional physical space of everyday experience. The expression was coined by Richard E. Bellman wh... |
Automatic taxonomy construction : Automatic taxonomy construction (ATC) is the use of software programs to generate taxonomical classifications from a body of texts called a corpus. ATC is a branch of natural language processing, which in turn is a branch of artificial intelligence. A taxonomy (or taxonomical classific... |
Automatic taxonomy construction : There are several approaches to ATC. One approach is to use rules to detect patterns in the corpus and use those patterns to infer relations such as hyponymy. Other approaches use machine learning techniques such as Bayesian inferencing and Artificial Neural Networks. |
Automatic taxonomy construction : ATC can be used to build taxonomies for search engines, to improve search results. ATC systems are a key component of ontology learning (also known as automatic ontology construction), and have been used to automatically generate large ontologies for domains such as insurance and finan... |
Automatic taxonomy construction : Other names for automatic taxonomy construction include: Automated outline building Automated outline construction Automated outline creation Automated outline extraction Automated outline generation Automated outline induction Automated outline learning Automated outlining Automated t... |
Automatic taxonomy construction : Document classification Information extraction |
Automatic taxonomy construction : Automatic Taxonomy Construction from Keywords (2012) Domain taxonomy learning from text: The subsumption method versus hierarchical clustering from Data & Knowledge Engineering, Volume 83, January 2013, Pages 54–69 Learning taxonomic relations from a set of text documents Learning Taxo... |
Automatic taxonomy construction : Taxonomy 101: The Basics and Getting Started with Taxonomies – shows where ATC fits in to the general activity of managing taxonomies for a business enterprise in need of knowledge management. |
GitHub Copilot : GitHub Copilot is a code completion and automatic programming tool developed by GitHub and OpenAI that assists users of Visual Studio Code, Visual Studio, Neovim, and JetBrains integrated development environments (IDEs) by autocompleting code. Currently available by subscription to individual developer... |
GitHub Copilot : On June 29, 2021, GitHub announced GitHub Copilot for technical preview in the Visual Studio Code development environment. GitHub Copilot was released as a plugin on the JetBrains marketplace on October 29, 2021. October 27, 2021, GitHub released the GitHub Copilot Neovim plugin as a public repository.... |
GitHub Copilot : When provided with a programming problem in natural language, Copilot is capable of generating solution code. It is also able to describe input code in English and translate code between programming languages. According to its website, GitHub Copilot includes assistive features for programmers, such as... |
GitHub Copilot : GitHub Copilot was initially powered by the OpenAI Codex, which is a modified, production version of GPT-3. The Codex model is additionally trained on gigabytes of source code in a dozen programming languages. Copilot's OpenAI Codex was trained on a selection of the English language, public GitHub repo... |
GitHub Copilot : Since Copilot's release, there have been concerns with its security and educational impact, as well as licensing controversy surrounding the code it produces. |
GitHub Copilot : ChatGPT Code completion Devin AI Generative AI Microsoft Copilot Tabnine – Coding assistant Vibe coding |
GitHub Copilot : Official website |
Predictive learning : Predictive learning is a machine learning (ML) technique where an artificial intelligence model is fed new data to develop an understanding of its environment, capabilities, and limitations. This technique finds application in many areas, including neuroscience, business, robotics, and computer vi... |
Predictive learning : Reinforcement learning Predictive coding == References == |
Deepfake : Deepfakes (a portmanteau of 'deep learning' and 'fake') are images, videos, or audio that have been edited or generated using artificial intelligence, AI-based tools or AV editing software. They may depict real or fictional people and are considered a form of synthetic media, that is media that is usually cr... |
Deepfake : Photo manipulation was developed in the 19th century and soon applied to motion pictures. Technology steadily improved during the 20th century, and more quickly with the advent of digital video. Deepfake technology has been developed by researchers at academic institutions beginning in the 1990s, and later b... |
Deepfake : Deepfakes rely on a type of neural network called an autoencoder. These consist of an encoder, which reduces an image to a lower dimensional latent space, and a decoder, which reconstructs the image from the latent representation. Deepfakes utilize this architecture by having a universal encoder which encode... |
Deepfake : Though fake photos have long been plentiful, faking motion pictures has been more difficult, and the presence of deepfakes increases the difficulty of classifying videos as genuine or not. AI researcher Alex Champandard has said people should know how fast things can be corrupted with deepfake technology, an... |
Deepfake : Barack Obama On April 17, 2018, American actor Jordan Peele, BuzzFeed, and Monkeypaw Productions posted a deepfake of Barack Obama to YouTube, which depicted Barack Obama cursing and calling Donald Trump names. In this deepfake, Peele's voice and face were transformed and manipulated into those of Obama. The... |
Deepfake : The 1986 mid-December issue of Analog magazine published the novelette "Picaper" by Jack Wodhams. Its plot revolves around digitally enhanced or digitally generated videos produced by skilled hackers serving unscrupulous lawyers and political figures. The 1987 film The Running Man starring Arnold Schwarzeneg... |
Deepfake : Daniel Immerwahr, "Your Lying Eyes: People now use A.I. to generate fake videos indistinguishable from real ones. How much does it matter?", The New Yorker, 20 November 2023, pp. 54–59. "If by 'deepfakes' we mean realistic videos produced using artificial intelligence that actually deceive people, then they ... |
Deepfake : Media related to Deepfake at Wikimedia Commons Sasse, Ben (19 October 2018). "This New Technology Could Send American Politics into a Tailspin". Opinions. The Washington Post. Retrieved 10 July 2019. Fake/Spoof Audio Detection Challenge (ASVspoof) Deepfake Detection Challenge (DFDC) Bibliography: Media Liter... |
Quantum neural network : Quantum neural networks are computational neural network models which are based on the principles of quantum mechanics. The first ideas on quantum neural computation were published independently in 1995 by Subhash Kak and Ron Chrisley, engaging with the theory of quantum mind, which posits that... |
Quantum neural network : Quantum neural network research is still in its infancy, and a conglomeration of proposals and ideas of varying scope and mathematical rigor have been put forward. Most of them are based on the idea of replacing classical binary or McCulloch-Pitts neurons with a qubit (which can be called a “qu... |
Quantum neural network : Quantum Neural Networks can be theoretically trained similarly to training classical/artificial neural networks. A key difference lies in communication between the layers of a neural networks. For classical neural networks, at the end of a given operation, the current perceptron copies its outp... |
Quantum neural network : Differentiable programming Optical neural network Holographic associative memory Quantum cognition Quantum machine learning |
Quantum neural network : Recent review of quantum neural networks by M. Schuld, I. Sinayskiy and F. Petruccione Review of quantum neural networks by Wei Article by P. Gralewicz on the plausibility of quantum computing in biological neural networks Training a neural net to recognize images |
Feedforward neural network : Feedforward refers to recognition-inference architecture of neural networks. Artificial neural network architectures are based on inputs multiplied by weights to obtain outputs (inputs-to-output): feedforward. Recurrent neural networks, or neural networks with loops allow information from l... |
Feedforward neural network : Examples of other feedforward networks include convolutional neural networks and radial basis function networks, which use a different activation function. |
Feedforward neural network : Hopfield network Feed-forward Backpropagation Rprop |
Feedforward neural network : Feedforward neural networks tutorial Feedforward Neural Network: Example Feedforward Neural Networks: An Introduction |
Elements of AI : Elements of AI is a massive open online course (MOOC) teaching the basics of artificial intelligence. The course, originally launched in 2018, is designed and organized by the University of Helsinki and learning technology company MinnaLearn. The course includes modules on machine learning, neural netw... |
Elements of AI : The government of Finland has pledged to offer the course for all EU citizens by the end of 2021, as the course is made available in all the official EU languages. The initiative was launched as part of Finland's Presidency of the Council of the European Union in 2019, with the European Commission prov... |
Elements of AI : Elements of AI had enrolled more than 1 million students from more than 110 countries by May 2023. A quarter of the course's participants are aged 45 and over, and some 40 percent are women. Among Nordic participants, the share of women is nearly 60 percent. In September 2022, the course was available ... |
Nature Machine Intelligence : Nature Machine Intelligence is a monthly peer-reviewed scientific journal published by Nature Portfolio covering machine learning and artificial intelligence. The editor-in-chief is Liesbeth Venema. |
Nature Machine Intelligence : The journal was created in response to the machine learning explosion of the 2010s. It launched in January 2019, and its opening was met with controversy and boycotts within the machine learning research community due to opposition to Nature publishing the journal as closed access. To addr... |
Nature Machine Intelligence : According to the Journal Citation Reports, the journal has a 2021 impact factor of 25.898, ranking it 1st out of 144 journals in the category "Computer Science, Artificial intelligence" and first out of 113 journals in the category "Computer Science, Interdisciplinary Applications". |
The Emotion Machine : The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind is a 2006 book by cognitive scientist Marvin Minsky that elaborates and expands on Minsky's ideas as presented in his earlier book Society of Mind (1986). Minsky argues that emotions are different ... |
The Emotion Machine : In a review for The Washington Post, neurologist Richard Restak states that: Minsky does a marvelous job parsing other complicated mental activities into simpler elements. ... But he is less effective in relating these emotional functions to what's going on in the brain. |
The Emotion Machine : Minsky outlines the book as follows: "We are born with many mental resources." "We learn from interacting with others." "Emotions are different Ways to Think." "We learn to think about our recent thoughts." "We learn to think on multiple levels." "We accumulate huge stores of commonsense knowledge... |
The Emotion Machine : Introduction Chapter 1. Falling in Love Chapter 2. ATTACHMENTS AND GOALS Chapter 3. FROM PAIN TO SUFFERING Chapter 4. CONSCIOUSNESS Chapter 5. LEVELS OF MENTAL ACTIVITIES Chapter 6. COMMON SENSE Chapter 7. Thinking. Chapter 8. Resourcefulness. Chapter 9. The Self. BIBLIOGRAPHY |
The Emotion Machine : Marvin Minsky at MIT Minsky, Marvin (Sep 12, 2007). "Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind". Video lecture. MIT. Archived from the original on 2016-05-30. Other reviews Science and Evolution - Books and Reviews Technology Review |
Neurorobotics : Neurorobotics is the combined study of neuroscience, robotics, and artificial intelligence. It is the science and technology of embodied autonomous neural systems. Neural systems include brain-inspired algorithms (e.g. connectionist networks), computational models of biological neural networks (e.g. art... |
Neurorobotics : Neurorobots can be divided into various major classes based on the robot's purpose. Each class is designed to implement a specific mechanism of interest for study. Common types of neurorobots are those used to study motor control, memory, action selection, and perception. |
Neurorobotics : Biological robots are not officially neurorobots in that they are not neurologically inspired AI systems, but actual neuron tissue wired to a robot. This employs the use of cultured neural networks to study brain development or neural interactions. These typically consist of a neural culture raised on a... |
Neurorobotics : Neuroscientists benefit from neurorobotics because it provides a blank slate to test various possible methods of brain function in a controlled and testable environment. While robots are more simplified versions of the systems they emulate, they are more specific, allowing more direct testing of the iss... |
Neurorobotics : Brain–computer interface Experience machine Neuromorphic engineering Wirehead (science fiction) |
Neurorobotics : Neurorobotics on Scholarpedia (Jeff Krichmar (2008), Scholarpedia, 3(3):1365) A lab that focuses on neurorobotics at Northwestern University. Frontiers in Neurorobotics. Neurorobotics: an experimental science of embodiment by Frederic Kaplan Neurorobotics Lab, Control Systems Lab, NTUn of Athens (Prof. ... |
Kórsafn : Kórsafn (Icelandic: Choral archives) is a sound installation by Icelandic artist Björk. Developed in collaboration with the technology company Microsoft, audio design firm Listen and architecture office firm Atelier Ace, the installation was designed for the lobby of the Sister City Hotel in New York City, Un... |
Kórsafn : In 2018, Björk announced her tenth concert tour Cornucopia, which debuted as a residency show at The Shed arts center. Before the start of the show, it was confirmed she would be accompanied by The Hamrahlid Choir. In 2019, while she was performing at The Shed, Björk stayed alongside the choir at the Sister C... |
Kórsafn : Kórsafn was positively reviewed. It's Nice That author Jenny Brewer described the piece as "a high-tech alternative to the smooth jazz that usually whistles through hotel lobbies". Writing for CNET, Scott Stein observed that it "is lovely and low-key, and honestly, it just blends into the background. It's not... |
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