text stringlengths 12 14.7k |
|---|
Self-supervised learning : Balestriero, Randall; Ibrahim, Mark; Sobal, Vlad; Morcos, Ari; Shekhar, Shashank; Goldstein, Tom; Bordes, Florian; Bardes, Adrien; Mialon, Gregoire; Tian, Yuandong; Schwarzschild, Avi; Wilson, Andrew Gordon; Geiping, Jonas; Garrido, Quentin; Fernandez, Pierre (24 April 2023). "A Cookbook of S... |
Self-supervised learning : Doersch, Carl; Zisserman, Andrew (October 2017). "Multi-task Self-Supervised Visual Learning". 2017 IEEE International Conference on Computer Vision (ICCV). pp. 2070–2079. arXiv:1708.07860. doi:10.1109/ICCV.2017.226. ISBN 978-1-5386-1032-9. S2CID 473729. Doersch, Carl; Gupta, Abhinav; Efros, ... |
Whisper (speech recognition system) : Whisper is a machine learning model for speech recognition and transcription, created by OpenAI and first released as open-source software in September 2022. It is capable of transcribing speech in English and several other languages, and is also capable of translating several non-... |
Whisper (speech recognition system) : Speech recognition has had a long history in research; the first approaches made use of statistical methods, such as dynamic time warping, and later hidden Markov models. At around the 2010s, deep neural network approaches became more common for speech recognition models, which wer... |
Whisper (speech recognition system) : The Whisper architecture is based on an encoder-decoder transformer. Input audio is resampled to 16,000 Hz and converting to an 80-channel log-magnitude Mel spectrogram using 25 ms windows with a 10 ms stride. The spectrogram is then normalized to a [-1, 1] range with near-zero mea... |
Whisper (speech recognition system) : The training dataset consists of 680,000 hours of labeled audio-transcript pairs sourced from the internet. This includes 117,000 hours in 96 non-English languages and 125,000 hours of X→English translation data, where X stands for any non-English language. Preprocessing involved s... |
Whisper (speech recognition system) : Whisper has been trained using semi-supervised learning on 680,000 hours of multilingual and multitask data, of which about one-fifth (117,000 hours) were non-English audio data. After training, it was fine-tuned to suppress the prediction of speaker names. It was trained by AdamW ... |
Whisper (speech recognition system) : Whisper does not outperform models which specialize in the LibriSpeech dataset, although when tested across many datasets, it is more robust and makes 50% fewer errors than other models. Whisper has a differing error rate with respect to transcribing different languages, with a hig... |
Whisper (speech recognition system) : The model has been used as the base for many applications, such as a unified model for speech recognition and more general sound recognition. |
Whisper (speech recognition system) : Transcription software List of speech recognition software Speech recognition software for Linux AI boom Neural machine translation aTrain: Open Source GUI for Whisper (local) == References == |
Percept (artificial intelligence) : A percept is the input that an intelligent agent is perceiving at any given moment. It is essentially the same concept as a percept in psychology, except that it is being perceived not by the brain but by the agent. A percept is detected by a sensor, often a camera, processed accordi... |
Percept (artificial intelligence) : Examples of percepts include inputs from touch sensors, cameras, infrared sensors, sonar, microphones, mice, and keyboards. A percept can also be a higher-level feature of the data, such as lines, depth, objects, faces, or gestures. |
Percept (artificial intelligence) : Machine perception == References == |
AIOps : AIOps (Artificial Intelligence for IT Operations) refers to the use of artificial intelligence, machine learning, and big data analytics to automate and enhance data center management. It helps organizations manage complex IT environments by detecting, diagnosing, and resolving issues more efficiently than trad... |
AIOps : AIOPs was first defined by Gartner in 2016, combining "artificial intelligence" and "IT operations" to describe the application of AI and machine learning to enhance IT operations. This concept was introduced to address the increasing complexity and data volume in IT environments, aiming to automate processes s... |
AIOps : AIOps refers to the multi-layered complex technology platforms which enhance and automate IT operations by using machine learning and analytics to analyze the large amounts of data collected from various DevOps devices and tools, automatically identifying and responding to issues in real-time. AIOps is used as ... |
AIOps : AIOps consists of a number of components including the following processes and techniques: Anomaly Detection Log Analysis Root Cause Analysis Cohort Analysis Event Correlation Predictive Analytics Hardware Failure Prediction Automated Remediation Performance Prediction Incident Management Causality Determinatio... |
AIOps : AI optimizes IT operations in five ways: First, intelligent monitoring powered by AI helps identify potential issues before they cause outages, improving metrics like Mean Time to Detect (MTTD) by 15-20%. Second, performance data analysis and insights enable quick decision-making by ingesting and analyzing larg... |
AIOps : AIOps tools use big data analytics, machine learning algorithms, and predictive analytics to detect anomalies, correlate events, and provide proactive insights. This automation reduces the burden on IT teams, allowing them to focus on strategic tasks rather than routine operational issues. AIOps is widely used ... |
AIOps : There are several conferences that are specific to AIOps: AIOps Summit AI Dev Summit IBM Think conference == References == |
ChaSen : ChaSen is a morphological parser for the Japanese language. This tool for analyzing morphemes was developed at the Matsumoto laboratory, Nara Institute of Science and Technology. |
ChaSen : ChaSen home page Nara Institute of Science and Technology Matsumoto Laboratory |
Mountain car problem : Mountain Car, a standard testing domain in Reinforcement learning, is a problem in which an under-powered car must drive up a steep hill. Since gravity is stronger than the car's engine, even at full throttle, the car cannot simply accelerate up the steep slope. The car is situated in a valley an... |
Mountain car problem : The mountain car problem, although fairly simple, is commonly applied because it requires a reinforcement learning agent to learn on two continuous variables: position and velocity. For any given state (position and velocity) of the car, the agent is given the possibility of driving left, driving... |
Mountain car problem : The mountain car problem appeared first in Andrew Moore's PhD thesis (1990). It was later more strictly defined in Singh and Sutton's reinforcement learning paper with eligibility traces. The problem became more widely studied when Sutton and Barto added it to their book Reinforcement Learning: A... |
Mountain car problem : Q-learning and similar techniques for mapping discrete states to discrete actions need to be extended to be able to deal with the continuous state space of the problem. Approaches often fall into one of two categories, state space discretization or function approximation. |
Mountain car problem : The mountain car problem has undergone many iterations. This section focuses on the standard well-defined version from Sutton (2008). |
Mountain car problem : There are many versions of the mountain car which deviate in different ways from the standard model. Variables that vary include but are not limited to changing the constants (gravity and steepness) of the problem so specific tuning for specific policies become irrelevant and altering the reward ... |
Mountain car problem : C++ Mountain Car Software. Richard s. Sutton. Java Mountain Car with support for RL Glue Python, with good discussion (blog post - down page) |
Mountain car problem : Sutton, Richard S. (1996). Mountain Car with Sparse Coarse Coding. Advances in Neural Information Processing Systems. MIT Press. pp. 1038–1044. CiteSeerx: 10.1.1.51.4764. Mountain Car with Replacing Eligibility Traces "More discussion on Continuous State Spaces". 2000. pp. 903–910. CiteSeerX 10.1... |
Vision-language-action model : A vision-language-action model (VLA) is a foundation model that allows control of robot actions through vision and language commands. One method for constructing a VLA is to fine-tune a vision-language model (VLM) by training it on robot trajectory data and large-scale visual language dat... |
Force control : Force control is the control of the force with which a machine or the manipulator of a robot acts on an object or its environment. By controlling the contact force, damage to the machine as well as to the objects to be processed and injuries when handling people can be prevented. In manufacturing tasks,... |
Force control : Controlling the contact force between a manipulator and its environment is an increasingly important task in the environment of mechanical manufacturing, as well as industrial and service robot. One motivation for the use of force control is safety for man and machine. For various reasons, movements of ... |
Force control : In force control, a basic distinction can be made between applications with pronounced contact and applications with potential contact. We speak of pronounced contact when the contact of the machine with the environment or the workpiece is a central component of the task and is explicitly controlled. Th... |
Force control : The first important work on force control was published in 1980 by John Kenneth Salisbury at Stanford University. In it, he describes a method for active stiffness control, a simple form of impedance control. However, the method does not yet allow a combination with motion control, but here force contro... |
Force control : To close the force control loop in the sense of a closed-loop control, the instantaneous value of the contact force must be known. The contact force can either be measured directly or estimated. |
Force control : Various control concepts are used for force control. Depending on the desired behavior of the system, a distinction is made between the concepts of direct force control and indirect control via specification of compliance or mechanical impedance. As a rule, force control is combined with motion control.... |
Force control : In recent years, the subject of research has increasingly been adaptive concepts, the use of fuzzy control system and machine learning, and force-based whole-body control. |
Force control : Bruno Siciliano, Luigi Villani (2000), Robot Force Control, Springer, ISBN 0-7923-7733-8 Wolfgang Weber (2002), Industrieroboter. Methoden der Steuerung und Regelung, Fachbuchverlag Leipzig, ISBN 3-446-21604-9 Lorenzo Sciavicco, Bruno Siciliano (1999), Modelling and Control of Robot Manipulators, Spring... |
Gorn address : A Gorn address (Gorn, 1967) is a method of identifying and addressing any node within a tree data structure. This notation is often used for identifying nodes in a parse tree defined by phrase structure rules. The Gorn address is a sequence of zero or more integers conventionally separated by dots, e.g.,... |
Gorn address : Gorn, S. (1967). Explicit definitions and linguistic dominoes. Systems and Computer Science, Eds. J. Hart & S. Takasu. 77-115. University of Toronto Press, Toronto Canada. |
Claude (language model) : Claude is a family of large language models developed by Anthropic. The first model was released in March 2023. The Claude 3 family, released in March 2024, consists of three models: Haiku, optimized for speed; Sonnet, which balances capability and performance; and Opus, designed for complex r... |
Claude (language model) : Claude models are generative pre-trained transformers. They have been pre-trained to predict the next word in large amounts of text. Then, they have been fine-tuned, notably using constitutional AI and reinforcement learning from human feedback (RLHF). |
Claude (language model) : The name Claude was notably inspired by Claude Shannon, a pioneer in artificial intelligence. |
Claude (language model) : In July 2024, Anthropic released the Artifacts feature, allowing users to generate and interact with code snippets and documents. In October 2024, Anthropic released the "computer use" feature, allowing Claude to attempt to navigate computers by interpreting screen content and simulating keybo... |
Outline of statistics : The following outline is provided as an overview of and topical guide to statistics: Statistics is a field of inquiry that studies the collection, analysis, interpretation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the physical and social sciences... |
Outline of statistics : Statistics can be described as all of the following: An academic discipline: one with academic departments, curricula and degrees; national and international societies; and specialized journals. A scientific field (a branch of science) – widely recognized category of specialized expertise within... |
Outline of statistics : History of statistics Founders of statistics History of probability Timeline of probability and statistics |
Outline of statistics : Descriptive statistics Average Mean Median Mode Measures of scale Variance Standard deviation Median absolute deviation Correlation Polychoric correlation Outlier Statistical graphics Histogram Frequency distribution Quantile Survival function Failure rate Scatter plot Bar chart |
Outline of statistics : Design of experiments Optimal design Factorial experiment Restricted randomization Repeated measures design Randomized block design Cross-over design Randomization Statistical survey Opinion poll |
Outline of statistics : Regression analysis Outline of regression analysis Analysis of variance (ANOVA) General linear model Generalized linear model Generalized least squares Mixed model Elastic net regularization Ridge regression Lasso (statistics) Survival analysis Density estimation Kernel density estimation Multiv... |
Outline of statistics : Recursive Bayesian estimation Kalman filter Particle filter Moving average SQL |
Outline of statistics : Statistical inference Mathematical statistics Likelihood function Exponential family Fisher information Sufficient statistic Ancillary statistic Minimal sufficiency Kullback–Leibler divergence Nuisance parameter Order statistic Bayesian inference Bayes' theorem Bayes estimator Prior distribution... |
Outline of statistics : Probability distribution Symmetric probability distribution Unimodal probability distribution Conditional probability distribution Probability density function Cumulative distribution function Characteristic function List of probability distributions |
Outline of statistics : Random variable Central moment L-moment Algebra of random variables |
Outline of statistics : Probability Conditional probability Law of large numbers Central limit theorem Concentration inequality Convergence of random variables |
Outline of statistics : Computational statistics Markov chain Monte Carlo Bootstrapping (statistics) Jackknife resampling Integrated nested Laplace approximations Nested sampling algorithm Metropolis–Hastings algorithm Importance sampling Mathematical optimization Convex optimization Linear programming Linear matrix in... |
Outline of statistics : Free statistical software List of statistical packages |
Outline of statistics : List of academic statistical associations List of national and international statistical services |
Outline of statistics : List of statistics journals List of important publications in statistics |
Outline of statistics : Combinatorics Glossary of probability and statistics Index of statistics articles List of fields of application of statistics List of graphical methods Lists of statistics topics Monte Carlo method Notation in probability and statistics Outline of probability Philosophy of statistics Simulation |
Self-management (computer science) : Self-management is the process by which computer systems manage their own operation without human intervention. Self-management technologies are expected to pervade the next generation of network management systems. The growing complexity of modern networked computer systems is a li... |
Self-management (computer science) : Fault tolerance Resilience (network) Robustness (computer science) |
Self-management (computer science) : Practical Autonomic Computing - Roadmap to Self Managing Technology |
Manifold regularization : In machine learning, Manifold regularization is a technique for using the shape of a dataset to constrain the functions that should be learned on that dataset. In many machine learning problems, the data to be learned do not cover the entire input space. For example, a facial recognition syste... |
Manifold regularization : Manifold regularization can extend a variety of algorithms that can be expressed using Tikhonov regularization, by choosing an appropriate loss function V and hypothesis space H . Two commonly used examples are the families of support vector machines and regularized least squares algorithms.... |
Manifold regularization : Manifold regularization assumes that data with different labels are not likely to be close together. This assumption is what allows the technique to draw information from unlabeled data, but it only applies to some problem domains. Depending on the structure of the data, it may be necessary to... |
Manifold regularization : Manifold learning Manifold hypothesis Semi-supervised learning Transduction (machine learning) Spectral graph theory Reproducing kernel Hilbert space Tikhonov regularization Differential geometry |
EleutherAI : EleutherAI () is a grass-roots non-profit artificial intelligence (AI) research group. The group, considered an open-source version of OpenAI, was formed in a Discord server in July 2020 by Connor Leahy, Sid Black, and Leo Gao to organize a replication of GPT-3. In early 2023, it formally incorporated as t... |
EleutherAI : EleutherAI began as a Discord server on July 7, 2020, under the tentative name "LibreAI" before rebranding to "EleutherAI" later that month, in reference to eleutheria, the Greek word for liberty. On December 30, 2020, EleutherAI released The Pile, a curated dataset of diverse text for training large langu... |
EleutherAI : According to their website, EleutherAI is a "decentralized grassroots collective of volunteer researchers, engineers, and developers focused on AI alignment, scaling, and open-source AI research". While they do not sell any of their technologies as products, they publish the results of their research in ac... |
Psychology of reasoning : The psychology of reasoning (also known as the cognitive science of reasoning) is the study of how people reason, often broadly defined as the process of drawing conclusions to inform how people solve problems and make decisions. It overlaps with psychology, philosophy, linguistics, cognitive ... |
Psychology of reasoning : One of the most obvious areas in which people employ reasoning is with sentences in everyday language. Most experimentation on deduction has been carried out on hypothetical thought, in particular, examining how people reason about conditionals, e.g., If A then B. Participants in experiments m... |
Psychology of reasoning : There are several alternative theories of the cognitive processes that human reasoning is based on. One view is that people rely on a mental logic consisting of formal (abstract or syntactic) inference rules similar to those developed by logicians in the propositional calculus. Another view is... |
Psychology of reasoning : It is an active question in psychology how, why, and when the ability to reason develops from infancy to adulthood. Jean Piaget's theory of cognitive development posited general mechanisms and stages in the development of reasoning from infancy to adulthood. According to the neo-Piagetian theo... |
Psychology of reasoning : Philip Johnson-Laird trying to taxonomize thought, distinguished between goal-directed thinking and thinking without goal, noting that association was involved in unrelated reading. He argues that goal directed reasoning can be classified based on the problem space involved in a solution, citi... |
Psychology of reasoning : Judgment and reasoning involve thinking through the options, making a judgment or conclusion and finally making a decision. Making judgments involves heuristics, or efficient strategies that usually lead one to the right answers. The most common heuristics used are attribute substitution, the ... |
Psychology of reasoning : The inferences people draw are related to factors such as linguistic pragmatics and emotion. Decision making is often influenced by the emotion of regret and by the presence of risk. When people are presented with options, they tend to select the one that they think they will regret the least.... |
Psychology of reasoning : Studying reasoning neuroscientifically involves determining the neural correlates of reasoning, often investigated using event-related potentials and functional magnetic resonance imaging. In fMRI studies, participants are presented with variations of tasks to determine the different cognitive... |
Psychology of reasoning : Bounded rationality Cognitive psychology Ecological rationality Emotional self-regulation Great Rationality Debate Heuristics in judgment and decision-making Naturalistic decision-making == Notes == |
Maharashtra Advanced Research and Vigilance for Enhanced Law Enforcement : Maharashtra Advanced Research and Vigilance for Enhanced Law Enforcement (MARVEL) is an artificial intelligence (AI) system implemented by the Maharashtra Police. It is noted for being the first state-level police AI system in India. Approved in... |
Maharashtra Advanced Research and Vigilance for Enhanced Law Enforcement : The Maharashtra state cabinet approved the creation of MARVEL in March 2024, just before the announcement of the Model Code of Conduct for the Lok Sabha elections. The project was allocated an initial budget of ₹23 crore. |
Maharashtra Advanced Research and Vigilance for Enhanced Law Enforcement : MARVEL is overseen by officials from the Maharashtra Police and the Indian Institute of Management (IIM) Nagpur. The Superintendent of Police, Nagpur (Rural), Harssh Poddar, serves as the ex-officio Chief Executive Officer (CEO) of MARVEL. Dr. B... |
Maharashtra Advanced Research and Vigilance for Enhanced Law Enforcement : MARVEL is established as a Special Purpose Vehicle (SPV) and operates through a partnership between: Government of Maharashtra Indian Institute of Management Nagpur Pinaka Technologies Private Limited The company is registered under the Companie... |
Maharashtra Advanced Research and Vigilance for Enhanced Law Enforcement : The Government of Maharashtra has committed to providing 100% share capital to MARVEL for the first five years, amounting to ₹4.2 crore annually. |
Maharashtra Advanced Research and Vigilance for Enhanced Law Enforcement : In addition to MARVEL, the Maharashtra government has approved other technology-driven law enforcement initiatives: A ₹76 crore semi-automated processing project for the speedy disposal of cybercrime cases Establishment of a ₹42 crore Computer F... |
Maharashtra Advanced Research and Vigilance for Enhanced Law Enforcement : Maharashtra Police Artificial intelligence in law enforcement == References == |
Recursive self-improvement : Recursive self-improvement (RSI) is a process in which an early or weak artificial general intelligence (AGI) system enhances its own capabilities and intelligence without human intervention, leading to a superintelligence or intelligence explosion. The development of recursive self-improve... |
Recursive self-improvement : The concept of a "seed improver" architecture is a foundational framework that equips an AGI system with the initial capabilities required for recursive self-improvement. This might come in many forms or variations. The term "Seed AI" was coined by Eliezer Yudkowsky. |
Recursive self-improvement : Artificial general intelligence Bifurcation theory Intelligence explosion Superintelligence == References == |
Vocabulary mismatch : Vocabulary mismatch is a common phenomenon in the usage of natural languages, occurring when different people name the same thing or concept differently. Furnas et al. (1987) were perhaps the first to quantitatively study the vocabulary mismatch problem. Their results show that on average 80% of t... |
Vocabulary mismatch : Stemming Full-text indexing instead of only indexing keywords or abstracts Use of controlled vocabularies in both indexing and retrieval, such as taxonomies or ontologies Indexing text on inbound links from other documents (or other social tagging) Query expansion. A 2012 study by Zhao and Callan ... |
CarynAI : CarynAI is a chatbot launched by Snapchat influencer Caryn Marjorie, and powered by BanterAI. == References == |
Bayesian structural time series : Bayesian structural time series (BSTS) model is a statistical technique used for feature selection, time series forecasting, nowcasting, inferring causal impact and other applications. The model is designed to work with time series data. The model has also promising application in the ... |
Bayesian structural time series : The model consists of three main components: Kalman filter. The technique for time series decomposition. In this step, a researcher can add different state variables: trend, seasonality, regression, and others. Spike-and-slab method. In this step, the most important regression predicto... |
Bayesian structural time series : Bayesian inference using Gibbs sampling Correlation does not imply causation Spike-and-slab regression |
Bayesian structural time series : Scott, S. L., & Varian, H. R. 2014a. Bayesian variable selection for nowcasting economic time series. Economic Analysis of the Digital Economy. Scott, S. L., & Varian, H. R. 2014b. Predicting the present with bayesian structural time series. International Journal of Mathematical Modell... |
LanguageWare : LanguageWare is a natural language processing (NLP) technology developed by IBM, which allows applications to process natural language text. It comprises a set of Java libraries that provide a range of NLP functions: language identification, text segmentation/tokenization, normalization, entity and relat... |
LanguageWare : Data Discovery and Query Builder Formal language IBM Omnifind Linguistics Semantic Web Semantics Service-oriented architecture Web services UIMA |
LanguageWare : IBM LanguageWare Resource Workbench on alphaWorks IBM LanguageWare Miner for Multidimensional Socio-Semantic Networks on alphaWorks JumpStart Infocenter for IBM LanguageWare on IBM.com UIMA Homepage at the Apache Software Foundation UIMA Framework on SourceForge IBM OmniFind Yahoo! Edition (FREE enterpri... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.