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Ablation (artificial Intelligence)
In artificial intelligence (AI), particularly machine learning (ML), ablation is the removal of a component of an AI system. An ablation study investigates the performance of an AI system by removing certain components to understand the contribution of the component to the overall system. The term is an analogy with biology (removal of components of an organism), and is particularly used in the analysis of artificial neural nets by analogy with ablative brain surgery. Other analogies include other neuroscience biological systems such as Drosophilla central nervous system and the vertebrate brain. Ablation studies require that a system exhibit graceful degradation: the system must continue to function even when certain components are missing or degraded. According to some researchers, ablation studies have been deemed a convenient technique in investigating artificial intelligence and its durability to structural damages. Ablation studies damage and/or remove certain components in a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. The ''Oxford English Dictionary'' of Oxford University Press defines artificial intelligence as: the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI applications include advanced web search engines (e.g., Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Tesla), automated decision-making and competing at the highest level in strategic game systems (such as chess and G ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Neural Net
Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute 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. An artificial neuron receives signals then processes them and can signal neurons connected to it. The "signal" at a connection is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs. The connections are called ''edges''. Neurons and edges typically have a ''weight'' that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Neurons may have a threshold such that a signal is sent only if the aggregate signal crosses that threshold. Typically, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ablative Brain Surgery
Ablative brain surgery (also known as brain lesioning) is the surgical ablation by various methods of brain tissue to treat neurological or psychological disorders. The word "Ablation" stems from the Latin word ''Ablatus'' meaning "carried away". In most cases, however, ablative brain surgery does not involve removing brain tissue, but rather destroying tissue and leaving it in place. The lesions it causes are irreversible. There are some target nuclei for ablative surgery and deep brain stimulation. Those nuclei are the motor thalamus, the globus pallidus, and the subthalamic nucleus. Ablative brain surgery was first introduced by Pierre Flourens (1774–1867), a French physiologist. He removed different parts of the nervous system from animals and observed what effects were caused by the removal of certain parts. For example, if an animal could not move its arm after a certain part was removed, it was assumed that the region would control arm movements. The method of removal of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Graceful Degradation
Fault tolerance is the property that enables a system to continue operating properly in the event of the failure of one or more faults within some of its components. If its operating quality decreases at all, the decrease is proportional to the severity of the failure, as compared to a naively designed system, in which even a small failure can cause total breakdown. Fault tolerance is particularly sought after in high-availability, mission-critical, or even life-critical systems. The ability of maintaining functionality when portions of a system break down is referred to as graceful degradation. A fault-tolerant design enables a system to continue its intended operation, possibly at a reduced level, rather than failing completely, when some part of the system fails. The term is most commonly used to describe computer systems designed to continue more or less fully operational with, perhaps, a reduction in throughput or an increase in response time in the event of some partial ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ProQuest
ProQuest LLC is an Ann Arbor, Michigan-based global information-content and technology company, founded in 1938 as University Microfilms by Eugene B. Power. ProQuest is known for its applications and information services for libraries, providing access to dissertations, theses, ebooks, newspapers, periodicals, historical collections, governmental archives, cultural archives,"Jisc and ProQuest Enable Access to Essential Digital Content" retrieved May 21, 2014 and other aggregated databases. This content was estimated to be around 125 billion digital pages, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Allen Newell
Allen Newell (March 19, 1927 – July 19, 1992) was a researcher in computer science and cognitive psychology at the RAND Corporation and at Carnegie Mellon University’s School of Computer Science, Tepper School of Business, and Department of Psychology. He contributed to the Information Processing Language (1956) and two of the earliest AI programs, the Logic Theory Machine (1956) and the General Problem Solver (1957) (with Herbert A. Simon). He was awarded the ACM's A.M. Turing Award along with Herbert A. Simon in 1975 for their basic contributions to artificial intelligence and the psychology of human cognition. Early studies Newell completed his Bachelor's degree in physics from Stanford in 1949. He was a graduate student at Princeton University from 1949–1950, where he did mathematics. Due to his early exposure to an unknown field known as game theory and the experiences from the study of mathematics, he was convinced that he would prefer a combination ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Speech Recognition
Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers with the main benefit of searchability. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis. Some speech recognition systems require "training" (also called "enrollment") where an individual speaker reads text or isolated vocabulary into the system. The system analyzes the person's specific voice and uses it to fine-tune the recognition of that person's speech, resulting in increased accuracy. Systems that do not use training are called "speaker-independent" systems. Systems that use training are called "speaker dependent". Speech recognitio ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ablation
Ablation ( la, ablatio – removal) is removal or destruction of something from an object by vaporization, chipping, erosive processes or by other means. Examples of ablative materials are described below, and include spacecraft material for ascent and atmospheric reentry, ice and snow in glaciology, biological tissues in medicine and passive fire protection materials. Artificial intelligence In artificial intelligence (AI), especially machine learning, ablation is the removal of a component of an AI system. The term is by analogy with biology: removal of components of an organism. Biology Biological ablation is the removal of a biological structure or functionality. Genetic ablation is another term for gene silencing, in which gene expression is abolished through the alteration or deletion of genetic sequence information. In cell ablation, individual cells in a population or culture are destroyed or removed. Both can be used as experimental tools, as in loss-of-functi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Neural Networks
Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute 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. An artificial neuron receives signals then processes them and can signal neurons connected to it. The "signal" at a connection is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs. The connections are called ''edges''. Neurons and edges typically have a ''Weighting, weight'' that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Neurons may have a threshold such that a signal is sent only if the aggregate signal crosses that threshold. T ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
