CoML | Cognitive Machine Learning

The aim of the Cognitive Machine Learning team is to reverse engineer such human abilities, i.e., to construct effective and scalable algorithms which perform as well (or better) than humans, when provided with similar data, study their mathematical and algorithmic properties and test their empirical validity as models of humans by comparing ...

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What is Cognitive Computing?

 — Cognitive Computing Explained. The main purpose of cognitive computing is to develop computer systems that are capable of tackling complex problems that usually require human cognition. This involves advanced techniques like machine learning, neural networks, natural language processing, computer vision and more.

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Cognitive automation | Electronic Markets

 — Thus, cognitive automation is a phenomenon that incorporates the approximation and mimicking of a certain degree of human cognition by machines (i.e., artificial cognition, especially system 2 thinking (Kahneman, 2015)) with the primary goal to target the automation of cognitive knowledge and service work (see also Target in Fig. …

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Human and artificial cognition

 — De Winter and Dodou (2014) detail one of the earliest attempts, in 1951, to allocate cognitive tasks to machines or humans: Fitts List. This list allocated functions based on which agent, human or machine, would be best able to perform the task. A total of 11 statements were offered around actions such as automation (machine) and deductive ...

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The brain of the future and the viability of democratic …

 — 1. Introduction. The golden age of cognitive machines: a new paradigm of artificial intelligence. In recent years, a paradigm change in the design of artificial intelligence (AI) is catalyzing an age of extraordinary progress for the development of 'Cognitive Machines': from 'programmable computers' (Turing machine equivalent) that …

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What Is Cognitive Computing?

Cognitive computing is the use of computerized models to not only process information in pre-programmed ways, but also look for new information, interpret it and take whatever actions it deems necessary. Systems are able to formulate responses on their own, rather than adhere to a …

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The Rise of Cognitive AI

 — Part 1: Next, Machines Get Wiser; Part 2: Efficiency, Extensibility and Cognition: Charting the Frontiers; Part 3: Deep Knowledge as the Key to Higher Machine Intelligence; Cognitive Computing …

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A new era in cognitive neuroscience: the tidal wave of …

 — Translating artificial intelligence techniques into the realm of cognitive neuroscience holds promise for significant breakthroughs in our ability to probe the intrinsic mechanisms of the brain. The recent unprecedented development of robust AI models is changing how and what we understand about the brain. In this Editorial, we invite …

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IEEE CogMI 2021

The cognitive machine intelligence (CogMI) is creating unprecedented opportunities for impactful scientific innovations and societal transformations by significantly augmenting the human ability for problem solving and rapid decision making in terms of speed, precision and variety, while fostering innovations in all our human endeavors from ...

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Cognitive psychology-based artificial intelligence review

 — Research status. Research related to artificial intelligence in cognitive psychology is trending in recent years. In the mid-1980s, the term "Kansei Engineeirng" was introduced in the Japanese science and technology community (Ali et al., 2020).They interpret sensibility as human psychological characteristics, study people's perceptual …

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IEEE CogMI 2022

The cognitive machine intelligence (CogMI) is creating unprecedented opportunities for impactful scientific innovations and societal transformations by significantly augmenting the human ability for problem solving and rapid decision making in terms of speed, precision and variety, while fostering innovations in all our human endeavors from ...

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Towards Cognitive Machines: Multiscale Measures and Analysis

An important component of this cognitive machine research includes multiscale measures and analysis. This article presents definitions of cognitive machines, representations of processes, as well as their measurements, measures, and analysis. It provides examples from current research, including cognitive radio, cognitive radar, and cognitive ...

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What is Cognitive Computing? Definition, Advantages, …

At its core, cognitive computing aims to emulate the human brain's decision-making process in machines. The cognitive computing process uses a combination of artificial intelligence, machine learning, neural networks, sentiment analysis, natural language processing, and contextual awareness to solve daily problems just like human beings.

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Building machines that learn and think like people

 — Challenges for building more human-like machines. Although cognitive science has not yet converged on a single account of the mind or intelligence, the claim that a mind is a collection of general-purpose neural networks with few initial constraints is rather extreme in contemporary cognitive science. A different picture has emerged that ...

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Cognitive Machine Theory of Mind

CogToM: A Cognitive Machine Theory of Mind Framework In the Cognitive Machine Theory of Mind (CogToM) (Fig 1), an observer is a cognitive model that builds ToM by observ-ing the actions of agents that play in a gridworld. The ob-server makes predictions regarding the agent's future behav-ior, such as a next-step action or the agent's goal ...

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Cognitive Approach In Psychology

 — Cognitive psychology is the scientific study of the mind as an information processor. It concerns how we take in information from the outside world, and how we make sense of that information. ... Such machine reductionism (simplicity) ignores the influence of human emotion and motivation on the cognitive system and how this may affect our ...

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What is Cognitive Computing? An Architecture and …

Cognitive Computing (COC) aims to build highly cognitive machines with low computational resources that respond in real-time. However, scholarly literature shows varying research areas and various interpretations of COC. This calls for a cohesive architecture that delineates the nature of COC. We argue that if Herbert Simon considered the design

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