You are looking at all articles with the topic "Robotics". We found 24 matches.

Hint: To view all topics, click here. Too see the most popular topics, click here instead.

🔗 Robotics 🔗 Electronics

Surface-mount technology (SMT) component placement systems, commonly called pick-and-place machines or P&Ps, are robotic machines which are used to place surface-mount devices (SMDs) onto a printed circuit board (PCB). They are used for high speed, high precision placing of a broad range of electronic components, like capacitors, resistors, integrated circuits onto the PCBs which are in turn used in computers, consumer electronics as well as industrial, medical, automotive, military and telecommunications equipment. Similar equipment exists for through-hole components. This type of equipment is sometimes also used to package microchips using the flip chip method.

🔗 International relations 🔗 Technology 🔗 Internet 🔗 Computing 🔗 Computer science 🔗 Law 🔗 Business 🔗 Politics 🔗 Robotics 🔗 International relations/International law 🔗 Futures studies 🔗 European Union 🔗 Science Policy 🔗 Artificial Intelligence

The Artificial Intelligence Act (AI Act) is a European Union regulation concerning artificial intelligence (AI).

It establishes a common regulatory and legal framework for AI in the European Union (EU). Proposed by the European Commission on 21 April 2021, and then passed in the European Parliament on 13 March 2024, it was unanimously approved by the Council of the European Union on 21 May 2024. The Act creates a European Artificial Intelligence Board to promote national cooperation and ensure compliance with the regulation. Like the EU's General Data Protection Regulation, the Act can apply extraterritorially to providers from outside the EU, if they have users within the EU.

It covers all types of AI in a broad range of sectors; exceptions include AI systems used solely for military, national security, research and non-professional purposes. As a piece of product regulation, it would not confer rights on individuals, but would regulate the providers of AI systems and entities using AI in a professional context. The draft Act was revised following the rise in popularity of generative AI systems, such as ChatGPT, whose general-purpose capabilities did not fit the main framework. More restrictive regulations are planned for powerful generative AI systems with systemic impact.

The Act classifies AI applications by their risk of causing harm. There are four levels – unacceptable, high, limited, minimal – plus an additional category for general-purpose AI. Applications with unacceptable risks are banned. High-risk applications must comply with security, transparency and quality obligations and undergo conformity assessments. Limited-risk applications only have transparency obligations and those representing minimal risks are not regulated. For general-purpose AI, transparency requirements are imposed, with additional evaluations when there are high risks.

La Quadrature du Net (LQDN) stated that the adopted version of the AI Act would be ineffective, arguing that the role of self-regulation and exemptions in the act rendered it "largely incapable of standing in the way of the social, political and environmental damage linked to the proliferation of AI".

🔗 Robotics 🔗 Transhumanism

In aesthetics, the uncanny valley is a hypothesized relationship between the degree of an object's resemblance to a human being and the emotional response to such an object. The concept of the uncanny valley suggests that humanoid objects which imperfectly resemble actual human beings provoke uncanny or strangely familiar feelings of eeriness and revulsion in observers. "Valley" denotes a dip in the human observer's affinity for the replica, a relation that otherwise increases with the replica's human likeness.

Examples can be found in robotics, 3D computer animations, and lifelike dolls among others. With the increasing prevalence of virtual reality, augmented reality, and photorealistic computer animation, the "valley" has been cited in the popular press in reaction to the verisimilitude of the creation as it approaches indistinguishability from reality. The uncanny valley hypothesis predicts that an entity appearing almost human will risk eliciting cold, eerie feelings in viewers.

🔗 Computing 🔗 Computer science 🔗 Science Fiction 🔗 Cognitive science 🔗 Robotics 🔗 Transhumanism 🔗 Software 🔗 Software/Computing 🔗 Futures studies

Artificial general intelligence (AGI) is the hypothetical intelligence of a machine that has the capacity to understand or learn any intellectual task that a human being can. It is a primary goal of some artificial intelligence research and a common topic in science fiction and futures studies. AGI can also be referred to as strong AI, full AI, or general intelligent action. (Some academic sources reserve the term "strong AI" for machines that can experience consciousness.)

Some authorities emphasize a distinction between strong AI and applied AI (also called narrow AI or weak AI): the use of software to study or accomplish specific problem solving or reasoning tasks. Weak AI, in contrast to strong AI, does not attempt to perform the full range of human cognitive abilities.

As of 2017, over forty organizations were doing research on AGI.

🔗 Economics 🔗 Robotics 🔗 Game theory

Mechanism design is a field in economics and game theory that takes an objectives-first approach to designing economic mechanisms or incentives, toward desired objectives, in strategic settings, where players act rationally. Because it starts at the end of the game, then goes backwards, it is also called reverse game theory. It has broad applications, from economics and politics (markets, auctions, voting procedures) to networked-systems (internet interdomain routing, sponsored search auctions).

Mechanism design studies solution concepts for a class of private-information games. Leonid Hurwicz explains that 'in a design problem, the goal function is the main "given", while the mechanism is the unknown. Therefore, the design problem is the "inverse" of traditional economic theory, which is typically devoted to the analysis of the performance of a given mechanism.' So, two distinguishing features of these games are:

• that a game "designer" chooses the game structure rather than inheriting one
• that the designer is interested in the game's outcome

The 2007 Nobel Memorial Prize in Economic Sciences was awarded to Leonid Hurwicz, Eric Maskin, and Roger Myerson "for having laid the foundations of mechanism design theory".

🔗 Robotics

An eigenface () is the name given to a set of eigenvectors when used in the computer vision problem of human face recognition. The approach of using eigenfaces for recognition was developed by Sirovich and Kirby (1987) and used by Matthew Turk and Alex Pentland in face classification. The eigenvectors are derived from the covariance matrix of the probability distribution over the high-dimensional vector space of face images. The eigenfaces themselves form a basis set of all images used to construct the covariance matrix. This produces dimension reduction by allowing the smaller set of basis images to represent the original training images. Classification can be achieved by comparing how faces are represented by the basis set.

🔗 Statistics 🔗 Robotics

Thompson sampling, named after William R. Thompson, is a heuristic for choosing actions that address the exploration-exploitation dilemma in the multi-armed bandit problem. It consists of choosing the action that maximizes the expected reward with respect to a randomly drawn belief.

🔗 Robotics 🔗 Transhumanism

Utility fog (coined by Dr. John Storrs Hall in 1989) is a hypothetical collection of tiny robots that can replicate a physical structure. As such, it is a form of self-reconfiguring modular robotics.

🔗 Computing 🔗 Mathematics 🔗 Statistics 🔗 Robotics

In graph theory, a moral graph is used to find the equivalent undirected form of a directed acyclic graph. It is a key step of the junction tree algorithm, used in belief propagation on graphical models.

The moralized counterpart of a directed acyclic graph is formed by adding edges between all pairs of non-adjacent nodes that have a common child, and then making all edges in the graph undirected. Equivalently, a moral graph of a directed acyclic graph G is an undirected graph in which each node of the original G is now connected to its Markov blanket. The name stems from the fact that, in a moral graph, two nodes that have a common child are required to be married by sharing an edge.

Moralization may also be applied to mixed graphs, called in this context "chain graphs". In a chain graph, a connected component of the undirected subgraph is called a chain. Moralization adds an undirected edge between any two vertices that both have outgoing edges to the same chain, and then forgets the orientation of the directed edges of the graph.

🔗 Computing 🔗 Robotics

The Viterbi algorithm is a dynamic programming algorithm for obtaining the maximum a posteriori probability estimate of the most likely sequence of hidden states—called the Viterbi path—that results in a sequence of observed events, especially in the context of Markov information sources and hidden Markov models (HMM).

The algorithm has found universal application in decoding the convolutional codes used in both CDMA and GSM digital cellular, dial-up modems, satellite, deep-space communications, and 802.11 wireless LANs. It is now also commonly used in speech recognition, speech synthesis, diarization, keyword spotting, computational linguistics, and bioinformatics. For example, in speech-to-text (speech recognition), the acoustic signal is treated as the observed sequence of events, and a string of text is considered to be the "hidden cause" of the acoustic signal. The Viterbi algorithm finds the most likely string of text given the acoustic signal.