Pluggable diffractive neural networks based on cascaded metasurfaces
Deep learning algorithms based on artificial neural networks are completely changing information processing methods in many scientific and engineering fields.
Aug 16, 2023
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Deep learning algorithms based on artificial neural networks are completely changing information processing methods in many scientific and engineering fields.
Aug 16, 2023
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The model of democracy in the 1920s is sometimes called "the melting pot"—the dissolution of different cultures into an American soup. An update for the 2020s might be "open source," where cultural mixing, sharing and collaborating ...
Aug 11, 2023
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Seeking to reduce the computing power needed for the widely used dynamic mode decomposition algorithm, a team of researchers in China led by Guo-Ping Guo developed a quantum-classical hybrid algorithm. They tested their algorithm ...
Aug 7, 2023
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Biomedical engineers at Duke University have demonstrated a new method to significantly improve the effectiveness of machine learning models searching for new molecular therapeutics when using just a fraction of the available ...
Jul 27, 2023
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Reservoir computing is a promising computational framework based on recurrent neural networks (RNNs), which essentially maps input data onto a high-dimensional computational space, keeping some parameters of artificial neural ...
The term "artificial intelligence," usually abbreviated as AI, means many things to many people. Initially, the phrase was used to allude to the potential of machines, computers, specifically, somehow gaining sentience on ...
Jun 26, 2023
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Researchers have developed a novel artificial intelligence (AI) model that combines an algorithm based on the scouting and foraging behavior of bee colonies with a fuzzy wavelet neural network to accurately predict road traffic ...
Jun 16, 2023
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Sorting, or data structuring, has been a core principle of computing operations since the first computers were developed.
In theory, quantum computers vastly outperform classical computers in terms of computing speed. For them to do so in practice, it is necessary to design more and novel high-speed algorithms, says ETH supercomputing specialist ...
May 26, 2023
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Despite their enormous size and power, today's artificial intelligence systems routinely fail to distinguish between hallucination and reality. Autonomous driving systems can fail to perceive pedestrians and emergency vehicles ...
May 25, 2023
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In mathematics, computing, linguistics, and related subjects, an algorithm is a finite sequence of instructions, an explicit, step-by-step procedure for solving a problem, often used for calculation and data processing. It is formally a type of effective method in which a list of well-defined instructions for completing a task, will when given an initial state, proceed through a well-defined series of successive states, eventually terminating in an end-state. The transition from one state to the next is not necessarily deterministic; some algorithms, known as probabilistic algorithms, incorporate randomness.
A partial formalization of the concept began with attempts to solve the Entscheidungsproblem (the "decision problem") posed by David Hilbert in 1928. Subsequent formalizations were framed as attempts to define "effective calculability" (Kleene 1943:274) or "effective method" (Rosser 1939:225); those formalizations included the Gödel-Herbrand-Kleene recursive functions of 1930, 1934 and 1935, Alonzo Church's lambda calculus of 1936, Emil Post's "Formulation 1" of 1936, and Alan Turing's Turing machines of 1936–7 and 1939.
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