Engineers solve 50-year-old puzzle in signal processing

Something called the fast Fourier transform is running on your cell phone right now. The FFT, as it is known, is a signal-processing algorithm that you use more than you realize. It is, according to the title of one research ...

Machine learning & AI

How artificial intelligence is supercharging materials science

Machine learning and artificial intelligence are increasingly being used in materials science research. For example, MIT associate professor of materials science and engineering Juejun "JJ" Hu developed an algorithm that ...


Engineers build drones to test hypersonic tech

Sandia National Laboratories is developing autonomy and artificial intelligence for flight systems soaring at more than 3,800 mph. The technologies to get there will initially be tested on drones that shuffle around at about ...


A smart artificial hand for amputees merges user and robotic control

EPFL scientists are developing new approaches for improved control of robotic hands—in particular for amputees—that combines individual finger control and automation for improved grasping and manipulation. This interdisciplinary ...

Hi Tech & Innovation

AI learns the language of chemistry to predict how to make medicines

Researchers have designed a machine learning algorithm that predicts the outcome of chemical reactions with much higher accuracy than trained chemists and suggests ways to make complex molecules, removing a significant hurdle ...

Machine learning & AI

AI learns complex gene-disease patterns

Artificial intelligence (AI) is being harnessed by researchers to track down genes that cause disease. A KAUST team is taking a creative, combined deep learning approach that uses data from multiple sources to teach algorithms ...

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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.

This text uses material from Wikipedia, licensed under CC BY-SA