Hardware

A deep learning-augmented smart mirror to enhance fitness training

In recent years, engineers and computer scientists have created a wide range of technological tools that can enhance fitness training experiences, including smart watches, fitness trackers, sweat-resistant earphones or headphones, ...

Computer Sciences

Using AI to create more efficient math algorithms

A team of researchers at Google's DeepMind, London, has found that AI can find faster algorithms to solve matrix multiplication problems. In their paper published in the journal Nature, the group describes using reinforcement ...

Computer Sciences

Algorithms predict sports teams' moves with 80% accuracy

Algorithms developed in Cornell's Laboratory for Intelligent Systems and Controls can predict the in-game actions of volleyball players with more than 80% accuracy, and now the lab is collaborating with the Big Red hockey ...

Security

Collaborative machine learning that preserves privacy

Training a machine-learning model to effectively perform a task, such as image classification, involves showing the model thousands, millions, or even billions of example images. Gathering such enormous datasets can be especially ...

Computer Sciences

Do trucks mean Trump? AI shows how humans misjudge images

A study on the types of mistakes that humans make when evaluating images may enable computer algorithms that help us make better decisions about visual information, such as while reading an X-ray or moderating online content.

Computer Sciences

Three questions about quantum computing and secure communications

A radically different type of computing technology under development, known as quantum computing, could in theory decode secure communications and jeopardize military communications, critical infrastructure, and financial ...

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Algorithm

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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