Facebook to warn users who 'liked' coronavirus hoaxes

Facebook will soon let you know if you shared or interacted with dangerous coronavirus misinformation on the site, the latest in a string of aggressive efforts the social media giant is taking to contain an outbreak of viral ...

Machine learning & AI

Artificial intelligence accelerates blood flow MRI

Imaging technology helps to detect cardiovascular diseases much earlier; however, precise examinations are still very time-consuming. Researchers from ETH and the University of Zurich have now presented a method that could ...


Algorithm tracker monitors Reddit rankings of COVID posts

On Reddit, which boasts 430 million monthly users, a trustworthy news article about California flattening its coronavirus curve was 77th in the day's recommended posts. Meanwhile, "Socially Distant Drinking Games" was a top-ranked ...

Energy & Green Tech

AI techniques used to improve battery health and safety

Researchers have designed a machine learning method that can predict battery health with 10x higher accuracy than current industry standard, which could aid in the development of safer and more reliable batteries for electric ...


Predicting in-flight air density for more accurate landing

In the final few minutes of a spacecraft landing it is moving at hypersonic speeds through many layers of atmosphere. Knowing the air density outside of the vehicle can have a substantial effect on its angle of descent and ...

Computer Sciences

Google trains chips to design themselves

One of the key challenges of computer design is how to pack chips and wiring in the most ergonomic fashion, maintaining power, speed and energy efficiency.

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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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