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Pronounced "A-star". A graph traversal and pathfinding algorithm which is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. abductive logic programming (ALP) A high-level knowledge-representation framework that can be used to solve problems declaratively based on abductive reasoning. It extends normal logic programming by allowing some ...
The artificial intelligence (AI) boom has brought with it a cornucopia of jargon — from "generative AI" to "synthetic data" — that can be hard to parse. An AI glossary: The words and terms to ...
In the context of AI, it is particularly used for embedded systems and robotics. Libraries such as TensorFlow C++, Caffe or Shogun can be used. [1] JavaScript is widely used for web applications and can notably be executed with web browsers. Libraries for AI include TensorFlow.js, Synaptic and Brain.js. [6]
Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
A recent survey by the U.S. Chamber of Commerce reports that 84% of small businesses using AI are optimistic that it will help their future growth, and 82% of respondents already using AI agree ...
We’re a few weeks away from a new year, and Silicon Valley’s obsession with artificial intelligence isn’t going anywhere. Yes, the biggest trend of 2024 will continue to dominate 2025.
A problem is informally called "AI-complete" or "AI-hard" if it is believed that in order to solve it, one would need to implement AGI, because the solution is beyond the capabilities of a purpose-specific algorithm. [44] There are many problems that have been conjectured to require general intelligence to solve as well as humans.
In probability theory and information theory, the mutual information (MI) of two random variables is a measure of the mutual dependence between the two variables. More specifically, it quantifies the " amount of information " (in units such as shannons ( bits ), nats or hartleys ) obtained about one random variable by observing the other random ...