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Artificial intelligence (AI) refers to the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, ...
For AI research, Searle's "weak AI hypothesis" is equivalent to the statement "artificial general intelligence is possible". Thus, according to Russell and Norvig, "most AI researchers take the weak AI hypothesis for granted, and don't care about the strong AI hypothesis."
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.
Meanwhile, America’s leadership in AI, while narrow, has the potential to right the scales and capitalize on an enormous opportunity: McKinsey estimates that AI could add up to $22.1 trillion ...
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 ...
AI is just the latest, and by far the greatest, of these highly profitable revolutions. Nvidia’s bread and butter has long been graphics processing units (GPUs) and system on a chip units (SoCs ...
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation.LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.
AI is remarkable as an optimizer, but it is fundamentally limited as an orienting force. It calculates but does not comprehend. It executes but does not question.
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