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t. e. Generative Pre-trained Transformer 3 ( GPT-3) is a large language model released by OpenAI in 2020. Like its predecessor, GPT-2, it is a decoder-only [2] transformer model of deep neural network, which supersedes recurrence and convolution-based architectures with a technique known as "attention". [3]
History Initial developments. Generative pretraining (GP) was a long-established concept in machine learning applications. 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.
Winograd schema challenge. The Winograd schema challenge ( WSC) is a test of machine intelligence proposed in 2012 by Hector Levesque, a computer scientist at the University of Toronto. Designed to be an improvement on the Turing test, it is a multiple-choice test that employs questions of a very specific structure: they are instances of what ...
An average word in another language encoded by such an English-optimized tokenizer is however split into suboptimal amount of tokens. GPT-2 tokenizer can use up to 15 times more tokens per word for some languages, for example for the Shan language from Myanmar. Even more widespread languages such as Portuguese and German have "a premium of 50% ...
OpenAI's GPT-4 model is released in March 2023 and is regarded as an impressive improvement over GPT-3.5, with the caveat that GPT-4 retains many of the same problems of the earlier iteration. Unlike previous iterations, GPT-4 is multimodal, allowing image input as well as text. GPT-4 is integrated into ChatGPT as a subscriber service.
e. Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous ...
A physical symbol system (also called a formal system) takes physical patterns (symbols), combining them into structures (expressions) and manipulating them (using processes) to produce new expressions. The physical symbol system hypothesis ( PSSH) is a position in the philosophy of artificial intelligence formulated by Allen Newell and Herbert ...
v. t. e. An artistic representation of AI. In artificial intelligence, symbolic artificial intelligence is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. [1] Symbolic AI used tools such as logic programming ...
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