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Lean is a proof assistant and a functional programming language. [ 1] It is based on the calculus of constructions with inductive types. It is an open-source project hosted on GitHub. It was developed primarily by Leonardo de Moura while employed by Microsoft Research and now Amazon Web Services, and has had significant contributions from other ...
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] [18] 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.
Successor to Derive. Based on Derive's engine used in TI-89/Voyage 200 and TI-Nspire handheld. Wolfram Alpha. Wolfram Research. 2009. 2013. Pro version: $4.99 / month, Pro version for students: $2.99 / month, ioRegular version: free. Proprietary. Online computer algebra system with step-by step solutions.
OpenAI also makes GPT-4 available to a select group of applicants through their GPT-4 API waitlist; [240] after being accepted, an additional fee of US$0.03 per 1000 tokens in the initial text provided to the model ("prompt"), and US$0.06 per 1000 tokens that the model generates ("completion"), is charged for access to the version of the model ...
Math, calculator. License. GPL. Website. qalculate .github .io. Qalculate! is an arbitrary precision cross-platform software calculator. [9] It supports complex mathematical operations and concepts such as derivation, integration, data plotting, and unit conversion. It is a free and open-source software released under GPL v2.
A calculator doesn't make a person better at math, he said, "but it makes people better at math a whole lot faster." Spell check and Grammarly are examples, he said, of AI in use for years. "We're ...
Apache 2.0. Website. arxiv .org /abs /1810 .04805. Bidirectional Encoder Representations from Transformers ( BERT) is a language model introduced in October 2018 by researchers at Google. [ 1][ 2] It learned by self-supervised learning to represent text as a sequence of vectors. It had the transformer encoder architecture.
The perplexity is the exponentiation of the entropy, a more straightforward quantity. Entropy measures the expected or "average" number of bits required to encode the outcome of the random variable using an optimal variable-length code. It can also be regarded as the expected information gain from learning the outcome of the random variable ...
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