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Procedural generation is a common technique in computer programming to automate the creation of certain data according to guidelines set by the programmer. Many games generate aspects of the environment or non-player characters procedurally during the development process in order to save time on asset creation.
Generator (mathematics) The 5th roots of unity in the complex plane under multiplication form a group of order 5. Each non-identity element by itself is a generator for the whole group. In mathematics and physics, the term generator or generating set may refer to any of a number of related concepts. The underlying concept in each case is that ...
The Lightweight Java Game Library (LWJGL) is an open-source software library that provides bindings to a variety of C libraries for video game developers to Java. It exposes cross-platform libraries commonly used in developing video games and multimedia titles, such as Vulkan, OpenGL, OpenAL and OpenCL. The primary goal of the project is to ...
Integer overflow can be demonstrated through an odometer overflowing, a mechanical version of the phenomenon. All digits are set to the maximum 9 and the next increment of the white digit causes a cascade of carry-over additions setting all digits to 0, but there is no higher digit (1,000,000s digit) to change to a 1, so the counter resets to zero.
In computing, procedural generation (sometimes shortened as proc-gen) is a method of creating data algorithmically as opposed to manually, typically through a combination of human-generated content and algorithms coupled with computer-generated randomness and processing power. In computer graphics, it is commonly used to create textures and 3D ...
Google Dataset Search. Google Dataset Search is a search engine from Google that helps researchers locate online data that is freely available for use. [1] The company launched the service on September 5, 2018, and stated that the product was targeted at scientists and data journalists. The service was out of beta as of January 23, 2020.
The Pile (dataset) The Pile is an 886.03 GB diverse, open-source dataset of English text created as a training dataset for large language models (LLMs). It was constructed by EleutherAI in 2020 and publicly released on December 31 of that year. [1][2] It is composed of 22 smaller datasets, including 14 new ones. [1]
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
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