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Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 2 ] [ 3 ] [ 4 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 5 ] [ 6 ] based on ...
The systems studied in chaos theory are deterministic. If the initial state were known exactly, then the future state of such a system could theoretically be predicted. However, in practice, knowledge about the future state is limited by the precision with which the initial state can be measured, and chaotic systems are characterized by a strong dependence on the initial condit
In flow-based diffusion models, the forward process is a deterministic flow along a time-dependent vector field, and the backward process is also a deterministic flow along the same vector field, but going backwards. Both processes are solutions to ODEs. If the vector field is well-behaved, the ODE will also be well-behaved.
In May 2020, Nvidia researchers taught an AI system (termed "GameGAN") to recreate the game of Pac-Man simply by watching it being played. [ 94 ] [ 95 ] In August 2019, a large dataset consisting of 12,197 MIDI songs each with paired lyrics and melody alignment was created for neural melody generation from lyrics using conditional GAN-LSTM ...
Deterministic algorithms are by far the most studied and familiar kind of algorithm, as well as one of the most practical, since they can be run on real machines efficiently. Formally, a deterministic algorithm computes a mathematical function ; a function has a unique value for any input in its domain , and the algorithm is a process that ...
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.
For example, GPT-3, and its precursor GPT-2, [11] are auto-regressive neural language models that contain billions of parameters, BigGAN [12] and VQ-VAE [13] which are used for image generation that can have hundreds of millions of parameters, and Jukebox is a very large generative model for musical audio that contains billions of parameters. [14]
Lisp was the first language developed for artificial intelligence. It includes features intended to support programs that could perform general problem solving, such as lists, associations, schemas (frames), dynamic memory allocation, data types , recursion, associative retrieval, functions as arguments, generators (streams), and cooperative ...