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As of August 2023, more than 15 billion images had been generated using text-to-image algorithms, with 80% of these created by models based on Stable Diffusion. [165] If AI-generated content is included in new data crawls from the Internet for additional training of AI models, defects in the resulting models may occur. [166]
Diagram of the latent diffusion architecture used by Stable Diffusion The denoising process used by Stable Diffusion. The model generates images by iteratively denoising random noise until a configured number of steps have been reached, guided by the CLIP text encoder pretrained on concepts along with the attention mechanism, resulting in the desired image depicting a representation of the ...
Prompt engineering. Prompt engineering is the process of structuring an instruction that can be interpreted and understood by a generative artificial intelligence (AI) model. [1][2] A prompt is natural language text describing the task that an AI should perform. [3]
A large language model (LLM) is a type of computational model designed for natural language processing tasks such as language generation. As language models, LLMs acquire these abilities by learning statistical relationships from vast amounts of text during a self-supervised and semi-supervised training process. [1]
Mathematical foundations. Journals and conferences. Related articles. v. t. e. Generative Pre-trained Transformer 2 (GPT-2) is a large language model by OpenAI and the second in their foundational series of GPT models. GPT-2 was pre-trained on a dataset of 8 million web pages. [2] It was partially released in February 2019, followed by full ...
BERT (language model) Bidirectional encoder representations from transformers (BERT) is a language model introduced in October 2018 by researchers at Google. [1][2] It learns to represent text as a sequence of vectors using self-supervised learning. It uses the encoder-only transformer architecture.
Recurrent neural networks (RNNs) are a class of artificial neural network commonly used for sequential data processing. Unlike feedforward neural networks, which process data in a single pass, RNNs process data across multiple time steps, making them well-adapted for modelling and processing text, speech, and time series. [1]
Glossary. v. t. e. Ideogram is a freemium text-to-image model developed by Ideogram, Inc. using deep learning methodologies to generate digital images from natural language descriptions known as "prompts". The model is capable of generating legible text in the images compared to other text-to-image models. [1][2]
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