The transformer is a deep learning architecture based on the multi-head attention mechanism, in which text is converted to numerical representations called...

speech processing[citation needed]. Language modeling Transformer (machine learning model) State-space model Recurrent neural network The name comes from...

In machine learning, diffusion models, also known as diffusion-based generative models or score-based generative models, are a class of latent variable...

of 1.6 exaFLOPs. Transformer (machine learning model) Convolutional neural network Attention (machine learning) Perceiver Deep learning PyTorch TensorFlow...

language model (LLM) is a machine learning model designed for natural language processing tasks, especially language generation. LLMs are language models with...

that is used in natural language processing by machines. It is based on the transformer deep learning architecture, pre-trained on large data sets of...

and Survey. Attention (machine learning) Transformer (machine learning model) Seq2seq Koehn, Philipp (2020). Neural Machine Translation. Cambridge University...

2021. Zhang, Ruiqi (2024). "Trained Transformers Learn Linear Models In-Context" (PDF). Journal of Machine Learning Research 1-55. 25. arXiv:2306.09927...

Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn...

(2023), and Muse (2023). Unlike later models, DALL-E is not a diffusion model. Instead, it uses a decoder-only Transformer that autoregressively generates a...

includes every stage from beginning with a raw dataset to building a machine learning model ready for deployment. AutoML was proposed as an artificial intelligence-based...

Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. Like the original Transformer model, T5 models are encoder-decoder...

in machine learning authored by eight scientists working at Google. The paper introduced a new deep learning architecture known as the transformer, based...

reward model to represent preferences, which can then be used to train other models through reinforcement learning. In classical reinforcement learning, an...

Ensemble learning trains two or more machine learning algorithms on a specific classification or regression task. The algorithms within the ensemble model are...

common attacks in adversarial machine learning include evasion attacks, data poisoning attacks, Byzantine attacks and model extraction. At the MIT Spam...

approaches. Whisper is a weakly-supervised deep learning acoustic model, made using an encoder-decoder transformer architecture. Whisper Large V2 was released...

Self-supervised learning (SSL) is a paradigm in machine learning where a model is trained on a task using the data itself to generate supervisory signals...

Hasbro Transformers: The Ride 3D, theme park rides located in several Universal Studios parks Transformer (machine learning model) Transformer (disambiguation)...

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 transformer model of...

model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with...

simplification Transformer (machine learning model) Truecasing Question answering Word2vec "NLP". Hutchins, J. (2005). "The history of machine translation...

In machine learning, support vector machines (SVMs, also support vector networks) are supervised max-margin models with associated learning algorithms...

pre-trained transformer (GPT) models and is fine-tuned for conversational applications using a combination of supervised learning and reinforcement learning from...

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...

Deep learning is a subset of machine learning that focuses on utilizing multilayered neural networks to perform tasks such as classification, regression...

Changliang; Wong, Derek F.; Chao, Lidia S. (2019). "Learning Deep Transformer Models for Machine Translation". arXiv:1906.01787 [cs.CL]. Xiong, Ruibin;...

which a machine learning model "learns". In the adaptive control literature, the learning rate is commonly referred to as gain. In setting a learning rate...

information retrieval. Large language models (LLMs), currently their most advanced form, are predominantly based on transformers trained on larger datasets (frequently...

intelligence (AI), a foundation model (FM), also known as large X model (LxM), is a machine learning or deep learning model trained on vast datasets so that...