A transformer is a deep learning architecture developed by Google and based on the multi-head attention mechanism, proposed in a 2017 paper "Attention...
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Mamba is a deep learning architecture focused on sequence modeling. It was developed by researchers from Carnegie Mellon University and Princeton University...
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paper "Attention Is All You Need" which introduced the Transformer model, a novel architecture that uses a self-attention mechanism and has since become...
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a {\displaystyle W_{a}} is a learnable weight matrix. Transformer (deep learning architecture) § Efficient implementation Rumelhart, David E.; Mcclelland...
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supervised, semi-supervised or unsupervised. Deep-learning architectures such as deep neural networks, deep belief networks, recurrent neural networks,...
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used in natural language processing tasks. GPTs are based on the transformer architecture, pre-trained on large data sets of unlabelled text, and able to...
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Multimodal learning, in the context of machine learning, is a type of deep learning using a combination of various modalities of data, such as text, audio...
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That Transformer (machine learning model), a deep learning architecture Transformer (flying car), a DARPA military project "Electronic transformer", a...
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made available for TensorFlow. Transformer (machine learning model) Attention (machine learning) Perceiver Deep learning PyTorch TensorFlow Dosovitskiy...
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Google Brain (redirect from Google deep learning project)
present in a photo that a human could easily spot. The transformer deep learning architecture was invented by Google Brain researchers in 2017, and explained...
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Things, and pharmaceuticals. Federated learning aims at training a machine learning algorithm, for instance deep neural networks, on multiple local datasets...
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GPT-3 (redirect from Generative Pre-trained Transformer 3)
transformer-based deep-learning neural network architectures. Previously, the best-performing neural NLP models commonly employed supervised learning...
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Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the...
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T5 (language model) (section Architecture)
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI. Introduced in 2019, T5 models are trained on a massive...
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AI accelerator (redirect from Deep learning accelerator)
An AI accelerator, deep learning processor, or neural processing unit (NPU) is a class of specialized hardware accelerator or computer system designed...
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mechanisms proposed by Bahdanau et al. into a new deep learning architecture known as the transformer. The paper is considered by some to be a founding...
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Whisper is a weakly-supervised deep learning acoustic model, made using an encoder-decoder transformer architecture. Whisper V2 was released on December...
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ongoing AI spring, and further increasing interest in ANNs. The transformer architecture was first described in 2017 as a method to teach ANNs grammatical...
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Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs...
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adversarial networks (GAN) and transformers are used for content creation across numerous industries. This is because deep learning models are able to learn...
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Large language model (category Deep learning)
capable, as of March 2024[update], are built with a decoder-only transformer-based architecture. Up to 2020, fine tuning was the only way a model could be adapted...
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Q-learning algorithm. In 2014, Google DeepMind patented an application of Q-learning to deep learning, titled "deep reinforcement learning" or "deep Q-learning"...
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GPT-1 (category Generative pre-trained transformers)
Pre-trained Transformer 1 (GPT-1) was the first of OpenAI's large language models following Google's invention of the transformer architecture in 2017. In...
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modalities through the use of deep neural network architectures such as CNNs and transformers. Supervised feature learning is learning features from labeled data...
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Residual neural network (category Deep learning)
network (also referred to as a residual network or ResNet) is a seminal deep learning model in which the weight layers learn residual functions with reference...
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GPT-4 (redirect from Generative Pre-trained Transformer 4)
Generative Pre-trained Transformer 4 (GPT-4) is a multimodal large language model created by OpenAI, and the fourth in its series of GPT foundation models...
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Multilayer perceptron (category Neural network architectures)
successes of deep learning being applied to language modelling by Yoshua Bengio with co-authors. In 2017, modern transformer architectures has been introduced...
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GPT-2 (redirect from Generative Pre-trained Transformer 2)
GPT-4, a generative pre-trained transformer architecture, implementing a deep neural network, specifically a transformer model, which uses attention instead...
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Bidirectional Encoder Representations from Transformers (BERT) is a language model based on the transformer architecture, notable for its dramatic improvement...
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performance of their model. If deep learning is used, the architecture of the neural network must also be chosen by the machine learning expert. Each of these...
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