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2. Artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Artificial_intelligence

   Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]

3. Deep learning - Wikipedia

   en.wikipedia.org/wiki/Deep_learning

   Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning.The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.

4. Transformer (deep learning architecture) - Wikipedia

   en.wikipedia.org/wiki/Transformer_(deep_learning...

   The plain transformer architecture had difficulty converging. In the original paper [1] the authors recommended using learning rate warmup. That is, the learning rate should linearly scale up from 0 to maximal value for the first part of the training (usually recommended to be 2% of the total number of training steps), before decaying again.

5. Machine learning - Wikipedia

   en.wikipedia.org/wiki/Machine_learning

   Federated learning is an adapted form of distributed artificial intelligence to training machine learning models that decentralizes the training process, allowing for users' privacy to be maintained by not needing to send their data to a centralized server. This also increases efficiency by decentralizing the training process to many devices.

6. Neural network (machine learning) - Wikipedia

   en.wikipedia.org/wiki/Neural_network_(machine...

   Artificial neural networks are used for various tasks, including predictive modeling, adaptive control, and solving problems in artificial intelligence. They can learn from experience, and can derive conclusions from a complex and seemingly unrelated set of information.

7. Recurrent neural network - Wikipedia

   en.wikipedia.org/wiki/Recurrent_neural_network

   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.

8. Multilayer perceptron - Wikipedia

   en.wikipedia.org/wiki/Multilayer_perceptron

   In deep learning, a multilayer perceptron (MLP) is a name for a modern feedforward neural network consisting of fully connected neurons with nonlinear activation functions, organized in layers, notable for being able to distinguish data that is not linearly separable.

9. AI accelerator - Wikipedia

   en.wikipedia.org/wiki/AI_accelerator

   An AI accelerator, deep learning processor or neural processing unit (NPU) is a class of specialized hardware accelerator [1] or computer system [2] [3] designed to accelerate artificial intelligence and machine learning applications, including artificial neural networks and computer vision.