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IEEE Ethically Aligned Design is a set of guidelines developed by the Institute of Electrical and Electronics Engineers to promote ethical considerations in the design and development of autonomous and intelligent systems. It aims to ensure that technology aligns with human values and societal wellbeing.
Skills discovery in reinforcement learning focuses on identifying and learning useful skills or behaviors that agents can utilize to solve tasks more efficiently.
The Cityscapes dataset is a large-scale dataset for semantic urban scene understanding, primarily used for training and evaluating computer vision algorithms.
Few-shot imitation learning is a branch of machine learning where an agent learns to perform tasks by observing only a small number of demonstrations. This approach aims to enable efficient learning with limited data, often applied in robotics and artificial intelligence.
Self-imitation learning is a machine learning technique where an agent leverages its own past successful experiences to improve future performance. It is primarily used within reinforcement learning to enhance policy optimization by reusing beneficial behaviors.
TimeSformer is a neural network architecture designed for video understanding, leveraging the transformer model to analyze both spatial and temporal features.
ReAct (reasoning and acting) prompting is a method in artificial intelligence that integrates reasoning processes with action generation within language models. It enables models to interleave cognitive reasoning steps with task-oriented actions, enhancing problem-solving and decision-making capabilities.
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ResNet, short for Residual Network, is a type of deep neural network architecture that introduced residual learning to ease the training of very deep networks. It has significantly advanced the field of computer vision by enabling networks with hundreds of layers to be trained effectively.
Prompt injection is a technique that manipulates the input given to AI language models to alter their intended behavior. It exploits the model’s reliance on textual prompts to produce outputs that may bypass restrictions or produce unintended results.