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Physics-informed neural networks (PINNs) are a class of deep learning models that incorporate physical laws, typically expressed as differential equations, into the training process. By embedding these constraints, PINNs can solve forward and inverse problems in scientific computing with improved accuracy and generalization.
System identification for sim-to-real involves creating models that bridge the gap between simulated environments and real-world applications, enhancing the transferability of learned behaviors.
A large language model (LLM) is an advanced type of artificial intelligence designed to understand, generate, and interact using human language. These models are trained on vast amounts of text data and utilize deep learning techniques to perform a wide range of language-related tasks.
CodeGen is a family of large-scale language models designed to generate computer code from natural language prompts. Developed to assist programmers by automating coding tasks, CodeGen leverages advanced machine learning techniques and large datasets of code to improve software development workflows.
Mamba is a computational framework designed for Bayesian inference in state space models, providing flexible tools for modeling time series data with latent variables.
Knowledge distillation is a machine learning technique where a smaller model is trained to replicate the behavior of a larger, more complex model. This process helps deploy efficient models by transferring knowledge from a ‘teacher’ model to a ‘student’ model.
Artificial intelligence in Russia encompasses the development and application of AI technologies within Russian academia, industry, and government sectors. Russia has made significant strides in AI research and deployment, particularly in fields like computer vision, natural language processing, and military applications.
Chain-of-thought for robotics refers to methodologies enabling robots to process information in a logical sequence, enhancing decision-making and problem-solving capabilities.
BigBird is a transformer-based neural network architecture designed to efficiently process long sequences by extending the standard attention mechanism with sparse attention patterns. It enables scalable natural language processing and other sequence modeling tasks.
A virtual assistant is a software agent that can perform tasks or services for an individual based on commands or questions. These assistants use artificial intelligence, voice recognition, and natural language processing to provide user interaction.