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We have compiled hundreds of related entries to help you understand "artificial intelligence"
Future Multi-Predictor Mixture is a model component for time series forecasting that is part of the TimeMixer architecture.
PDM is a theoretical concept for time series forecasting and it is one of the core components of the TimeMixer model.
MRL learns information with different granularities by optimizing nested low-dimensional vectors and allows a single embedding to adapt to the computational constraints of downstream tasks.
Hadoop is an open source framework developed by the Apache Software Foundation for storing and processing large amounts of data on clusters of commodity hardware.
Edge AI refers to the deployment of AI algorithms and AI models directly on local edge devices such as sensors or Internet of Things (IoT) devices, enabling real-time data processing and analysis without constant reliance on cloud infrastructure. Simply put, edge AI refers to the integration of edge computing and human […]
An open source project, product, or initiative embraces and promotes the principles of open communication, collaborative participation, rapid prototyping, transparency, meritocracy, and community-oriented development.
Neuromorphic computing is the process by which computers are designed and built to mimic the structure and function of the human brain, with the aim of using artificial neurons and synapses to process information in this way.
Function calling is a basic concept in programming, which means to perform a specific task by calling a defined function during program execution.
Spiking Neural Network (SNN), at the intersection of neuroscience and artificial intelligence, is a neural network model that simulates the behavior of biological neurons in the brain.
Finite Element Model (FEM) is a numerical calculation method that approximates the physical behavior of an entity by discretizing a continuous physical structure into a finite number of small parts, namely "elements". These elements can be one-dimensional line elements, two-dimensional surface elements, or three-dimensional volume elements.
Contextual position encoding is a new type of position encoding method that allows the position information to vary according to context conditions.
Learning With Errors (LWE) is a very important problem in cryptography and theoretical computer science, proposed by Oded Regev in 2005. The LWE problem can be described as: given a system of linear equations, where each […]
In mathematics, low-rank approximation is a minimization problem where the cost function measures the goodness of fit between a given matrix (the data) and an approximation matrix (the optimization variables), but the rank of the approximation matrix must be reduced.
Knowledge distillation is a machine learning technique that aims to transfer the learnings of a large pre-trained model (the “teacher model”) to a smaller “student model”.
YOLOv10 achieves state-of-the-art performance while significantly reducing computational overhead
Infrastructure as a Service (IaaS) is a cloud computing service that provides the necessary computing, storage, and network resources on a pay-as-you-go basis.
NAS refers to storage devices that connect to a network and provide file access services to computer systems.
Data lakes are different from data warehouses or silos in that they use a flat architecture with object storage to maintain metadata for files.
The General Data Protection Regulation (GDPR) is the strictest privacy and security law in the world.
Hyper Converged Infrastructure (HCI) combines servers and storage into a distributed infrastructure platform, creates flexible building blocks through intelligent software, and replaces traditional infrastructure consisting of separate servers, storage networks, and storage arrays.
Exascale computing refers to computing systems capable of computing at least “10 18 IEEE 754 double-precision (64-bit) operations (multiplications and/or additions) per second (exa FLOPS)” and is a standard measure of supercomputer performance. Exascale computing is computing […]
HyperNetworks is a neural network structure that has some differences in model parameterization compared to traditional neural networks. The paper "HyperNetworks" published by Google Brain in 2016 stated that in HyperNetworks, the model parameterization of the model is different from that of traditional neural networks.
Predictive Coding (PC) is a theoretical framework in cognitive science that holds that the human brain processes cognition through spatiotemporal predictions of the visual world.
The diffusion probability model demonstrates the connection between the diffusion probability model and PC theory.
Future Multi-Predictor Mixture is a model component for time series forecasting that is part of the TimeMixer architecture.
PDM is a theoretical concept for time series forecasting and it is one of the core components of the TimeMixer model.
MRL learns information with different granularities by optimizing nested low-dimensional vectors and allows a single embedding to adapt to the computational constraints of downstream tasks.
Hadoop is an open source framework developed by the Apache Software Foundation for storing and processing large amounts of data on clusters of commodity hardware.
Edge AI refers to the deployment of AI algorithms and AI models directly on local edge devices such as sensors or Internet of Things (IoT) devices, enabling real-time data processing and analysis without constant reliance on cloud infrastructure. Simply put, edge AI refers to the integration of edge computing and human […]
An open source project, product, or initiative embraces and promotes the principles of open communication, collaborative participation, rapid prototyping, transparency, meritocracy, and community-oriented development.
Neuromorphic computing is the process by which computers are designed and built to mimic the structure and function of the human brain, with the aim of using artificial neurons and synapses to process information in this way.
Function calling is a basic concept in programming, which means to perform a specific task by calling a defined function during program execution.
Spiking Neural Network (SNN), at the intersection of neuroscience and artificial intelligence, is a neural network model that simulates the behavior of biological neurons in the brain.
Finite Element Model (FEM) is a numerical calculation method that approximates the physical behavior of an entity by discretizing a continuous physical structure into a finite number of small parts, namely "elements". These elements can be one-dimensional line elements, two-dimensional surface elements, or three-dimensional volume elements.
Contextual position encoding is a new type of position encoding method that allows the position information to vary according to context conditions.
Learning With Errors (LWE) is a very important problem in cryptography and theoretical computer science, proposed by Oded Regev in 2005. The LWE problem can be described as: given a system of linear equations, where each […]
In mathematics, low-rank approximation is a minimization problem where the cost function measures the goodness of fit between a given matrix (the data) and an approximation matrix (the optimization variables), but the rank of the approximation matrix must be reduced.
Knowledge distillation is a machine learning technique that aims to transfer the learnings of a large pre-trained model (the “teacher model”) to a smaller “student model”.
YOLOv10 achieves state-of-the-art performance while significantly reducing computational overhead
Infrastructure as a Service (IaaS) is a cloud computing service that provides the necessary computing, storage, and network resources on a pay-as-you-go basis.
NAS refers to storage devices that connect to a network and provide file access services to computer systems.
Data lakes are different from data warehouses or silos in that they use a flat architecture with object storage to maintain metadata for files.
The General Data Protection Regulation (GDPR) is the strictest privacy and security law in the world.
Hyper Converged Infrastructure (HCI) combines servers and storage into a distributed infrastructure platform, creates flexible building blocks through intelligent software, and replaces traditional infrastructure consisting of separate servers, storage networks, and storage arrays.
Exascale computing refers to computing systems capable of computing at least “10 18 IEEE 754 double-precision (64-bit) operations (multiplications and/or additions) per second (exa FLOPS)” and is a standard measure of supercomputer performance. Exascale computing is computing […]
HyperNetworks is a neural network structure that has some differences in model parameterization compared to traditional neural networks. The paper "HyperNetworks" published by Google Brain in 2016 stated that in HyperNetworks, the model parameterization of the model is different from that of traditional neural networks.
Predictive Coding (PC) is a theoretical framework in cognitive science that holds that the human brain processes cognition through spatiotemporal predictions of the visual world.
The diffusion probability model demonstrates the connection between the diffusion probability model and PC theory.