Microsoft Research proposes energy-efficient time series predictions using spiking neural networks
Spiking neural networks (SNNs), a family of artificial neural networks that mimic the spiking behavior of biological neurons, have been ...
Tag: networks
Palo Alto Networks price target raised, CrowdStrike cut at Susquehanna
Michael Vi/iStock Editorial via Getty Images Susquehanna reviewed the target prices of several tech stocks, including CrowdStrike (NASDAQ: CRWD) and ...
What if game engines could be powered by neural networks? This Google AI paper introduces GameNGen and explores how diffusion models are revolutionizing real-time gaming
A major challenge in ai-powered game simulation is the ability to accurately simulate complex interactive environments in real-time using neural ...
From text to networks: the revolutionary impact of LLMs on knowledge graphs | by Lina Faik | August, 2024
Illustration by the authorA step-by-step guide to creating and leveraging knowledge graphs with LLMIThe rise of large language models (LLMs) ...
Ethereum Layer 2 Networks Hit New Record with 12.42 Million Daily Transactions
ethereum layer 2s are abuzz with activity. The latest data suggests that the ecosystem has hit a new record in ...
Vitalik Buterin believes Ethereum layer 2 networks are close to solving the interoperability problem
<img src="https://cryptoslate.com/wp-content/uploads/2024/04/ethereum-layer2.jpg" />ethereum co-founder Vitalik Buterin predicts a quick resolution of Layer 2 interoperability issues within the ethereum ecosystem.Buterin said ...
Revealing the utilized range of learning subspaces in neural networks
In this work, we study how well the learned weights of a neural network utilize the space available to them. ...
What are neural networks with radial basis functions?
Introduction Radial basis function neural networks (RBFNNs) are a type of neural network that uses radial basis functions for activation. ...
Hyperparameter tuning in neural networks
Hyperparameters determine how well your neural network learns and processes information. Model parameters are learned during training. Unlike these parameters, ...
History of Convolutional Neural Networks for Image Classification (1989-present) | by Avishek Biswas | June, 2024
A visual tour of the greatest innovations in Deep Learning and Computer Vision.Before CNNs, the standard way to train a ...
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