Researchers have developed a transfer learning-enhanced physics-informed neural network (TLE-PINN) for predicting melt pool morphology in selective ...

Embedl Turbocharges Kodiak's GenAI Edge Deployment (Figure 1) The subsequent optimization with the Embedl SDK resulted in dramatically faster inference speeds. Autonomous trucking leader Kodiak ...

Abstract: Graph Neural Networks (GNNs) have exhibited exceptional performance ... for adversarial training of GNNs through an optimization framework which provides attack agnostic robustness. By ...

In the domain of neural computation, Spiking Neural Networks (SNNs) are distinguished by their unique, biologically informed ...

Abstract: A circuit-informed neural network (CINN) is proposed for broadening the bandwidth ... The CINN significantly reduced the computational costs on optimization, dataset construction, and ...

BY Mila Simmons In the rapid development of cloud computing technology, resource management and optimization have become ...

But Threads isn’t Twitter, and it’s never going to be. Twitter was never the biggest or most successful social network — far from it — but Twitter was at the absolute epicenter of culture ...

In other words, games that are no longer rendered by a traditional 3D pipeline, but fully rendered by neural networks. The technology could arrive with Blackwell, a new graphics architecture that ...

The question then becomes: How can we make prompt optimization faster, more accessible, and more adaptable across diverse tasks? PromptWizard (PW) is designed to automate and simplify prompt ...

Universal Transformer Memory uses neural networks to determine which tokens in the LLM's context window are useful or redundant.