By integrating an evolutionary genetic algorithm for hyperparameter optimisation, the study achieved marked improvements in model performance and reduced reliance on extensive manual annotations [4].

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even ...

Joint research led by Sosuke Ito of the University of Tokyo has shown that nonequilibrium thermodynamics, a branch of physics ...

Andes AutoOpTune™ uses genetic algorithms to intelligently explore over 280 compiler options and identify the optimal settings based on the user’s goals, whether they are to maximize performance, ...

A common AI fine-tuning practice could be unintentionally poisoning your models with hidden biases and risks, a new Anthropic study warns.

Small grains researcher Juan David Arbelaez-Velez knows the secret to making perfect rice—and it's not about how you cook it.

Despite the AI hype, ML tools really are proving valuable for leading-edge chip manufacturing. More aggressive feature scaling and increasingly complex transistor structures are driving a steady ...

Aware Fine-Tuning of Spiking Q-Networks on the SpiNNaker2 Neuromorphic Platform” was published by researchers at TU Dresden, ScaDS.AI and Centre for Tactile Internet with Human-in-the-Loop (CeTI).

The graph below shows the total number of publications each year in Performance Tuning and Auto-Tuning of Algorithms for GPU Kernels.

Logan Cyr, 16, is researching genetic malformations as part of an intensive science program for teens His project is inspired by his mom's and sister's health struggles and the desire to help ...