Enterprises achieve 50% faster testing cycles with AI-driven autonomous quality assurance

Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.
IEEE

Research on SNN Learning Algorithms and Networks Based on Biological Plausibility

Abstract: Spiking Neural Networks, inspired by the brain’s neuronal information processing mech- anisms, utilize sparse, event-based spike signals to emulate biological computation. These networks aim ...
Science Daily

Brain inspired machines are better at math than expected

Neuromorphic computers modeled after the human brain can now solve the complex equations behind physics simulations — something once thought possible only with energy-hungry supercomputers. The ...
Le Lézard

Food Allergy Diagnostics are Enhanced by Machine Learning and Deep Learning AI Models

Both machine learning and deep learning AI models show significant improvements over existing clinical criteria of food allergy diagnostics, according to new research being presented at the 2026 AAAAI ...