What 23 tests reveal about Google AI Max performance

Testing across 16 advertisers reveals how text customization, URL optimization, and account-wide adoption influence AI Max results.
HUB

An efficient, reusable framework to evaluate AI safety

As new large language models, or LLMs, are rapidly developed and deployed, existing methods for evaluating their safety and discovering potential vulnerabilities quickly become outdated. To identify ...
IEEE

A Relay-based Hybrid PSO-Jaya Algorithm for Efficient Test Redundancy Reduction

Abstract: In software development, test redundancy increases resource consumption and execution time. To address this problem, Test Redundancy Reduction (TRR) has emerged as a critical optimization ...
IEEE

Investment Efficiency Prediction and Dynamic Optimization Based on Deep Learning Algorithm

Abstract: Traditional investment efficiency evaluation methods have problems such as low accuracy, slow response speed, and static analysis in terms of multi-dimensional feature processing, dynamic ...