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.
CargoForwarder Global

Automating Air Cargo: Robo-Ops – Part 2

In Part 1 of our 3-part series on air cargo automation, Manuel Wehner (MW), Project Manager and Research Associate at the Fraunhofer Institute for Material Flow and Logistics IML, touched on the ...
GitHub

Python library for interacting with the Solvecaptcha API (captcha-solving service)

A simple and efficient method to integrate the Solvecaptcha captcha-solving service into your code, enabling the automation of solving various types of captchas. Examples of API requests for different ...
Wired

ICE Is Using Palantir’s AI Tools to Sort Through Tips

United States Immigration and Customs Enforcement is leveraging Palantir’s generative artificial intelligence tools to sort and summarize immigration enforcement tips from its public submission form, ...
IEEE

Adaptive Random Testing of Deep Learning Systems Using Image Hashing

Abstract: In recent years, deep learning (DL) systems have been applied in many areas, including image processing and autonomous driving. Software testing is an important way to ensure the quality of ...
IEEE

Comparing the Adaptability of a Genetic Algorithm and an LLM-Based Framework for Automated Software Test Data Generation: In the Context of Web Applications

Abstract: In the fast-paced world of software development, ensuring software quality is paramount. Software Quality Assurance (SQA) plays a vital role, primarily through testing, which can be carried ...