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Top AI Automation Testing Tools 2024

Ever since we have entered the third decade of the 21st century, artificial intelligence has proven to be the driving force behind innovation. However, the growing need for technology and constant development demands access to rapid testing and quality assurance. Besides, the software testing landscape is undergoing a revolutionary transformation, as we hurtle into a tech-driven era. It means AI-powered tools are being tested using the power of AI automation testing tools.

Kong Mesh 2.5: Tailored Use Cases for an Elevated Experience

The latest release of Kong Mesh (version 2.5) brings many new features that push the envelope and make Kong Mesh the logical choice of a service mesh to meet your objectives. In this blog, we'll break down these new features and provide tailored use cases to illustrate how Kong Mesh 2.5 can elevate your service mesh experience. We'll focus on three main categories: flexibility, resiliency, and security.

How to Handle CSV Files Over SFTP: Best Practices

Secure File Transfer Protocol (SFTP) stands as a robust protocol at the disposal of businesses, offering enhanced collaborative capabilities, operational efficiency, and heightened security for confidential data. Using SFTP, organizations can confidently exchange files among users and locations, irrespective of device variations. This adoption contributes to increased productivity levels and improved security around sensitive data, shielding it from unauthorized breaches.

Scaling MLOps Infrastructure: Components and Considerations for Growth

An MLOps platform enables streamlining and automating the entire ML lifecycle, from model development and training to deployment and monitoring. This helps enhance collaboration between data scientists and developers, bridge technological silos, and ensure efficiency when building and deploying ML models, which brings more ML models to production faster.

Private vs. Internal APIs: Similarities and Differences

Private APIs vs. internal APIs – at first glance, they might seem synonymous, given their non-public nature. However, delving deeper reveals unique characteristics and purposes for each. As with any technical concept, a clear understanding is key to harnessing its full potential. To help navigate this intricate landscape, this article aims to demystify these terms, shedding light on their similarities and, more importantly, their differences.

Managing PDFs in Node.js with pdf-lib

In today's digital age, Portable Document Format (PDF) files have become an integral part of how we share and manage documents. Regardless of whether it's contracts, reports, or presentations, PDFs provide a consistent and reliable way to present information across different platforms and devices. As developers, being able to manipulate and generate PDFs programmatically is a valuable skill. This is where the pdf-lib library for Node.js comes into play.

Building Efficient Data-Driven Apps: A GraphQL Tutorial for iOS App Developers

GraphQL is a query language and runtime for APIs, developed by Facebook in 2012 and later open-sourced in 2015. And it has changed the way we fetch data from our server. Typically, most front-end clients – like React, Angular, Vue, or mobile apps like iOS and Android – use REST APIs to fetch data from the server. REST APIs require more HTTP calls than GraphQL, which leads to over and underfetching.

Generative AI in Insurance: How is Generative AI Helping in Risk Assessment and Claim Processing

Generative artificial intelligence represents a category of AI that utilizes generative models to produce text, images, or other forms of media. These models grasp the intricacies and structure of their input training data, enabling them to generate new data with similar characteristics. In insurance, generative AI plays a pivotal role in expediting digitization processes.

The latest Tricentis Testim release boosts testing power and stability through AI and ML

We are thrilled to introduce the latest updates to Tricentis Testim, bringing exciting new capabilities across the Testim platform. In this update, generative AI makes finding answers to your questions easier, mobile test authoring and execution in the cloud becomes completely seamless and zero-footprint, and test cases become even more stable using Machine Learning (ML) locators.