The topic of testing AI and ensuring its responsibility, safety, and security has never been more urgent. Controversy and incidents of AI misuse have increased 26-fold since 2021, highlighting growing concerns. As users quickly find out, AI tools are not infallible; they can make mistakes, display overconfidence, and lack critical questioning. The reality of the market is that AI is prone to error. This is exactly why testing AI is crucial. But how do we test AI?

When you think about improving your website, consider the impact user feedback can have. It comes directly from those who navigate and use your site. Let’s say visitors struggle to find information on your website. They may suggest adding a search function. Implementing their suggestion can dramatically enhance user experience. Such an update can make your site more navigable and efficient. It will allow users to find what they need quickly.

With the ever-increasing pressure to release faster and better due to the growing user expectations about quality, reliability, and zero tolerance for defects, effective test management in the development of applications has never been so critical. Xray is a Jira-native application designed to streamline test management processes within your project management tool.

Many organizations are turning to SharePoint to store their files and share documents. Allowing your systems to access these files might seem like a challenge at first, but with the help of the Microsoft Graph API, you can quickly download the file to start processing on your back-end. Download the example solution to get started. Use the created functions in your solution to simplify Microsoft Graph integration.

Support for model fine-tuning in BigQuery takes input text (the prompt) and the expected output, and teaches the model to mimic the behavior.

Organizations that monitor their LLMs will benefit from higher performing models at higher efficiency, while meeting ethical considerations like ensuring privacy and eliminating bias and toxicity. In this blog post, we bring the top LLM metrics we recommend measuring and when to use each one. In the end, we explain how to implement these metrics in your ML and gen AI pipelines.

Extracting values from server responses is a common operation in scripting scenarios for performance testing. In most cases it is a mandatory step in order to reproduce realistic traffic using dynamic values generated on server side like sessionIds or Tokens. The most known way to extract values is using regular expression. While regular expressions are efficient for raw text-based responses, they are less efficient for structured responses like XML or JSON.

Beginning a career in web design is like setting out on an unforgettable voyage. Your creativity combined with computer knowledge can result in stunning online creations as you use Chrome extensions to your advantage. Like any journey worth undertaking, web designing requires specific tools for success in order for students to thrive while staying entertained throughout.

Over a decade of helping startups improve quality, we’ve arrived at a set of QA testing best practices that work for teams shipping fast and frequently. They fit neatly into five organizing principles: Together, these principles represent The Rainforest Method. We’ve built our QA solution to make it easy for you to put this software testing method into practice and develop a quality product. A few notes: Contents Toggle.