Systems | Development | Analytics | API | Testing

Every company around the globe is trying to get in on the GenAI wave to simplify user experiences with natural language. And this is especially true in the realm of data and analytics. Imagine if you could enable all of your marketers to evaluate the performance of their campaigns with a simple question? Or, if you could provide all of your insurance risk managers with the ability to analyze the risk profile of their claims with the power of search and automated insights?

Back in August, SmartBear acquired Stoplight, a leader in API design and documentation. Since this acquisition, our focus has been on seamlessly integrating Stoplight's open-source tools—Spectral, Elements, and Prism—into SwaggerHub. Our goal is to simplify complex API development tasks and address the common challenges encountered in API development.

Grape is a popular Ruby framework for building RESTful APIs. Exception handling plays a crucial role in ensuring the stability and reliability of any application, including those made with Grape. This article will explore the basics of Grape exception handling, including customizing exceptions. We'll also touch on some best practices, and how to integrate your app with AppSignal for enhanced error monitoring and management. Let's get started!

Data lakes can save your enterprise money but come with unique challenges. These tips will help you overcome three of the biggest issues.

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.

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.

Today Snowflake is launching and open-sourcing with an Apache 2.0 license the Snowflake Arctic embed family of models. Based on the Massive Text Embedding Benchmark (MTEB) Retrieval Leaderboard, the largest Arctic embed model with only 334 million parameters is the only one to surpass average retrieval performance of 55.9, a feat only less practical to deploy models with over 1 billion parameters are able to achieve.

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.