‍McKinsey’s latest research projects that generative AI could contribute between $2.6 trillion and $4.4 trillion annually across various sectors. Experts have also observed that integrating AI-driven automation, threat detection, and low-code platforms redefines next-gen software development. Whether it is code generation, bug fixing, or even designing a new digital component, generative AI is seeping into all product engineering processes.

Developing high-quality products involves careful definition and tracking of both functional and non-functional requirements (NFRs). But what exactly are non-functional requirements? And what's the best way to keep track of them? Let’s dive into what non-functional requirements are and how they compare to functional requirements, review some common types of non-functional requirements with examples, learn best practices for writing them, then discuss how to track and manage them.

Testing tools in AI and data automation have evolved to offer sophisticated features that ensure the quality of the end product and reduce its time to market. With reports suggesting 50% of manual testing being replaced by automated, these tools can help with various aspects of software testing, including unit testing, performance testing, and security testing. They can be integrated practically anywhere across the CI/CD pipeline for continuous testing and shift left testing.

What’s the very first thing that crosses your mind when you hear ‘smart technology’? Well, we 100% agree with you. The way technology is making everything smart, the day is not far when we’ll be able to do everything with just a command. Don’t you agree? With that being said, it’s also not hidden anymore how technology is making our homes smarter and smarter every passing day.

Machine learning APIs provide developers with powerful tools to integrate complex algorithms and models into applications without building them from scratch. These APIs simplify the development process by offering pre-trained models and standardized methods for different tasks. These include image recognition, natural language processing, and predictive analytics. This accessibility democratizes machine learning so that developers of varying expertise can leverage cutting-edge technology efficiently.

‍ A survey suggests that 61% of companies' compliance teams have identified that keeping abreast of upcoming regulatory changes should be a top strategic priority. This indicates that businesses are not only striving to meet current compliance requirements but are also proactively staying ahead of them. However, maintaining such compliance requirements needs tight security strategies.

What comes to mind when you think of an outdated website? Your answer will depend on how far back you’ve seen the internet, but it could range anywhere from glossy interfaces to the default blue, Times New Roman links. But even a few years of age could put your website behind the competition, even if it doesn’t look like MySpace or the first version of IMDB. Its audience and goals could outgrow its design, especially if you don’t make small changes often.

At Snowflake, we are committed to helping customers derive meaningful insights from data with simplicity and speed. That’s why we’re thrilled to announce the general availability of our enhanced RANGE-based window frame, which will help accelerate time-series analytics. For customers across industries, the ability to perform time-series analytics is crucial. This often involves calculating rolling statistics that remain robust despite gaps or nonuniform time-series data.

The total cost of ownership for mobile devices on premises is 2x-5x higher than opting for a cloud infrastructure provider.

DreamFactory's custom SQL endpoints let you create APIs that are tailored to your exact needs, making your data more flexible and powerful. In this article, we will show you how to set up these endpoints, provide practical examples, and explain how to connect endpoints to your external systems.