Generative AI’s (gen AI) capabilities seemed startlingly novel a year ago, when ChatGPT’s release led to an explosion of public usage and, simultaneously, intense debate about its potential societal and business impacts. That period of initial amazement and suspicion has given way to business urgency, as companies scramble to adopt gen AI in ways that leverage its potential for maximizing workforce productivity and profitability.

Dive into the essentials of DevOps and Mobile DevOps. This blog post covers the DevOps core principles, the differences between DevOps and Mobile DevOps, and the integration of security and engineering practices, alongside answers to common DevOps questions and a glossary of terms.

From personal AI to the data that’ll train it, browse our bets on how AI develops in 2024 and beyond.

Imagine your software transforming from merely a tool into a strategic partner that can automatically alert your users to trends, provide explanations of data with a click, and help you ask the right questions of your data-sets - in addition to delivering data-led insights. This is the power of AI analytics solutions for independent software vendors (ISV). Today's users demand more than just functionality. They crave intelligent software that analyzes data, surfaces insights, and empowers them to act.

In Cloudera deployments on public cloud, one of the key configuration elements is the DNS. Get it wrong and your deployment may become wholly unusable with users unable to access and use the Cloudera data services. If the DNS is set up less ideal than it could be, connectivity and performance issues may arise. In this blog, we’ll take you through our tried and tested best practices for setting up your DNS for use with Cloudera on Azure.

Apple’s App Store has undergone significant changes recently, and savvy iOS developers are working hard to stay ahead of the curve. Together, the recent implementation of the Digital Markets Act (DMA) regulations in the EU and App Store Review Guidelines will reshape the iOS application landscape. While some of these changes pose exciting opportunities, others demand rapid and proactive adaptation.

Artificial intelligence (AI) is rapidly transforming the business world, and Application testing is no exception. AI-powered testing tools can help businesses to automate tasks, improve accuracy, and reduce costs. One of the most important benefits of using AI for Application testing is that it can help automate repetitive tasks. This can free up testers to focus on more complex and strategic tasks. For example, AI can automate creating test cases, executing test cases, and analyzing test results.