Leveraging Codezero can significantly benefit AI developers in building better, larger, and more sophisticated models through its suite of features designed to simplify and secure microservices development. By addressing common challenges in AI model development, such as environment consistency, collaboration, scalability, and security, Codezero provides a conducive environment for innovation and efficiency. Here’s how AI developers can harness Codezero for these advantages.

Some mobile app development teams today are still dealing with the challenges of maintaining physical/on-premises real devices for mobile app testing. This blog post makes the case for moving real device testing to the cloud.

This article was origninally published here. In this article, we’re spilling the beans on why we switched from Azure to Codemagic and showing you exactly how to supercharge your CI/CD game. We’re covering the entire spectrum — from compiling and creating release notes to testing and deployment. Let’s rewind a bit to our iOS developers’ struggles. Our CI process (think builds, tests, and coverage) was taking a chunky 40–50 minutes.

Introducing new BigQuery SQL features for performing two of the most common time-series operations: windowing and gap filling.

You can now unpack the Christmas present that was promised to you at the end of 2023! As you may have already read in the Flamegraph Feature Preview, this exciting new feature of the Profiler is now the focus of our first release in 2024. The Flamegraph complements the Timeline and Callgraph features and visualizes Aggregated Traces. The goal was to provide profiling information across many traces and thereby gaining new and deeper insights into performance.

According to Gartner’s Top Priorities for Customer Service Leaders -2024 – Three priority areas are Self Service, Gen AI, and Customer Journey Analytics. When delved into the primary concern, it became apparent that many customers abandon product or service issues rather than seek agent assistance if online solutions are unavailable. Additionally, a notable proportion of Millennials and Gen Z adhere to a “self-service or no service” mindset.

In this article, we present some best practices and key concepts for using Confluent Schema Registry.

Headline: The transition to Codemagic made our CI builds faster and more reliable and positively impacted the experience of contributors contributing to our open-source project, Tuist. Thanks to Codemagic’s support, we can bring new free goods to the Swift community and the ecosystem of app developers.

In this blog series, I am exploring the “sliding doors”, or divergent paths, for creating value with data across different use cases, practices, and strategies. In this post, I want to discuss how to generate value with Data Products. As I reviewed in my last blog, grabbing the door to the better path for managing your data isn’t just about solving your particular use case: it’s ultimately about delivering value for your business.

Having frequently worked with governments around the world over the course of my career, I’ve had all kinds of discussions about the global impact of generative AI. Today, I’m publicly wading into those waters to deliver my perspective, and my opinion is that … it’s incredibly hard to predict the future. Done. Wrapped up this entire post in a single sentence.