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According to Ruby tradition, the core team will release Ruby 3.4 on December 25—but the preview has been out since May! If you're anticipating the release like we are, you're probably wondering what's new in Ruby 3.4. There aren't any huge changes in this release, but you'll want to be aware of a few really cool things. Let's dig into some of the language changes first.

The demand for food delivery services is skyrocketing, driven by our busy lifestyles and the need for convenience and variety. Apps like Uber Eats, Zomato, and DoorDash have changed how we order food, giving us access to countless restaurant options and smooth delivery experiences. For entrepreneurs, developing an app similar to DoorDash is a great opportunity to tap into this booming market.

Today we’re going to be talking about Strings in Java. If you write Java often, you know that a String is considered a first-class object, even though it is not one of the eight primitive types. What you may not know is how to handle Strings in production applications best. From handling internationalization and localization to optimizing performance for large-scale applications, understanding how to work with Strings can significantly improve code quality and maintainability.

In the dynamic world of mobile app development, the speed and simplicity with which you can share builds with testers and stakeholders can be the difference between a successful, on-time, bug-free release – or watching that opportunity fly by. To help your team maximize all of these opportunities, there’s a new feature within Release Management: Build distribution for testing.

Following the deprecation of Realm, we have partnered with MongoDB to ensure that MongoDB customers can continue to deliver the device sync capabilities their customers depend on. The solution: a MongoDB Connector for the Ably LiveSync product. Ably LiveSync enables you to seamlessly fan-out your MongoDB Atlas state to billions of clients in realtime - ensuring reliable, low-latency delivery of your document data.

What are some common AI/ML use cases? What use cases should business and IT leaders track as they shape a holistic process automation strategy? Let’s find out. Artificial intelligence (AI) refers to computer systems that mimic human thought and decision-making. Within AI, deep learning and machine learning play crucial roles. Deep learning uses neural networks to process large amounts of data and uncover patterns.