Understanding context factors that influence healthy technology use and understanding the limitations of the current evidence are vital for informing future research. This review demonstrates positive ...

Abstract: Most of the content on various social media platforms has enormous textual data. Before being used in machine learning models, this textual data must be transformed into numerical formats ...

Get started with Java streams, including how to create streams from Java collections, the mechanics of a stream pipeline, examples of functional programming with Java streams, and more. You can think ...

2025 has seen a significant shift in the use of AI in software engineering— a loose, vibes-based approach has given way to a systematic approach to managing how AI systems process context. Provided ...

When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. It continues with an explanation on obfuscation within the Java Edition: "For a long time, Java ...

Creating simple data classes in Java traditionally required substantial boilerplate code. Consider how we would represent Java’s mascots, Duke and Juggy: public class JavaMascot { private final String ...

What if the secret to unlocking the full potential of AI wasn’t in the algorithms themselves, but in how we frame their world? Imagine an AI agent tasked with organizing a massive library of knowledge ...

The Court of Justice of the European Union issued a decision 4 Sept. that provided clarity to the EU General Data Protection Regulation's definition of personal data when it is pseudonymized and where ...

This repository contains an implementation inspired by the ICLR paper on dynamic representation learning and semantic reorganization in graph-based tasks. The implementation features advanced analysis ...

The Model Context Protocol (MCP) is a cutting-edge framework designed to standardize interactions between AI models and client applications. This open-source curriculum offers a structured learning ...

The code generated by large language models (LLMs) has improved some over time — with more modern LLMs producing code that has a greater chance of compiling — but at the same time, it's stagnating in ...