As artificial intelligence continues to evolve, we’re witnessing a shift from passive language models to agentic AI systems—autonomous programs that can perceive, plan, and act in dynamic environments. These AI agents are capable of executing complex tasks independently. (If you're unfamiliar with this concept, check out our article for a quick introduction.)

Rapid advancements in artificial intelligence technologies have ushered in a new approach that goes beyond traditional systems: AI agents. These autonomous software systems represent a form of AI that not only responds to commands but can also perceive its environment, make decisions, and act upon them.

The United Kingdom’s Information Commissioner’s Office (ICO: Information Commissioner’s Office) examined the future through its Tech Horizons report, published on 20 February 2025. The report scrutinizes four key technologies expected to impact our lives within the next 2–7 years.

In this article, aimed at technology enthusiasts, data protection professionals, and developers, we will closely analyze the opportunities offered by each technology and the accompanying responsibilities regarding data protection and privacy—all based on the data presented in the report.

The development of video games continues to accelerate as technology advances daily. One of the most crucial elements enriching the storyline and offering diverse interaction options for players is NPCs (Non-Player Characters), which are characters not controlled by the player. This article explores the origins and evolution of the NPC concept, from its inception to its transformation through artificial intelligence.

A Deep Dive

As of 2024, generative artificial intelligence (GenAI) has transcended its role as merely an "assistive tool" to become an indispensable part of professionals' daily workflows in creative industries. Creative professionals are now leveraging these technologies to produce more engaging and innovative content.

Natural Language Processing (NLP) and Natural Language Generation (NLG) are subfields of AI focused on enabling machines to understand and generate human language. NLP improves machines' abilities to analyze and interpret human language, while NLG allows them to produce fluent and meaningful language. These two fields together enable human-machine interaction to become more intuitive.