Natural Language Understanding (NLU) is a critical area of Natural Language Processing (NLP) that enables computers to accurately interpret human language in context. Beyond recognizing individual words, NLU can grasp user intent and emotions, making it applicable to chatbots, voice assistants, sentiment analysis, and more. This enhances conversational AI and data-driven decision-making.

With the advancement of DX, generative AI is now widely used in text creation, customer support, and data analysis, contributing to improved efficiency and competitiveness. However, at the same time, a serious issue known as “hallucination” has emerged—when AI generates information that appears plausible but is in fact incorrect.

In today’s digital society, high-quality images are indispensable—from Instagram posts to web banners, game characters, and advertising posters. However, traditional production required specialized skills and significant costs, creating major barriers. This is where “Image Generation AI” comes into the spotlight. By simply entering text or a simple prompt, users can instantly generate professional-level visuals. For example, marketers can create advertising materials in seconds, and artists can easily experiment with new styles.

AI agents are gaining attention as powerful tools for automating and streamlining operations. For technology-driven companies in particular, reducing repetitive tasks, accelerating data analysis, and enhancing customer support are critical to boosting competitiveness. However, many organizations face challenges such as “where to start” and “how best to deploy them” when considering adoption.

With the evolution of AI technologies, AI agent tools are becoming essential drivers of business process automation and operational efficiency.

Especially for technology-driven companies, reducing repetitive tasks, enhancing data analysis, and strengthening customer support are crucial sources of competitive advantage.

However, with so many tools available, selecting the one best suited to your organisation—and implementing it effectively—is no easy task.

Artificial intelligence (AI) continues to evolve to meet a wide range of modern-day needs—workflow automation, data analysis, customer support, and more. Among the newest entrants, Claude, developed by Anthropic, has attracted attention as a large-language model (LLM) that prioritizes safety and ethics through a unique “Constitutional AI” approach. Competing with ChatGPT and Gemini, Claude positions itself as a highly trustworthy option for enterprises and researchers alike.