Category: AI in Practice
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AI has shown remarkable capabilities in language understanding and generation, but it also has notable weaknesses. Understanding where AI performs well, and where it doesn’t, is crucial for responsible and effective use. Where AI Excels AI systems, particularly large language models (LLMs), shine in: These successes stem from large amounts of training data and extensive…
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Writing effective prompts in languages other than English—like French, Spanish, or Arabic—takes care and precision. Multilingual prompt engineering ensures your AI model understands intent, style, and context in diverse linguistic settings. Why Language Matters in Prompting Multilingual LLMs often perform better when prompts align with their dominant training languages. As research shows, prompts crafted in…
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In our globalized world, many people naturally mix languages in the same sentence—a phenomenon called code-switching. But can AI tools like ChatGPT, Claude, or Gemini handle these mixed-language prompts effectively? Let’s explore how they perform, where they struggle, and what this means for multilingual communication. What Are Mixed-Language Prompts? A mixed-language prompt is a query…
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AI models like GPT‑4 and Claude are powerful—but are they equally effective in English and French? Let’s explore strengths, differences, and what it means in real multilingual use. How AI Performs in English vs French Studies show that GPT‑4 performs similarly in English and French on clinical tasks, with accuracy rates of 35.8% in English…