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As large language models (LLMs) grow smarter and AI agents gain more tools and capabilities, the responsible development of these technologies becomes paramount. Having worked extensively in both industry and academia, I have observed a significant divide in how responsible AI is prioritized.

Introduction: Academia vs. Industry Perspectives on Responsible AI

Academia tends to approach responsible AI with an idealistic mindset. Students and researchers are taught to embed ethical, legal, and safety considerations into AI systems from day one and throughout the development process. This approach is valuable and ensures the highest standard is achieved. However, it is often impractical in industry settings, where financial pressures and product deadlines demand rapid development and deployment.

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