The intricacy of real-world navigation must be addressed in order to integrate AI into the physical world. Delve into the article to find out how AI can be used to overcome obstacles in the physical world.

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The rapid advancement of artificial intelligence (AI) is revolutionising our lives and work, making processes more efficient. Technologies like large-scale machine learning and natural language processing models, such as ChatGPT, are pushing the boundaries of what was once confined to the realm of science fiction. However, a significant challenge remains in bridging the gap between technical brilliance and real-world application.

While AI has made significant progress in virtual environments, the introduction of AI-powered general-purpose robots in the physical world still faces substantial obstacles. Why is this the case, and how can we address these barriers? We explore the topic in more detail below. 

Energy efficiency stands out as a primary obstacle. At its core, a robot is essentially a self-propelled computer. Anyone who has used a laptop knows that even the best devices struggle to operate for more than a few hours without recharging. With robots, energy demands are even higher due to internal processes and physical movement. Safety considerations prevent them from relying on tethered connections, necessitating extended battery life. 

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