Artificial Intelligence has become a household word and has brought great benefits to many people. With its many models, AI is undoubtedly the most important technological development in decades, enhancing work efficiency and assisting us in our daily activities. However, despite these advances, AI will never surpass the capabilities of the human brain.
To understand the relationship between the real world and AI, a study by Dr. Stuart Wilson and Professor Tony Prescott of the University’s Department of Computer Science concluded that no matter how much AI evolves, it will not be able to catch up with humans. – As knowledge.
Since the emergence of models such as ChatGPT and Dall-E, our lives have become easier, they have increased the efficiency of our work, in terms of assistance in studies, daily tasks, office work. However, it should be noted that these models rely on large neural networks to complete tasks that mimic human-generated responses. However, researchers at the University of Sheffield have pointed out that there are natural differences that prevent AI from thinking like a human.
To add to it, two crucial differences have been highlighted. First, the human mind is directly connected to physical bodies, enabling direct perception and interaction with the real world. This difference plays an important role in distinguishing AI from the human brain. Moreover, our brain is built in a special architecture, that is, not in AI models. According to the study, AI can learn complex patterns from data, but it lacks the connection to the real world, which plays an important role in thinking.
But the real question is, will AI evolve to think like the human brain? Professor Tony, an expert in cognitive robotics at the University of Sheffield, believes that if AI continues to develop at its current rate, it will be impossible to achieve human intelligence. However, there are ways AI can achieve human-like thinking, such as equipping cameras, microphones, and other sensory devices. It’s good to see that progress is being made in developing AI intelligence using recurrent neural network models that can make more accurate predictions about the future.
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