A group of American scientists discussed the issue of artificial intelligence (AI). The question that a long time ago has not been answered accurately: Is AI different from human intelligence?

Since the beginning of research on this issue of artificial intelligence, movies and media have made AI real, or people can turn it into a movie or media villain pine.

However, the issue of artificial intelligence is still a topic of discussion that is of great interest to scientists. And that’s not part of the conscious life answer either.

At the end of November, AI in the form of ChatGPT – the conversational format – broke free of the sci-fi speculations and labs, and appeared on the desktops and phones of the general public. It’s called creative AI, it can generate an essay or set of shopping recipes. Scientific researchers have marveled at the prospect of perception. As is the case with LaMDA – a serverless service that allows users to execute application code.

And the central issue of all the questions surrounding it is whether AI is different from human intelligence?

What does ‘AI’ really mean?

AI is defined into two categories: artificial narrow intelligence (ANI) and artificial general intelligence (AGI). AGI will work like a human and as of now, AGI doesn’t exist yet. Most of what we call AI today has limited intelligence. To qualify for AI, a system must exhibit some degree of learning and adaptation. Unlike human intelligence, AI intelligence is narrow and effective only to the extent that it was created by humans. Such as fraud detection, facial recognition,…

What AI needs is high-quality data. Research scientists have built neural networks using large data sets. AI also needs a computational infrastructure to train effectively. As computers become more and more advanced, models now require intensive efforts and large-scale computations to be processed. However, as the world around us is constantly changing, AI systems need to be constantly retrained using new data. Without the above important information, AI systems will give incorrect answers in practice or do not take into account new information that has emerged since they were trained.