How would you compare the "thinking" of GPT-5 to the human brain?
Introduction
Have you ever had a conversation with an AI and felt that it was thinking like a human being? Especially with modern language models like GPT-5, it responds more "like it understands" than before.
So - how would this "thinking" be compared to the human brain? In this article, we will look at the structure of GPT-5 thinking from the perspective of brain science.
---In this article, we will look at the structure of GPT-5 thinking from the perspective of brain science.
Does GPT-5 have a "brain"?
First of all, GPT-5 does not have a "brain" or "consciousness" like humans. However, its information processing mechanism is similar to that of the brain.
● Neurons = Artificial Neurons
The human brain contains about 86 billion neurons (nerve cells), which exchange information via electrical signals. In the same way, GPT-5 has hundreds of billions of "artificial neurons (nodes)" that are connected in a layered fashion to process input sentences in a multilayered manner.
● Synapses = weighting
In the brain, the strength of the synapses that connect neurons changes with learning. Similarly, in AI, a value called weight is adjusted to increase the accuracy of the output. In other words, GPT-5 has a structure similar to the "brain that gains experience by adjusting weights.
--- GPT-5
How would you describe GPT-5's "thinking" in terms of the brain?
Let's divide the human brain into four regions and consider the function of GPT-5 corresponding to each region.
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Prefrontal cortex (thinking and judgment) → Reasoning layer of GPT-5. This is the part that understands the context of a conversation and selects "what words to say next. It plays a role similar to that of human logical thinking.
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Hippocampus (memory and learning) → Learning data and weights. GPT-5 learns a large amount of text and stores language "memories" in its weights. It is a bit like human experiential memory, but without the emotion and subjectivity.
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Temporoparietal Junction (understanding others) → Context Awareness. The GPT-5 "context understanding" corresponds to the human theory of mind (the ability to read the thoughts of others). It responds by inferring the flow of the conversation and the intent of the other person's questions.
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Cerebellum (adjustment and fine-tuning) → Token control and mode of thinking. GPT-5 enables fine adjustment of output, such as "balance mode" and "thinking mode. This function is similar to "sensory fine-tuning" in humans.
---The GPT-5 can also be used as a "thinking mode" or "balance mode.
Difference between GPT-5 and human "thinking
Although there appear to be similarities, there are some critical differences.
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① Emotionless. GPT-5's "empathy" is an imitation derived from learning data. GPT-5's "empathy" is a mimicry derived from learning data; it does not feel emotions, but only chooses expressions that appear emotional.
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② No awareness or purpose. Humans think with the intention of "wanting to do this," but GPT-5 only probabilistically calculates the optimal output for the input. Spontaneous decision-making does not exist.
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③ Memory is temporary. GPT-5's "conversational memory" is only for the duration of the session, and does not retain long-term memory like the brain does. However, in some environments, continuous learning is becoming possible using the "memory function.
---...
Why do we still "seem" to think?
The reason GPT-5 seems to think like a human is that it is highly predictive of word patterns and context. This "linguistic simulation" is similar to the process by which humans externalize thoughts in conversation.
To use an analogy,
GPT-5 reproduces human "verbalization of thoughts" as "verbalization of thoughts".
As a result, we perceive GPT-5 as "seeming to think.
--- (emphasis added)
Summary: AI "thinking" and the future of human understanding
GPT-5 handles language in a structure similar to the human brain, GPT-5 handles language with a structure similar to that of the human brain, but it does not have fundamental elements such as "emotion" and "consciousness.
Nevertheless, through the AI's thinking model Nevertheless, through the thinking model of AI, we may be given an opportunity to rethink our own "thinking mechanism".
Understanding AI will eventually lead to "understanding human thinking.
-> Understanding AI will eventually lead to "understanding human thinking.
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