I’m envisioning a system composed of an “LLM teacher” and a “learning model.” The learning model is organized much like the human brain, with distinct specialized regions. The LLM teacher understands the role of each region and dynamically adjusts their learning intensities during training as needed.
In this architecture, a dedicated memory module—akin to the human hippocampus—is separated out, and by tuning learning strength, the LLM learns to distinguish between memory-based reasoning (non‑hallucinatory answers) and imaginative reasoning (hallucinatory answers).
Right now it’s just an idea and lacks detailed technical specifications, so it may not be practically feasible—but I hope you’ll take it as a fun thought experiment, and I’d love to hear what others think!
I’m not very good at English, so I’m not sure if my idea was conveyed clearly.
In summary, my idea is that the LLM determines which parts of the brain should be activated or deactivated depending on the situation and adjusts the intensity of training accordingly.
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I am conceptualizing a system composed of an “LLM Teacher” and an actual “Learning Model”. The learning model is structured similarly to the human brain, divided into specialized functional areas such as visual processing, language comprehension, and reasoning. The LLM teacher identifies the roles of these different areas and instructs the system on when and which area to activate.
Depending on the type of training data, the neural network adjusts the training intensity across each functional area. Additionally, a dedicated memory area is included, enabling the LLM teacher to review whether certain information has been previously learned or is novel. By selectively adjusting the activation level of this memory region, the system can differentiate between learned knowledge and unlearned content.
Furthermore, by clearly distinguishing whether responses are derived from the memory region or generated without memory assistance, the system could effectively reduce hallucination phenomena.
Although currently at an ideation stage and lacking detailed technical specifications, I would like to discuss and refine this concept further together.