# GPT is all you need

## TL;DR

This paper discusses how GPT models like ChatGPT may influence human cognition and learning, proposing new concepts like multi-modal GPT and Hybrid AGI.

## Contribution

The paper introduces theoretical mechanisms and future research directions for GPT's impact on cognition, including the concept of Hybrid AGI.

## Key findings

- GPT may support structured thinking and interdisciplinary learning through cognitive frameworks like Cognitive Load Theory.
- The paper outlines limitations such as hallucination and surface-level learning, alongside practical recommendations for users and developers.

## Abstract

The advent of Generative Pre-trained Transformer (GPT) models, exemplified by systems like ChatGPT, has begun to reshape how humans think, learn, and interact. This paper explores GPT's role as a cognitive scaffold, supporting structured thinking, conversational agility, emotional regulation, and interdisciplinary learning. Grounded in established psychological frameworks—Cognitive Load Theory, Social Cognitive Theory, and Zone of Proximal Development—this work proposes theoretical mechanisms through which GPT may influence cognition, including neuroplasticity, meta-cognition, and implicit learning. While these claims remain speculative, the paper outlines future research pathways for empirically testing GPT's long-term cognitive impacts. It also introduces the concepts of multi-modal GPT and Hybrid AGI, defined as human-AI symbiosis systems that may extend cognition through sensory integration and co-adaptive learning. Limitations such as hallucination, surface-level learning, and cognitive overreliance are critically examined, alongside practical recommendations for educators, users, and developers. By offering a conceptual foundation and forward-looking agenda, this paper aims to catalyze interdisciplinary dialogue on GPT's evolving role in human cognition and learning.