GPTs Window Shopping: An analysis of the Landscape of Custom ChatGPT Models
Benjamin Zi Hao Zhao, Muhammad Ikram, Mohamed Ali Kaafar

TL;DR
This paper analyzes the landscape of custom ChatGPT models on the GPT Store, examining community perceptions, model details, and monetization efforts, highlighting the impact of user-driven customization in the LLM ecosystem.
Contribution
It provides a large-scale overview of the GPT Store, including community insights, model characteristics, and an analysis of third-party storefronts and creator monetization strategies.
Findings
Community perception of custom GPTs is generally positive.
Many creators seek to monetize their GPTs independently.
The third-party storefront hosts a diverse range of user-submitted GPTs.
Abstract
OpenAI's ChatGPT initiated a wave of technical iterations in the space of Large Language Models (LLMs) by demonstrating the capability and disruptive power of LLMs. OpenAI has prompted large organizations to respond with their own advancements and models to push the LLM performance envelope. OpenAI has prompted large organizations to respond with their own advancements and models to push the LLM performance envelope. OpenAI's success in spotlighting AI can be partially attributed to decreased barriers to entry, enabling any individual with an internet-enabled device to interact with LLMs. What was previously relegated to a few researchers and developers with necessary computing resources is now available to all. A desire to customize LLMs to better accommodate individual needs prompted OpenAI's creation of the GPT Store, a central platform where users can create and share custom GPT…
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Taxonomy
TopicsArtificial Intelligence in Healthcare and Education · Machine Learning in Healthcare
