  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 models.
Customization comes in the form of prompt-tuning, analysis of reference
resources, browsing, and external API interactions, alongside a promise of
revenue sharing for created custom GPTs. In this work, we peer into the window
of the GPT Store and measure its impact. Our analysis constitutes a large-scale
overview of the store exploring community perception, GPT details, and the GPT
authors, in addition to a deep-dive into a 3rd party storefront indexing
user-submitted GPTs, exploring if creators seek to monetize their creations in
the absence of OpenAI's revenue sharing.
