# Survey of Artificial Intelligence Model Marketplace
## 2 AI Marketplace Overview
### Marketplace for Existing AI Models
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Type** & **Features** & **GenAI Models** & **Model Example** & **Price** \\ \hline \multirow{3}{*}{Text-to-Text} & input: text, & \begin{tabular}{c} Variational Autoencoder (VAE), \\ Transformer-Based Models \\ (TBM), Large Language Models \\ (LLM) \\ \end{tabular} & \begin{tabular}{c} ChatGPT (OpenAI), \\ Gemini (Google) \\ \end{tabular} & \begin{tabular}{c} ChatGPT ($20.00/month), \\ Gemini($20.00/month) \\ \end{tabular} \\ \hline \multirow{3}{*}{Text-to-Images} & input: text, & \begin{tabular}{c} Generative Adversarial \\ Network (GAN) \\ \end{tabular} & DALLE & \$20.00/month \\ \cline{2-5}  & \begin{tabular}{c} Input: text, \\ output: videos \\ \end{tabular} & Diffusion Models (DM) & Adobe Premiere Pro, SORA & Adobe ($20.99/month), \\ \hline \multirow{3}{*}{\begin{tabular}{c} Code \\ Generation \\ \end{tabular} } & input: text, & \multirow{3}{*}{TBM} & \begin{tabular}{c} Genimi (Google), ChatGPT \\ (OpenAI), Claude \\ (Claude.ai), etc. \\ \end{tabular} & \begin{tabular}{c} Genimi ($20.00/month), \\ ChatGPT ($20.00/month), \\ Claude Pro ($20.00/month) \\ \end{tabular} \\ \cline{1-1} \cline{2-5}  & \begin{tabular}{c} Input: text, \\ output: Website \\ \end{tabular} & VAE & \
\begin{tabular}{c} Frame \\ \end{tabular} &
\begin{tabular}{c} Frame \\ \end{tabular} ($10.00/month) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: An overview of generative AI applications. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  
Our study employs a three-dimensional problem space as Figure 2 to explore the potential for leveraging existing AI models with commonly shared functional capabilities. The analysis focuses on variations in data resources, potential hardware investment requirements, and labor resource utilization, highlighting the feasibility and implications of these factors in optimizing AI model deployment. For example, ChatGPT 3.0 is a text-to-text GenAI. Based on the problem space designed for the existing AI models marketplace (Figure 2), the data type is text only. The data acquired is public. The GenAI model uses VAE, TBM, and LM; therefore, the training AI model needs a large dataset. According to ChatGPT published data, for ChatGPT3, the pertaining dataset size is 45 TB [71]. Due to the extensive data requirements, ChatGPT relies on GPUs and ASICs to enable rapid response times and manage large-scale language processing tasks. Significant computational resources and multiple AI models are employed to fulfill performance requirements. Suppose a new AI product with similar functionality to ChatGPT is introduced. In that case, pricing for this model can be benchmarked against ChatGPT's current pricing, such as a monthly subscription, which is recommended for the GenAI model itself. A model developed on top of ChatGPT, the recommended selling price would reflect ChatGPT's base price plus an additional amount for any newly introduced features. AI marketplace focused on promoting existing AI models should provide services with general tasks such as ChatBots to answer customer questions, HR products to predict