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Use Case

Automated scientific research papers

Generative AI models like Language Models (LLMs) and image generators stand to revolutionize automated scientific research. Tools like OpenAI’s GPT-3 and AI image generators can generate new scientific hypotheses, design experimental protocol and write research papers. For instance, GPT-3 can suggest potential avenues for investigation based on given dataset; it could look for factors influencing a disease’s incidence or predict the properties of a new material. Additionally, an AI image generator can be used to create visual representations of these findings, producing diagrams or graphical abstracts. Moreover, once the research is complete, LLMs can draft the research paper itself. This includes creating summaries, abstracts, and even generating citations. In this way, generative AI models can automate most stages of the scientific research process, potentially accelerating scientific innovation.

How to build with Clevis

Text Input

Enter the topic of the research paper

HTTP Request

Fetch related research papers from an academic database API

Prompt ChatGPT

Prompt ChatGPT to summarize the fetched research papers

Generate Image (DALL-E)

Generate an image visualizing the main findings of the research

Display Output

Display the summarized research papers and the generated image

In this example, Clevis is used to create an Automated Scientific Research Papers application. The user initiates the process by entering the topic of their research paper. The system then uses an HTTP Request to gather related academic papers from an API specially created for accessing a scientific research papers database.

After gathering the papers, the application leverages OpenAI's ChatGPT in the next step to digest and summarize the collected data. Summarizing the research papers makes it easier for users to understand and assimilate the central ideas of the fetched materials without having to go through every detail.

Once summarized, DALL-E, another model by OpenAI, is used by the application to create a visual depiction of the main findings, thus facilitating an even easier comprehension of the topic for the user.

The final step in the process involves displaying the summarized research papers alongside the image that was generated. All these tasks are automated and the interface is user-friendly.

Building apps within the scientific research realm using Clevis becomes quite straightforward with this configuration, making it an excellent tool for such use cases.

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