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CRESt – Copilot for Real-world Experimental Scientist

26 October 2023, Version 2
Working Paper
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Autonomous laboratories were previously controlled mainly by scripting languages such as Python, limiting their usage among experimentalists. The recent release of OpenAI's ChatGPT API's function calling feature has enabled seamless integration and execution of Python subroutines in experimental workflows using voice commands. We have developed a system of Copilot for Real-world Experimental Scientist (CRESt) system, with a demonstration shown on YouTube. Large language models (LLMs) empower all research group members, regardless of coding experience, to leverage the robotic platform for their own projects, simply by talking with CRESt.

Keywords

Artificial Intelligence
High-throughput Experiment
Autonomous System

Supplementary weblinks

Title
Description
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Title
CRESt - Copilot for Real-world Experimental Scientists
Description
A video demo of the CRESt system on YouTube
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Version History

Oct 26, 2023 Version 2

Version Notes

Add a chapter describing newly integrated vision capability of CRESt platform

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The content is available under CC BY 4.0 [opens in a new tab]

DOI

10.26434/chemrxiv-2023-tnz1x-v2
D O I: 10.26434/chemrxiv-2023-tnz1x-v2 [opens in a new tab]

Author’s competing interest statement

The author(s) have declared they have no conflict of interest with regard to this content

Ethics

The author(s) have declared ethics committee/IRB approval is not relevant to this content

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