Welcome to AI-Scientist, an open-source initiative focused on revolutionizing scientific research through automation. By harnessing the power of large-language models (LLMs) and other AI modalities, we aim to develop automated frameworks that streamline the research process, improving innovation and efficiency across the scientific spectrum. From literature reviews, hypothesis generation, to experimentation, we aim to develop adaptable and scalable solutions that could drive meaningful scientific progress that benefits society.

Currently, the repository is organized by the functionality of the automated agents/frameworks, we propose the following functionality that preoccupies the day-to-day of many scientists' jobs:

• literature_review: Summarize key findings, synthesize knowledge, and identify emerging trends.
• hypothesis_generation: Leverage data-driven insights and AI models to formulate hypotheses, fostering novel research avenues and accelerating discovery.
• data_analyses: Develop and implement machine learning models and statistical tools flexible to adapt to various datasets.
• results_interpretation: Interpret results in the context of existing knowledge.
• peer_review: Interpret results in the context of existing knowledge.
• multi_function: Execute multiple functionalities required in scientific research. While we envision the eventual AI scientist to be multi-functional, there may be unique advantages to focusing on and evaluating a specific functionality. It is possible and likely that AI-driven scientific processes will differ from human-driven ones (for example, they may not require the same peer review). We shall find out when we get there.

1. Please describe the motivation behind your project
2. Please specify the requirements and installation guide
3. Please include a usage statement

Notable references are documented in Notable References for inspiration.

Join us in our mission to democratize scientific research through AI. Whether you're a scientist, developer, or enthusiast, your contributions can help shape the future of research across disciplines.

We are committed to ensuring the safety and ethical use of these automated agents in scientific research. Contributors are encouraged to consider the implications of their work, particularly in terms of privacy, data security, and the potential impact on society and the environment. We will not accept developments that may lead to harm. All projects here must adhere to best practices and guidelines for ethical AI development and application.

• AutoGPT
• BabyAGI
• LangChain
• AutoGen

AI-Scientist is made available under the MIT License and welcome community contributions.