Originally published on Towards AI.

An overview plus examples from the public and private sectors applying cutting-edge LLMs to research and development
Image composed by the author from free screenshots and Dall-E-3 generations. All other figures of this post were generated in similar ways.

In the age of big data and in a highly scientific and technological society where fundamental and applied research advances with huge steps, it is clear that AI has emerged as a crucial tool across various scientific domains, revolutionizing research and development. While I’ve touched on multiple applications of AI models specialized for various tasks in bioinformatics, engineering, etc., I will focus here on something different. I will show you how Large Language Models (LLMs) are reshaping how scientists work, not only regarding the rather obvious applications of LLMs in everyday work but actually having them do science, distill results, run data analysis, etc.

Firstly, LLMs are utilized for processing extensive scientific literature, enabling efficient information retrieval, summarization, and question-answering. From assisting in mining Pubmed articles to summarizing complex scientific concepts for public consumption, LLMs offer unprecedented capabilities in handling vast amounts of textual data. I will overview this with some example apps I’ve made and with a couple of highly capable, paid systems.

Secondly, I will show you how LLMs can be leveraged for the automated processing of scientific texts,… Read the full blog for free on Medium.

Published via Towards AI