Summary of Understanding Biology in the Age Of Artificial Intelligence, by Elsa Lawrence et al.
Understanding Biology in the Age of Artificial Intelligence
by Elsa Lawrence, Adham El-Shazly, Srijit Seal, Chaitanya K Joshi, Pietro Liò, Shantanu Singh, Andreas Bender, Pietro Sormanni, Matthew Greenig
First submitted to arxiv on: 6 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper discusses the intersection of artificial intelligence (AI) and life sciences, particularly the use of machine learning (ML) models in biological research. While ML is useful for identifying patterns in large data sets, its widespread application in biology deviates from traditional methods of scientific inquiry. The authors examine recent applications of ML in biological sciences through an epistemological lens, drawing on philosophical theories of understanding to guide the design and application of ML systems. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper explores how AI can help us better understand living things. It looks at two areas where AI has been used: predicting protein structures and analyzing single cells’ genetic material. The authors discuss how these approaches have helped scientists learn more about biological systems, what obstacles remain, and how we can improve the use of AI in biology. |
Keywords
» Artificial intelligence » Machine learning
