Difference between revisions of "Science Agents"

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(Regression (Data Fitting))
(Science Agents)
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* 2024-12-06: [https://www.biorxiv.org/content/10.1101/2024.11.11.623004v1 The Virtual Lab: AI Agents Design New SARS-CoV-2 Nanobodies with Experimental Validation] (writeup: [https://www.nature.com/articles/d41586-024-01684-3 Virtual lab powered by ‘AI scientists’ super-charges biomedical research: Could human–AI collaborations be the future of interdisciplinary studies?])
 
* 2024-12-06: [https://www.biorxiv.org/content/10.1101/2024.11.11.623004v1 The Virtual Lab: AI Agents Design New SARS-CoV-2 Nanobodies with Experimental Validation] (writeup: [https://www.nature.com/articles/d41586-024-01684-3 Virtual lab powered by ‘AI scientists’ super-charges biomedical research: Could human–AI collaborations be the future of interdisciplinary studies?])
 
* 2024-12-11: Google [https://blog.google/products/gemini/google-gemini-deep-research/ Deep Research]
 
* 2024-12-11: Google [https://blog.google/products/gemini/google-gemini-deep-research/ Deep Research]
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* 2024-12-30: [https://arxiv.org/abs/2412.21154 Aviary: training language agents on challenging scientific tasks]
  
 
=AI Science Systems=
 
=AI Science Systems=

Revision as of 15:49, 31 December 2024

AI Use-cases for Science

Literature

AI finding links in literature

Autonomous Ideation

Adapting LLMs to Science

AI/ML Methods tailored to Science

Regression (Data Fitting)

Symbolic Regression

Literature Discovery

Commercial

AI/ML Methods co-opted for Science

Mechanistic Interpretability

Train large model on science data. Then apply mechanistic interpretability (e.g. sparse autoencoders, SAE) to the feature/activation space.

Uncertainty

Science Agents

AI Science Systems

Inorganic Materials Discovery

Chemistry

Impact of AI in Science

Related Tools

Data Visualization

See Also