CLAIOct 27, 2022

Towards Language-driven Scientific AI

arXiv:2210.15327v2h-index: 2
Originality Synthesis-oriented
AI Analysis

It addresses the problem of enhancing scientific AI capabilities for researchers, but is incremental as it only identifies and discusses challenges without implementing a solution.

The paper tackles the challenge of designing AI systems for complex scientific discovery by proposing natural language as the core representation and communication medium between AI and human scientists, but does not present concrete results or numbers.

Inspired by recent and revolutionary developments in AI, particularly in language understanding and generation, we set about designing AI systems that are able to address complex scientific tasks that challenge human capabilities to make new discoveries. Central to our approach is the notion of natural language as core representation, reasoning, and exchange format between scientific AI and human scientists. In this paper, we identify and discuss some of the main research challenges to accomplish such vision.

Foundations

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