21 August 2024
21 August 2024
Neil Lawrence and Jessica Montgomery have published Accelerating AI for science: open data science for science in Royal Society Open Science.
High-profile results, such as protein-structure prediction, show what AI can do inside a domain. The path from those results to routine use across the sciences is not a straight line. The paper argues for a diffusion engine: supply chains of ideas between disciplines, open research that moves capabilities quickly, tools that researchers can wield themselves, and data stewardship that makes reuse possible. Together those interventions are what the authors call open data science for science.
The article develops the agenda set out in the 2023 Dagstuhl report, AI for Science: an emerging agenda, and the practice of the Accelerate Science programme. It is available at doi:10.1098/rsos.231130.
7 June 2022
The Accelerate Science Programme and education technology company Cambridge Spark are offering researchers across Cambridge University a new self-learning module so they can learn programming in Python.
5 July 2022
(5 July 2022) The Accelerate Programme in collaboration with C2D3 is offering small grants for Cambridge University researchers pursuing innovative applications of AI, in research or real-world contexts. Funding can support a variety of activities, including events, workshops, teaching, software development, or research, with a focus on interdisciplinary collaboration.
8 March 2023
A report from Dagstuhl Seminar 22382 sets out how machine learning and domain science can work together on complex scientific systems.
