Prefiguration

Artificial Intelligence (AI) is gaining significant attention for its applications in science, but this workshop will focus on its potential use outside  primary scientific data analysis pipelines, hence the "meta" in AI for meta-science.

This workshop is mainly funded by AISSAI

Several key areas have been identified (work in progress):

• AI for managing the operation of very large  scientific apparatus, such as particle accelerators, telescope or large interferometers used in gravitational wave detection.
• AI for Data Quality Monitoring, which involves overseeing the performance of detectors during data collection and identifying both anticipated and unforeseen failures or anomalies.
• AI for optimizing computing resource management by intelligently pre-loading data and scheduling data processing tasks to maximize throughput.
• AI for enhancing experiment design, including the use of fully differentiable simulators to optimise experiment sensitivity and its integration with generative design techniques in engineering.
  Large Language Models (LLMs) for managing, processing, make available the internal documentation associated with extensive scientific experiments, including, but not only, the software base.
• speculative : AI for scientific discovery, to which extent AI can be used to become a major actor in the scientific process, making hypothesis, connecting insights, designing experiments
• speculative: LLMs for analyzing the dynamics of scientific thought, tracking the emergence and decline of ideas through the study of scientific peer review papers, but also non reviewed documents.

Structure : each theme will be covered in ½ to one day with 45-minute keynote talks and a series of short contributed talks, with ample time for discussion, well suited to Institut Pascal. 

One or two hackathons will take place, on specific themes and data proposed by participants (call for hackathons to be sent).

Contact : David Rousseau, IJCLab, rousseau@ijclab.in2p3.fr