Open (and Closed) Data in the Age of AI

Submitted by ogomezal on

The aim of the workshop is to explore what it means to build “cross-experiment multi-modal” foundation models in a landscape where the relevant scientific data can be subject to a range of policies from “open data” to experiment-restricted (either proprietary or limited distribution/raw) data as well as the use of simulations in this context. Similarly, both the data and simulation come with a range of latency/embargo, “initial use vs reuse/reinterpretation” and experiment governance structures. The goal of this workshop is to explore the technical, policy and cyberinfrastructure questions that arise when pursuing such shared models.

Specific questions:

  • What does it actually mean in practice to build a “foundation model” across experiments with different detector designs, data formats, and physics goals?

  • What does it mean in practice to do pre-training on “diverse data” in a shared environment vs fine-tuning in a restricted (experiment) environment?

  • How is benchmarking of the models done? How are the models validated when issues arise spanning the pre-training and restricted fine-tuning?

  • What are the technical and cyberinfrastructure implications?

  • Who owns the resulting models and what are the implications given different experiment governance structures? (And data ownership by international collaborations?)

  • If initially trained on a set of current and archived data, how do these models evolve going forward as new data appears from new experiments/upgrades/detector configurations?

  • If industry is involved in parts of this process, how do we avoid issues related to vendor lock-in and/or retain the “public” expectation that underlies most of the government funding of fundamental science?

 

Live Notes

 

This event is sponsored in part by the National Science Foundation through grants OAC-2226378, OAC-2226379 and OAC-2226380 (FAIROS-HEP) Any opinions, findings, conclusions or recommendations expressed in this material are those of the developers and do not necessarily reflect the views of the National Science Foundation.
Type
Conference
Timezone
US/Central
Category
Workshops
Category ID
16307
Indico iCal
https://indico.cern.ch/export/event/1659498.ics
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End Date